8_protein_data_acquisition_from_PDB.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMqOhIzK5MkMRzBFNu9Dd02",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "07cb09ced350422ba5c9c11360331e3e": {
          "model_module": "nglview-js-widgets",
          "model_name": "ColormakerRegistryModel",
          "model_module_version": "3.0.6",
          "state": {
            "_dom_classes": [],
            "_model_module": "nglview-js-widgets",
            "_model_module_version": "3.0.6",
            "_model_name": "ColormakerRegistryModel",
            "_msg_ar": [],
            "_msg_q": [],
            "_ready": true,
            "_view_count": null,
            "_view_module": "nglview-js-widgets",
            "_view_module_version": "3.0.6",
            "_view_name": "ColormakerRegistryView",
            "layout": "IPY_MODEL_3d2d3c20fdff4631b060a5f2620f289a"
          }
        },
        "3d2d3c20fdff4631b060a5f2620f289a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "d9d0bb310e9b4be594e69bbdab25d01d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_3af945774a224bb7aeb77f351be0848d",
              "IPY_MODEL_2421cb03b3e1422880598d3563675910",
              "IPY_MODEL_7535d3d910b549efafdb2ca0eddab508"
            ],
            "layout": "IPY_MODEL_6bae74dfc08f415c935d8c4efa3f7efb"
          }
        },
        "3af945774a224bb7aeb77f351be0848d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_74985a10f1114c9aa8f51d9e19f1279b",
            "placeholder": "​",
            "style": "IPY_MODEL_36f1956ce61743e1abfd67571f6de8f1",
            "value": "100%"
          }
        },
        "2421cb03b3e1422880598d3563675910": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_b74582143f4449c19c3741a54b5de83e",
            "max": 110,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_1d0bdcbce3274e39836ce5fcbcc57a09",
            "value": 110
          }
        },
        "7535d3d910b549efafdb2ca0eddab508": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_f8bc434b626c4de1a00b54c76fcdbe0c",
            "placeholder": "​",
            "style": "IPY_MODEL_1f39ba692b834be38d3c0bc59929901f",
            "value": " 110/110 [00:09&lt;00:00, 12.31it/s]"
          }
        },
        "6bae74dfc08f415c935d8c4efa3f7efb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "74985a10f1114c9aa8f51d9e19f1279b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "36f1956ce61743e1abfd67571f6de8f1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "b74582143f4449c19c3741a54b5de83e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1d0bdcbce3274e39836ce5fcbcc57a09": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "f8bc434b626c4de1a00b54c76fcdbe0c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1f39ba692b834be38d3c0bc59929901f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "ca2a51b78dd64358af22c9fb7a431f76": {
          "model_module": "nglview-js-widgets",
          "model_name": "NGLModel",
          "model_module_version": "3.0.6",
          "state": {
            "_camera_orientation": [
              45.741682214189154,
              57.97863130071914,
              -49.937635944777895,
              0,
              -3.0405019512808718,
              59.51089957637985,
              66.30836178443901,
              0,
              76.45943054419227,
              -32.31906259697319,
              32.51191069058447,
              0,
              0.22299957275390625,
              -6.229499816894531,
              26.937499046325684,
              1
            ],
            "_camera_str": "orthographic",
            "_dom_classes": [],
            "_gui_theme": null,
            "_ibtn_fullscreen": "IPY_MODEL_75817411ad774133890c5e5a3574373a",
            "_igui": null,
            "_iplayer": "IPY_MODEL_abbbf582d6634035929f1c58548eb78c",
            "_model_module": "nglview-js-widgets",
            "_model_module_version": "3.0.6",
            "_model_name": "NGLModel",
            "_ngl_color_dict": {},
            "_ngl_coordinate_resource": {},
            "_ngl_full_stage_parameters": {
              "impostor": true,
              "quality": "medium",
              "workerDefault": true,
              "sampleLevel": 0,
              "backgroundColor": "white",
              "rotateSpeed": 2,
              "zoomSpeed": 1.2,
              "panSpeed": 1,
              "clipNear": 0,
              "clipFar": 100,
              "clipDist": 10,
              "clipMode": "scene",
              "clipScale": "relative",
              "fogNear": 50,
              "fogFar": 100,
              "cameraFov": 40,
              "cameraEyeSep": 0.3,
              "cameraType": "perspective",
              "lightColor": 14540253,
              "lightIntensity": 1,
              "ambientColor": 14540253,
              "ambientIntensity": 0.2,
              "hoverTimeout": 0,
              "tooltip": true,
              "mousePreset": "default"
            },
            "_ngl_msg_archive": [
              {
                "target": "Stage",
                "type": "call_method",
                "methodName": "loadFile",
                "reconstruc_color_scheme": false,
                "args": [
                  {
                    "type": "blob",
                    "data": "TITLE     MDANALYSIS FRAME 0: Created by PDBWriter\nCRYST1    1.000    1.000    1.000  90.00  90.00  90.00 P 1           1\nREMARK     285 UNITARY VALUES FOR THE UNIT CELL AUTOMATICALLY SET\nREMARK     285 BY MDANALYSIS PDBWRITER BECAUSE UNIT CELL INFORMATION\nREMARK     285 WAS MISSING.\nREMARK     285 PROTEIN DATA BANK CONVENTIONS REQUIRE THAT\nREMARK     285 CRYST1 RECORD IS INCLUDED, BUT THE VALUES ON\nREMARK     285 THIS RECORD ARE MEANINGLESS.\nATOM      1  C5  8AM X9001     -15.044  16.768 -25.718  1.00 15.61      A       \nATOM      2  C6  8AM X9001     -13.289  15.888 -27.250  1.00 14.40      A       \nATOM      3  C8  8AM X9001     -13.359  13.536 -27.750  1.00 13.99      A       \nATOM      4  C10 8AM X9001     -11.677  15.011 -28.597  1.00 12.25      A       \nATOM      5  N12 8AM X9001     -10.572  14.937 -29.401  1.00 13.05      A       \nATOM      6  C13 8AM X9001     -10.456  13.612 -29.774  1.00 13.28      A       \nATOM      7  C15 8AM X9001      -9.721  16.085 -29.761  1.00 13.26      A       \nATOM      8  C17 8AM X9001      -8.279  15.692 -30.111  1.00 13.41      A       \nATOM      9  C20 8AM X9001     -15.845  12.696 -25.952  1.00 17.54      A       \nATOM     10  C26 8AM X9001     -17.976  12.242 -24.706  1.00 20.82      A       \nATOM     11  C1  8AM X9001     -15.255  18.177 -25.137  1.00 16.07      A       \nATOM     12  C2  8AM X9001     -14.594  19.080 -26.156  1.00 16.78      A       \nATOM     13  C3  8AM X9001     -13.365  18.285 -26.590  1.00 15.96      A       \nATOM     14  N4  8AM X9001     -13.867  16.926 -26.565  1.00 14.59      A       \nATOM     15  N7  8AM X9001     -13.863  14.660 -27.134  1.00 13.52      A       \nATOM     16  C9  8AM X9001     -12.185  13.714 -28.527  1.00 13.58      A       \nATOM     17  N11 8AM X9001     -12.175  16.118 -27.994  1.00 13.47      A       \nATOM     18  N14 8AM X9001     -11.411  12.856 -29.266  1.00 13.04      A       \nATOM     19  C16 8AM X9001     -10.325  16.858 -30.941  1.00 14.60      A       \nATOM     20  N18 8AM X9001     -13.998  12.292 -27.613  1.00 15.88      A       \nATOM     21  C19 8AM X9001     -15.154  12.007 -26.939  1.00 16.40      A       \nATOM     22  N21 8AM X9001     -16.945  11.939 -25.669  1.00 19.32      A       \nATOM     23  N22 8AM X9001     -17.026  10.809 -26.396  1.00 19.32      A       \nATOM     24  C23 8AM X9001     -15.928  10.861 -27.168  1.00 17.77      A       \nATOM     25  O24 8AM X9001     -15.601   9.901 -28.086  1.00 18.31      A       \nATOM     26  C25 8AM X9001     -16.500   8.795 -28.206  1.00 18.65      A       \nATOM     27  F27 8AM X9001     -15.445  19.229 -27.215  1.00 18.02      A       \nATOM     28  N28 8AM X9001     -14.552  18.323 -23.854  1.00 15.17      A       \nATOM     29  C29 8AM X9001     -15.007  17.806 -22.652  1.00 13.82      A       \nATOM     30  C30 8AM X9001     -14.037  18.146 -21.524  1.00 14.17      A       \nATOM     31  C31 8AM X9001     -14.359  17.468 -20.200  1.00 14.45      A       \nATOM     32  O32 8AM X9001     -16.044  17.165 -22.506  1.00 16.45      A       \nCONECT    1   11   14\nCONECT    2   14   15   17\nCONECT    3   15   16   20\nCONECT    4    5   16   17\nCONECT    5    4    6    7\nCONECT    6    5   18\nCONECT    7    5    8   19\nCONECT    8    7\nCONECT    9   21   22\nCONECT   10   22\nCONECT   11    1   12   28\nCONECT   12   11   13   27\nCONECT   13   12   14\nCONECT   14    1    2   13\nCONECT   15    2    3\nCONECT   16    3    4   18\nCONECT   17    2    4\nCONECT   18    6   16\nCONECT   19    7\nCONECT   20    3   21\nCONECT   21    9   20   24\nCONECT   22    9   10   23\nCONECT   23   22   24\nCONECT   24   21   23   25\nCONECT   25   24   26\nCONECT   26   25\nCONECT   27   12\nCONECT   28   11   29\nCONECT   29   28   30   32\nCONECT   30   29   31\nCONECT   31   30\nCONECT   32   29\nEND\n",
                    "binary": false
                  }
                ],
                "kwargs": {
                  "defaultRepresentation": true,
                  "ext": "pdb"
                }
              },
              {
                "target": "Widget",
                "type": "call_method",
                "methodName": "removeRepresentationsByName",
                "reconstruc_color_scheme": false,
                "args": [
                  "ball+stick",
                  0
                ],
                "kwargs": {}
              },
              {
                "component_index": 0,
                "target": "compList",
                "type": "call_method",
                "methodName": "addRepresentation",
                "reconstruc_color_scheme": false,
                "args": [
                  "licorice"
                ],
                "kwargs": {
                  "sele": "all"
                }
              },
              {
                "target": "Stage",
                "type": "call_method",
                "methodName": "loadFile",
                "reconstruc_color_scheme": false,
                "args": [
                  {
                    "type": "blob",
                    "data": "TITLE     MDANALYSIS FRAME 0: Created by PDBWriter\nCRYST1    1.000    1.000    1.000  90.00  90.00  90.00 P 1           1\nREMARK     285 UNITARY VALUES FOR THE UNIT CELL AUTOMATICALLY SET\nREMARK     285 BY MDANALYSIS PDBWRITER BECAUSE UNIT CELL INFORMATION\nREMARK     285 WAS MISSING.\nREMARK     285 PROTEIN DATA BANK CONVENTIONS REQUIRE THAT\nREMARK     285 CRYST1 RECORD IS INCLUDED, BUT THE VALUES ON\nREMARK     285 THIS RECORD ARE MEANINGLESS.\nATOM      1  C4  634 X9001      10.096  -4.018 -33.480  1.00 12.80      A       \nATOM      2  C5  634 X9001       9.809  -2.652 -33.604  1.00 13.93      A       \nATOM      3  C8  634 X9001       7.879  -3.776 -33.738  1.00 12.77      A       \nATOM      4  C13 634 X9001      15.547  -6.106 -33.267  1.00 18.87      A       \nATOM      5  C15 634 X9001      14.731  -6.361 -30.938  1.00 18.01      A       \nATOM      6  C20 634 X9001      15.603  -6.906 -27.303  1.00 17.48      A       \nATOM      7  C21 634 X9001      16.440  -6.245 -26.226  1.00 18.05      A       \nATOM      8  C24 634 X9001      15.130  -2.277 -33.021  1.00 18.65      A       \nATOM      9  C28 634 X9001      17.568  -2.708 -32.707  1.00 21.42      A       \nATOM     10  C1  634 X9001      12.002  -2.008 -33.403  1.00 15.57      A       \nATOM     11  N2  634 X9001      12.373  -3.314 -33.274  1.00 13.47      A       \nATOM     12  C3  634 X9001      11.453  -4.331 -33.308  1.00 13.41      A       \nATOM     13  N6  634 X9001      10.700  -1.613 -33.576  1.00 14.15      A       \nATOM     14  N7  634 X9001       8.459  -2.530 -33.759  1.00 13.16      A       \nATOM     15  C9  634 X9001       8.866  -4.720 -33.567  1.00 12.86      A       \nATOM     16  O10 634 X9001      11.856  -5.658 -33.171  1.00 13.63      A       \nATOM     17  C11 634 X9001      13.159  -5.881 -32.774  1.00 16.20      A       \nATOM     18  C12 634 X9001      14.225  -5.871 -33.720  1.00 17.34      A       \nATOM     19  C14 634 X9001      15.806  -6.351 -31.887  1.00 18.52      A       \nATOM     20  C16 634 X9001      13.409  -6.124 -31.396  1.00 16.50      A       \nATOM     21  N17 634 X9001      14.862  -6.605 -29.542  1.00 16.35      A       \nATOM     22  C18 634 X9001      15.991  -6.536 -28.733  1.00 18.67      A       \nATOM     23  O19 634 X9001      17.138  -6.238 -29.068  1.00 21.24      A       \nATOM     24  N22 634 X9001      13.006  -1.007 -33.357  1.00 16.25      A       \nATOM     25  C23 634 X9001      14.362  -1.140 -33.191  1.00 17.60      A       \nATOM     26  N25 634 X9001      16.415  -1.863 -32.901  1.00 20.40      A       \nATOM     27  N26 634 X9001      16.557  -0.530 -32.978  1.00 20.72      A       \nATOM     28  C27 634 X9001      15.304  -0.092 -33.155  1.00 18.59      A       \nCONECT    1    2   12   15\nCONECT    2    1   13   14\nCONECT    3   14   15\nCONECT    4   18   19\nCONECT    5   19   20   21\nCONECT    6    7   22\nCONECT    7    6\nCONECT    8   25   26\nCONECT    9   26\nCONECT   10   11   13   24\nCONECT   11   10   12\nCONECT   12    1   11   16\nCONECT   13    2   10\nCONECT   14    2    3\nCONECT   15    1    3\nCONECT   16   12   17\nCONECT   17   16   18   20\nCONECT   18    4   17\nCONECT   19    4    5\nCONECT   20    5   17\nCONECT   21    5   22\nCONECT   22    6   21   23\nCONECT   23   22\nCONECT   24   10   25\nCONECT   25    8   24   28\nCONECT   26    8    9   27\nCONECT   27   26   28\nCONECT   28   25   27\nEND\n",
                    "binary": false
                  }
                ],
                "kwargs": {
                  "defaultRepresentation": true,
                  "ext": "pdb"
                }
              },
              {
                "target": "Widget",
                "type": "call_method",
                "methodName": "removeRepresentationsByName",
                "reconstruc_color_scheme": false,
                "args": [
                  "ball+stick",
                  1
                ],
                "kwargs": {}
              },
              {
                "component_index": 1,
                "target": "compList",
                "type": "call_method",
                "methodName": "addRepresentation",
                "reconstruc_color_scheme": false,
                "args": [
                  "licorice"
                ],
                "kwargs": {
                  "sele": "all"
                }
              },
              {
                "target": "Stage",
                "type": "call_method",
                "methodName": "loadFile",
                "reconstruc_color_scheme": false,
                "args": [
                  {
                    "type": "blob",
                    "data": "TITLE     MDANALYSIS FRAME 0: Created by PDBWriter\nCRYST1    1.000    1.000    1.000  90.00  90.00  90.00 P 1           1\nREMARK     285 UNITARY VALUES FOR THE UNIT CELL AUTOMATICALLY SET\nREMARK     285 BY MDANALYSIS PDBWRITER BECAUSE UNIT CELL INFORMATION\nREMARK     285 WAS MISSING.\nREMARK     285 PROTEIN DATA BANK CONVENTIONS REQUIRE THAT\nREMARK     285 CRYST1 RECORD IS INCLUDED, BUT THE VALUES ON\nREMARK     285 THIS RECORD ARE MEANINGLESS.\nATOM      1  C5  8BP X9001     -15.017  16.863 -25.824  1.00 17.20      A       \nATOM      2  C6  8BP X9001     -13.278  16.004 -27.373  1.00 14.56      A       \nATOM      3  C8  8BP X9001     -13.346  13.635 -27.812  1.00 15.42      A       \nATOM      4  C10 8BP X9001     -11.686  15.102 -28.731  1.00 14.45      A       \nATOM      5  N12 8BP X9001     -10.594  15.014 -29.549  1.00 14.48      A       \nATOM      6  C13 8BP X9001     -10.475  13.679 -29.895  1.00 14.60      A       \nATOM      7  C15 8BP X9001      -9.754  16.160 -29.943  1.00 14.09      A       \nATOM      8  C17 8BP X9001      -8.304  15.775 -30.290  1.00 14.60      A       \nATOM      9  C20 8BP X9001     -15.945  12.923 -26.137  1.00 18.35      A       \nATOM     10  C24 8BP X9001     -18.008  12.519 -24.781  1.00 22.61      A       \nATOM     11  C28 8BP X9001     -14.041  18.158 -21.630  1.00 16.97      A       \nATOM     12  C1  8BP X9001     -15.251  18.258 -25.238  1.00 16.28      A       \nATOM     13  C2  8BP X9001     -14.604  19.186 -26.247  1.00 18.48      A       \nATOM     14  C3  8BP X9001     -13.384  18.412 -26.734  1.00 17.47      A       \nATOM     15  N4  8BP X9001     -13.859  17.045 -26.690  1.00 16.34      A       \nATOM     16  N7  8BP X9001     -13.840  14.773 -27.216  1.00 13.84      A       \nATOM     17  C9  8BP X9001     -12.187  13.801 -28.622  1.00 14.74      A       \nATOM     18  N11 8BP X9001     -12.179  16.227 -28.145  1.00 15.05      A       \nATOM     19  N14 8BP X9001     -11.416  12.929 -29.356  1.00 14.81      A       \nATOM     20  C16 8BP X9001     -10.370  16.900 -31.134  1.00 16.04      A       \nATOM     21  N18 8BP X9001     -13.980  12.390 -27.610  1.00 16.29      A       \nATOM     22  C19 8BP X9001     -15.106  12.099 -26.876  1.00 16.79      A       \nATOM     23  N21 8BP X9001     -16.907  12.116 -25.621  1.00 19.67      A       \nATOM     24  N22 8BP X9001     -16.767  10.824 -25.959  1.00 20.11      A       \nATOM     25  C23 8BP X9001     -15.668  10.820 -26.725  1.00 18.18      A       \nATOM     26  F25 8BP X9001     -15.469  19.365 -27.288  1.00 20.37      A       \nATOM     27  N26 8BP X9001     -14.550  18.378 -23.955  1.00 16.59      A       \nATOM     28  C27 8BP X9001     -15.018  17.851 -22.759  1.00 16.55      A       \nATOM     29  C29 8BP X9001     -14.392  17.502 -20.303  1.00 18.11      A       \nATOM     30  O30 8BP X9001     -16.073  17.221 -22.619  1.00 20.86      A       \nCONECT    1   12   15\nCONECT    2   15   16   18\nCONECT    3   16   17   21\nCONECT    4    5   17   18\nCONECT    5    4    6    7\nCONECT    6    5   19\nCONECT    7    5    8   20\nCONECT    8    7\nCONECT    9   22   23\nCONECT   10   23\nCONECT   11   28   29\nCONECT   12    1   13   27\nCONECT   13   12   14   26\nCONECT   14   13   15\nCONECT   15    1    2   14\nCONECT   16    2    3\nCONECT   17    3    4   19\nCONECT   18    2    4\nCONECT   19    6   17\nCONECT   20    7\nCONECT   21    3   22\nCONECT   22    9   21   25\nCONECT   23    9   10   24\nCONECT   24   23   25\nCONECT   25   22   24\nCONECT   26   13\nCONECT   27   12   28\nCONECT   28   11   27   30\nCONECT   29   11\nCONECT   30   28\nEND\n",
                    "binary": false
                  }
                ],
                "kwargs": {
                  "defaultRepresentation": true,
                  "ext": "pdb"
                }
              },
              {
                "target": "Widget",
                "type": "call_method",
                "methodName": "removeRepresentationsByName",
                "reconstruc_color_scheme": false,
                "args": [
                  "ball+stick",
                  2
                ],
                "kwargs": {}
              },
              {
                "component_index": 2,
                "target": "compList",
                "type": "call_method",
                "methodName": "addRepresentation",
                "reconstruc_color_scheme": false,
                "args": [
                  "licorice"
                ],
                "kwargs": {
                  "sele": "all"
                }
              },
              {
                "target": "Stage",
                "type": "call_method",
                "methodName": "loadFile",
                "reconstruc_color_scheme": false,
                "args": [
                  {
                    "type": "blob",
                    "data": "TITLE     MDANALYSIS FRAME 0: Created by PDBWriter\nCRYST1    1.000    1.000    1.000  90.00  90.00  90.00 P 1           1\nREMARK     285 UNITARY VALUES FOR THE UNIT CELL AUTOMATICALLY SET\nREMARK     285 BY MDANALYSIS PDBWRITER BECAUSE UNIT CELL INFORMATION\nREMARK     285 WAS MISSING.\nREMARK     285 PROTEIN DATA BANK CONVENTIONS REQUIRE THAT\nREMARK     285 CRYST1 RECORD IS INCLUDED, BUT THE VALUES ON\nREMARK     285 THIS RECORD ARE MEANINGLESS.\nATOM      1  C5  8BS X9001     -15.062  16.603 -25.611  1.00 25.65      A       \nATOM      2  C6  8BS X9001     -13.296  15.747 -27.149  1.00 23.63      A       \nATOM      3  C8  8BS X9001     -13.324  13.379 -27.589  1.00 24.27      A       \nATOM      4  C10 8BS X9001     -11.680  14.860 -28.499  1.00 22.65      A       \nATOM      5  N12 8BS X9001     -10.594  14.763 -29.313  1.00 23.77      A       \nATOM      6  C13 8BS X9001     -10.456  13.444 -29.656  1.00 22.65      A       \nATOM      7  C15 8BS X9001      -9.748  15.852 -29.737  1.00 23.53      A       \nATOM      8  C17 8BS X9001     -15.119  11.841 -26.797  1.00 27.29      A       \nATOM      9  C21 8BS X9001     -15.882  10.691 -27.050  1.00 28.72      A       \nATOM     10  C24 8BS X9001     -18.014  12.075 -24.662  1.00 31.85      A       \nATOM     11  C28 8BS X9001     -14.080  18.086 -21.441  1.00 23.85      A       \nATOM     12  C1  8BS X9001     -15.317  18.008 -25.049  1.00 25.83      A       \nATOM     13  C2  8BS X9001     -14.697  18.916 -26.095  1.00 26.79      A       \nATOM     14  C3  8BS X9001     -13.444  18.159 -26.526  1.00 25.63      A       \nATOM     15  N4  8BS X9001     -13.899  16.786 -26.474  1.00 23.48      A       \nATOM     16  N7  8BS X9001     -13.847  14.509 -26.997  1.00 22.96      A       \nATOM     17  C9  8BS X9001     -12.166  13.556 -28.389  1.00 23.23      A       \nATOM     18  N11 8BS X9001     -12.191  15.981 -27.915  1.00 23.17      A       \nATOM     19  N14 8BS X9001     -11.390  12.686 -29.117  1.00 22.37      A       \nATOM     20  N16 8BS X9001     -13.945  12.125 -27.431  1.00 25.73      A       \nATOM     21  C18 8BS X9001     -15.844  12.531 -25.837  1.00 28.29      A       \nATOM     22  N19 8BS X9001     -16.949  11.773 -25.590  1.00 29.64      A       \nATOM     23  N20 8BS X9001     -17.004  10.640 -26.316  1.00 29.95      A       \nATOM     24  O22 8BS X9001     -15.524   9.732 -27.955  1.00 29.94      A       \nATOM     25  C23 8BS X9001     -16.420   8.631 -28.109  1.00 31.18      A       \nATOM     26  F25 8BS X9001     -15.566  19.015 -27.149  1.00 28.30      A       \nATOM     27  N26 8BS X9001     -14.605  18.189 -23.774  1.00 25.07      A       \nATOM     28  C27 8BS X9001     -15.061  17.721 -22.551  1.00 23.87      A       \nATOM     29  C29 8BS X9001     -14.355  17.389 -20.116  1.00 22.33      A       \nATOM     30  O30 8BS X9001     -16.110  17.099 -22.372  1.00 28.99      A       \nCONECT    1   12   15\nCONECT    2   15   16   18\nCONECT    3   16   17   20\nCONECT    4    5   17   18\nCONECT    5    4    6    7\nCONECT    6    5   19\nCONECT    7    5\nCONECT    8    9   20   21\nCONECT    9    8   23   24\nCONECT   10   22\nCONECT   11   28   29\nCONECT   12    1   13   27\nCONECT   13   12   14   26\nCONECT   14   13   15\nCONECT   15    1    2   14\nCONECT   16    2    3\nCONECT   17    3    4   19\nCONECT   18    2    4\nCONECT   19    6   17\nCONECT   20    3    8\nCONECT   21    8   22\nCONECT   22   10   21   23\nCONECT   23    9   22\nCONECT   24    9   25\nCONECT   25   24\nCONECT   26   13\nCONECT   27   12   28\nCONECT   28   11   27   30\nCONECT   29   11\nCONECT   30   28\nEND\n",
                    "binary": false
                  }
                ],
                "kwargs": {
                  "defaultRepresentation": true,
                  "ext": "pdb"
                }
              },
              {
                "target": "Widget",
                "type": "call_method",
                "methodName": "removeRepresentationsByName",
                "reconstruc_color_scheme": false,
                "args": [
                  "ball+stick",
                  3
                ],
                "kwargs": {}
              },
              {
                "component_index": 3,
                "target": "compList",
                "type": "call_method",
                "methodName": "addRepresentation",
                "reconstruc_color_scheme": false,
                "args": [
                  "licorice"
                ],
                "kwargs": {
                  "sele": "all"
                }
              }
            ],
            "_ngl_original_stage_parameters": {
              "impostor": true,
              "quality": "medium",
              "workerDefault": true,
              "sampleLevel": 0,
              "backgroundColor": "white",
              "rotateSpeed": 2,
              "zoomSpeed": 1.2,
              "panSpeed": 1,
              "clipNear": 0,
              "clipFar": 100,
              "clipDist": 10,
              "clipMode": "scene",
              "clipScale": "relative",
              "fogNear": 50,
              "fogFar": 100,
              "cameraFov": 40,
              "cameraEyeSep": 0.3,
              "cameraType": "perspective",
              "lightColor": 14540253,
              "lightIntensity": 1,
              "ambientColor": 14540253,
              "ambientIntensity": 0.2,
              "hoverTimeout": 0,
              "tooltip": true,
              "mousePreset": "default"
            },
            "_ngl_repr_dict": {
              "0": {
                "0": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                },
                "1": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                }
              },
              "1": {
                "0": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                },
                "1": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                }
              },
              "2": {
                "0": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                },
                "1": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                }
              },
              "3": {
                "0": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                },
                "1": {
                  "type": "licorice",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "medium",
                    "sphereDetail": 1,
                    "radialSegments": 10,
                    "openEnded": true,
                    "disableImpostor": false,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.4,
                    "bondSpacing": 1,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 1,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": "all"
                  }
                }
              },
              "4": {
                "0": {
                  "type": "ball+stick",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "high",
                    "sphereDetail": 2,
                    "radialSegments": 20,
                    "openEnded": true,
                    "disableImpostor": false,
                    "aspectRatio": 1.5,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.3,
                    "bondSpacing": 0.75,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 2,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": ""
                  }
                }
              },
              "5": {
                "0": {
                  "type": "ball+stick",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "high",
                    "sphereDetail": 2,
                    "radialSegments": 20,
                    "openEnded": true,
                    "disableImpostor": false,
                    "aspectRatio": 1.5,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.3,
                    "bondSpacing": 0.75,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 2,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": ""
                  }
                }
              },
              "6": {
                "0": {
                  "type": "ball+stick",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "high",
                    "sphereDetail": 2,
                    "radialSegments": 20,
                    "openEnded": true,
                    "disableImpostor": false,
                    "aspectRatio": 1.5,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.3,
                    "bondSpacing": 0.75,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 2,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": ""
                  }
                }
              },
              "7": {
                "0": {
                  "type": "ball+stick",
                  "params": {
                    "lazy": false,
                    "visible": true,
                    "quality": "high",
                    "sphereDetail": 2,
                    "radialSegments": 20,
                    "openEnded": true,
                    "disableImpostor": false,
                    "aspectRatio": 1.5,
                    "lineOnly": false,
                    "cylinderOnly": false,
                    "multipleBond": "off",
                    "bondScale": 0.3,
                    "bondSpacing": 0.75,
                    "linewidth": 2,
                    "radiusType": "size",
                    "radiusData": {},
                    "radiusSize": 0.15,
                    "radiusScale": 2,
                    "assembly": "default",
                    "defaultAssembly": "",
                    "clipNear": 0,
                    "clipRadius": 0,
                    "clipCenter": {
                      "x": 0,
                      "y": 0,
                      "z": 0
                    },
                    "flatShaded": false,
                    "opacity": 1,
                    "depthWrite": true,
                    "side": "double",
                    "wireframe": false,
                    "colorScheme": "element",
                    "colorScale": "",
                    "colorReverse": false,
                    "colorValue": 9474192,
                    "colorMode": "hcl",
                    "roughness": 0.4,
                    "metalness": 0,
                    "diffuse": 16777215,
                    "diffuseInterior": false,
                    "useInteriorColor": true,
                    "interiorColor": 2236962,
                    "interiorDarkening": 0,
                    "matrix": {
                      "elements": [
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1,
                        0,
                        0,
                        0,
                        0,
                        1
                      ]
                    },
                    "disablePicking": false,
                    "sele": ""
                  }
                }
              }
            },
            "_ngl_serialize": false,
            "_ngl_version": "2.0.0-dev.39",
            "_ngl_view_id": [
              "3499A467-C697-4554-AF2C-70BC05F2AB17"
            ],
            "_player_dict": {},
            "_scene_position": {},
            "_scene_rotation": {},
            "_synced_model_ids": [],
            "_synced_repr_model_ids": [],
            "_view_count": null,
            "_view_height": "",
            "_view_module": "nglview-js-widgets",
            "_view_module_version": "3.0.6",
            "_view_name": "NGLView",
            "_view_width": "",
            "background": "white",
            "frame": 0,
            "gui_style": null,
            "layout": "IPY_MODEL_02a76b26e79c49bb903e89cdf2c521ce",
            "max_frame": 0,
            "n_components": 8,
            "picked": {}
          }
        },
        "02a76b26e79c49bb903e89cdf2c521ce": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "75817411ad774133890c5e5a3574373a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ButtonModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ButtonModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ButtonView",
            "button_style": "",
            "description": "",
            "disabled": false,
            "icon": "compress",
            "layout": "IPY_MODEL_22a58bd8e695438ca4df3ff403bb0b8a",
            "style": "IPY_MODEL_355ab8a08d1340a58440e85e200c5427",
            "tooltip": ""
          }
        },
        "abbbf582d6634035929f1c58548eb78c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_f584524bfd3c4aabb0126e63d1f0d793",
              "IPY_MODEL_ca55c46275854c79bc2b1a9981be5cdb"
            ],
            "layout": "IPY_MODEL_2df161c84a824dce86b955dc906a540a"
          }
        },
        "2fbb88fe740645b6b425fc04f6b4c072": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f3e3626f16df4985b120bd0725668e01": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "84f30a7b8e874c7ba25f1e091a97212f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1bf6a17f1c884600a1411354d0135d30": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "SliderStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "SliderStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": "",
            "handle_color": null
          }
        },
        "f584524bfd3c4aabb0126e63d1f0d793": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "PlayModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "PlayModel",
            "_playing": false,
            "_repeat": false,
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "PlayView",
            "description": "",
            "description_tooltip": null,
            "disabled": false,
            "interval": 100,
            "layout": "IPY_MODEL_2fbb88fe740645b6b425fc04f6b4c072",
            "max": 0,
            "min": 0,
            "show_repeat": true,
            "step": 1,
            "style": "IPY_MODEL_f3e3626f16df4985b120bd0725668e01",
            "value": 0
          }
        },
        "ca55c46275854c79bc2b1a9981be5cdb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "IntSliderModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "IntSliderModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "IntSliderView",
            "continuous_update": true,
            "description": "",
            "description_tooltip": null,
            "disabled": false,
            "layout": "IPY_MODEL_84f30a7b8e874c7ba25f1e091a97212f",
            "max": 0,
            "min": 0,
            "orientation": "horizontal",
            "readout": true,
            "readout_format": "d",
            "step": 1,
            "style": "IPY_MODEL_1bf6a17f1c884600a1411354d0135d30",
            "value": 0
          }
        },
        "22a58bd8e695438ca4df3ff403bb0b8a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": "34px"
          }
        },
        "355ab8a08d1340a58440e85e200c5427": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ButtonStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ButtonStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "button_color": null,
            "font_weight": ""
          }
        },
        "2df161c84a824dce86b955dc906a540a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/francescopatane96/Computer_aided_drug_discovery_kit/blob/main/8_protein_data_acquisition_from_PDB.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Protein data acquisition from PDB"
      ],
      "metadata": {
        "id": "YwcnGI9JLc0o"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import output\n",
        "output.enable_custom_widget_manager()"
      ],
      "metadata": {
        "id": "kPO7c3XnJ7FG"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install redo requests_cache nglview pypdb rdkit biotite"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FdoRl6awMWXW",
        "outputId": "3d23f055-0474-413b-f2b8-ce22ab26376e"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: redo in /usr/local/lib/python3.10/dist-packages (2.0.4)\n",
            "Requirement already satisfied: requests_cache in /usr/local/lib/python3.10/dist-packages (1.1.0)\n",
            "Requirement already satisfied: nglview in /usr/local/lib/python3.10/dist-packages (3.0.6)\n",
            "Requirement already satisfied: pypdb in /usr/local/lib/python3.10/dist-packages (2.3)\n",
            "Requirement already satisfied: rdkit in /usr/local/lib/python3.10/dist-packages (2023.3.2)\n",
            "Requirement already satisfied: biotite in /usr/local/lib/python3.10/dist-packages (0.37.0)\n",
            "Requirement already satisfied: attrs>=21.2 in /usr/local/lib/python3.10/dist-packages (from requests_cache) (23.1.0)\n",
            "Requirement already satisfied: cattrs>=22.2 in /usr/local/lib/python3.10/dist-packages (from requests_cache) (23.1.2)\n",
            "Requirement already satisfied: platformdirs>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests_cache) (3.10.0)\n",
            "Requirement already satisfied: requests>=2.22 in /usr/local/lib/python3.10/dist-packages (from requests_cache) (2.31.0)\n",
            "Requirement already satisfied: url-normalize>=1.4 in /usr/local/lib/python3.10/dist-packages (from requests_cache) (1.4.3)\n",
            "Requirement already satisfied: urllib3>=1.25.5 in /usr/local/lib/python3.10/dist-packages (from requests_cache) (2.0.4)\n",
            "Requirement already satisfied: ipywidgets>=7 in /usr/local/lib/python3.10/dist-packages (from nglview) (7.7.1)\n",
            "Requirement already satisfied: jupyterlab-widgets in /usr/local/lib/python3.10/dist-packages (from nglview) (3.0.8)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from nglview) (1.23.5)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from pypdb) (1.5.3)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from rdkit) (9.4.0)\n",
            "Requirement already satisfied: msgpack>=0.5.6 in /usr/local/lib/python3.10/dist-packages (from biotite) (1.0.5)\n",
            "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.10/dist-packages (from biotite) (3.1)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from cattrs>=22.2->requests_cache) (1.1.2)\n",
            "Requirement already satisfied: typing_extensions>=4.1.0 in /usr/local/lib/python3.10/dist-packages (from cattrs>=22.2->requests_cache) (4.7.1)\n",
            "Requirement already satisfied: ipykernel>=4.5.1 in /usr/local/lib/python3.10/dist-packages (from ipywidgets>=7->nglview) (5.5.6)\n",
            "Requirement already satisfied: ipython-genutils~=0.2.0 in /usr/local/lib/python3.10/dist-packages (from ipywidgets>=7->nglview) (0.2.0)\n",
            "Requirement already satisfied: traitlets>=4.3.1 in /usr/local/lib/python3.10/dist-packages (from ipywidgets>=7->nglview) (5.7.1)\n",
            "Requirement already satisfied: widgetsnbextension~=3.6.0 in /usr/local/lib/python3.10/dist-packages (from ipywidgets>=7->nglview) (3.6.5)\n",
            "Requirement already satisfied: ipython>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from ipywidgets>=7->nglview) (7.34.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.22->requests_cache) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.22->requests_cache) (3.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.22->requests_cache) (2023.7.22)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from url-normalize>=1.4->requests_cache) (1.16.0)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->pypdb) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->pypdb) (2023.3)\n",
            "Requirement already satisfied: jupyter-client in /usr/local/lib/python3.10/dist-packages (from ipykernel>=4.5.1->ipywidgets>=7->nglview) (6.1.12)\n",
            "Requirement already satisfied: tornado>=4.2 in /usr/local/lib/python3.10/dist-packages (from ipykernel>=4.5.1->ipywidgets>=7->nglview) (6.3.1)\n",
            "Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (67.7.2)\n",
            "Requirement already satisfied: jedi>=0.16 in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (0.19.0)\n",
            "Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (4.4.2)\n",
            "Requirement already satisfied: pickleshare in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (0.7.5)\n",
            "Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (3.0.39)\n",
            "Requirement already satisfied: pygments in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (2.16.1)\n",
            "Requirement already satisfied: backcall in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (0.2.0)\n",
            "Requirement already satisfied: matplotlib-inline in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (0.1.6)\n",
            "Requirement already satisfied: pexpect>4.3 in /usr/local/lib/python3.10/dist-packages (from ipython>=4.0.0->ipywidgets>=7->nglview) (4.8.0)\n",
            "Requirement already satisfied: notebook>=4.4.1 in /usr/local/lib/python3.10/dist-packages (from widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (6.4.8)\n",
            "Requirement already satisfied: parso<0.9.0,>=0.8.3 in /usr/local/lib/python3.10/dist-packages (from jedi>=0.16->ipython>=4.0.0->ipywidgets>=7->nglview) (0.8.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (3.1.2)\n",
            "Requirement already satisfied: pyzmq>=17 in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (23.2.1)\n",
            "Requirement already satisfied: argon2-cffi in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (21.3.0)\n",
            "Requirement already satisfied: jupyter-core>=4.6.1 in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (5.3.1)\n",
            "Requirement already satisfied: nbformat in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (5.9.2)\n",
            "Requirement already satisfied: nbconvert in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (6.5.4)\n",
            "Requirement already satisfied: nest-asyncio>=1.5 in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (1.5.7)\n",
            "Requirement already satisfied: Send2Trash>=1.8.0 in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (1.8.2)\n",
            "Requirement already satisfied: terminado>=0.8.3 in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.17.1)\n",
            "Requirement already satisfied: prometheus-client in /usr/local/lib/python3.10/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.17.1)\n",
            "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.10/dist-packages (from pexpect>4.3->ipython>=4.0.0->ipywidgets>=7->nglview) (0.7.0)\n",
            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=4.0.0->ipywidgets>=7->nglview) (0.2.6)\n",
            "Requirement already satisfied: argon2-cffi-bindings in /usr/local/lib/python3.10/dist-packages (from argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (21.2.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (2.1.3)\n",
            "Requirement already satisfied: lxml in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (4.9.3)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (4.11.2)\n",
            "Requirement already satisfied: bleach in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (6.0.0)\n",
            "Requirement already satisfied: defusedxml in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.7.1)\n",
            "Requirement already satisfied: entrypoints>=0.2.2 in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.4)\n",
            "Requirement already satisfied: jupyterlab-pygments in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.2.2)\n",
            "Requirement already satisfied: mistune<2,>=0.8.1 in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.8.4)\n",
            "Requirement already satisfied: nbclient>=0.5.0 in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.8.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (23.1)\n",
            "Requirement already satisfied: pandocfilters>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (1.5.0)\n",
            "Requirement already satisfied: tinycss2 in /usr/local/lib/python3.10/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (1.2.1)\n",
            "Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.10/dist-packages (from nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (2.18.0)\n",
            "Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.10/dist-packages (from nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (4.19.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (2023.7.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.30.2)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.9.2)\n",
            "Requirement already satisfied: cffi>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (1.15.1)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (2.4.1)\n",
            "Requirement already satisfied: webencodings in /usr/local/lib/python3.10/dist-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (0.5.1)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7->nglview) (2.21)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install biopython==1.77"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4NwNrUMwlvx3",
        "outputId": "083d88bf-319c-4b0f-f6f8-4c7c22ea1755"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: biopython==1.77 in /usr/local/lib/python3.10/dist-packages (1.77)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from biopython==1.77) (1.23.5)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install Bio==1.77"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eaSXNxa9LYhs",
        "outputId": "0191b47c-91f0-4b10-9e5d-c914cdbd99f4"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[31mERROR: Could not find a version that satisfies the requirement Bio==1.77 (from versions: 1.0.2, 1.2.0, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6, 1.3.7, 1.3.8, 1.3.9, 1.4.0, 1.5.0, 1.5.1, 1.5.2, 1.5.3, 1.5.4, 1.5.5, 1.5.6, 1.5.7, 1.5.8, 1.5.9)\u001b[0m\u001b[31m\n",
            "\u001b[0m\u001b[31mERROR: No matching distribution found for Bio==1.77\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install https://github.com/volkamerlab/opencadd/archive/master.tar.gz"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9SKr8uQzNOOk",
        "outputId": "43163917-5eed-4fc8-e3b0-527236c9cc7f"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting https://github.com/volkamerlab/opencadd/archive/master.tar.gz\n",
            "  Using cached https://github.com/volkamerlab/opencadd/archive/master.tar.gz\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17,
          "referenced_widgets": [
            "07cb09ced350422ba5c9c11360331e3e",
            "3d2d3c20fdff4631b060a5f2620f289a"
          ]
        },
        "id": "7X3c9weCLK74",
        "outputId": "5d8dfec1-0611-413b-e7d4-6cf1fce3fdea"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "07cb09ced350422ba5c9c11360331e3e"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "import collections\n",
        "import logging\n",
        "import pathlib\n",
        "import time\n",
        "import warnings\n",
        "import datetime\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from bs4 import BeautifulSoup\n",
        "import requests\n",
        "from tqdm.auto import tqdm\n",
        "import redo\n",
        "import requests_cache\n",
        "import nglview\n",
        "import pypdb\n",
        "import biotite.database.rcsb as rcsb\n",
        "from rdkit.Chem import Draw\n",
        "from rdkit.Chem import PandasTools\n",
        "\n",
        "import opencadd\n",
        "\n",
        "# Disable some unneeded warnings\n",
        "logger = logging.getLogger(\"opencadd\")\n",
        "logger.setLevel(logging.ERROR)\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# Cache requests -- this will speed up repeated queries to PDB\n",
        "requests_cache.install_cache(\"rcsb_pdb\", backend=\"memory\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "uniprot_id = \"P00533\""
      ],
      "metadata": {
        "id": "iXDf_GL5NpKL"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "query_by_uniprot_id = rcsb.FieldQuery(\n",
        "    \"rcsb_polymer_entity_container_identifiers.reference_sequence_identifiers.database_accession\",\n",
        "    exact_match=uniprot_id,\n",
        ")\n",
        "today = datetime.datetime.now()\n",
        "print(\n",
        "    f\"Number of structures on {today.year}-{today.month}-{today.day}: {rcsb.count(query_by_uniprot_id)}\"\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S9haGhuUNvR6",
        "outputId": "104b8f3d-3c7c-4ed6-ab43-f53c063cedf3"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of structures on 2023-8-13: 281\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Define lists for years and number of structures available in a given year\n",
        "years = range(1971, datetime.datetime.now().year)\n",
        "n_structures = []\n",
        "\n",
        "for year in years:\n",
        "    # Set latest date for allowed deposition\n",
        "    before_deposition_date = f\"{year}-12-31T23:59:59Z\"\n",
        "    # Set up query for structures deposited latest at given date\n",
        "    query_by_deposition_date = rcsb.FieldQuery(\n",
        "        \"rcsb_accession_info.deposit_date\", less_or_equal=before_deposition_date\n",
        "    )\n",
        "    # Set up combined query\n",
        "    query = rcsb.CompositeQuery(\n",
        "        [query_by_uniprot_id, query_by_deposition_date],\n",
        "        \"and\",\n",
        "    )\n",
        "    # Count matching structures and add to list\n",
        "    n_structures.append(rcsb.count(query))\n",
        "    # wait shortly to not overload the API\n",
        "    time.sleep(0.1)"
      ],
      "metadata": {
        "id": "uXcBbDikN1Bi"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(years, n_structures)\n",
        "plt.title(\"PDB entries for EGFR\")\n",
        "plt.xlabel(\"Year\")\n",
        "plt.ylabel(\"Number of structures available in a given year\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "iQSTOfguN2vj",
        "outputId": "338b89cd-8260-426c-b658-9cfd107f1477"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "uniprot_id = \"P00533\"\n",
        "before_deposition_date = \"2020-01-01T00:00:00Z\"\n",
        "experimental_method = \"X-RAY DIFFRACTION\"\n",
        "max_resolution = 3.0\n",
        "n_chains = 1\n",
        "min_ligand_molecular_weight = 100.0"
      ],
      "metadata": {
        "id": "9_RusgcPOMPN"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "query_by_uniprot_id = rcsb.FieldQuery(\n",
        "    \"rcsb_polymer_entity_container_identifiers.reference_sequence_identifiers.database_accession\",\n",
        "    exact_match=uniprot_id,\n",
        ")\n",
        "query_by_deposition_date = rcsb.FieldQuery(\n",
        "    \"rcsb_accession_info.deposit_date\", less=before_deposition_date\n",
        ")\n",
        "query_by_experimental_method = rcsb.FieldQuery(\"exptl.method\", exact_match=experimental_method)\n",
        "query_by_resolution = rcsb.FieldQuery(\n",
        "    \"rcsb_entry_info.resolution_combined\", less_or_equal=max_resolution\n",
        ")\n",
        "query_by_polymer_count = rcsb.FieldQuery(\n",
        "    \"rcsb_entry_info.deposited_polymer_entity_instance_count\", equals=n_chains\n",
        ")\n",
        "query_by_ligand_mw = rcsb.FieldQuery(\n",
        "    \"chem_comp.formula_weight\", molecular_definition=True, greater=min_ligand_molecular_weight\n",
        ")"
      ],
      "metadata": {
        "id": "b633GaIuOO99"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"Number of structures with UniProt ID {uniprot_id}: {rcsb.count(query_by_uniprot_id)}\")\n",
        "time.sleep(0.1)  # wait shortly to not overload the API\n",
        "print(\n",
        "    f\"Number of structures deposited before {before_deposition_date}: {rcsb.count(query_by_deposition_date)}\"\n",
        ")\n",
        "time.sleep(0.1)\n",
        "print(\n",
        "    f\"Number of structures resolved by {experimental_method}: {rcsb.count(query_by_experimental_method)}\"\n",
        ")\n",
        "time.sleep(0.1)\n",
        "print(\n",
        "    f\"Number of structures with resolution less than or equal to {max_resolution}: {rcsb.count(query_by_resolution)}\"\n",
        ")\n",
        "time.sleep(0.1)\n",
        "print(f\"Number of structures with only {n_chains} chain: {rcsb.count(query_by_polymer_count)}\")\n",
        "time.sleep(0.1)\n",
        "print(\n",
        "    f\"Number of structures with ligand of more than or equal to {min_ligand_molecular_weight} Da: {rcsb.count(query_by_ligand_mw)}\"\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2K4-nNVQORcy",
        "outputId": "8befcca8-c5e3-4df3-faaa-3dfed4804b47"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of structures with UniProt ID P00533: 281\n",
            "Number of structures deposited before 2020-01-01T00:00:00Z: 166261\n",
            "Number of structures resolved by X-RAY DIFFRACTION: 177521\n",
            "Number of structures with resolution less than or equal to 3.0: 170190\n",
            "Number of structures with only 1 chain: 75451\n",
            "Number of structures with ligand of more than or equal to 100.0 Da: 208346\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "query = rcsb.CompositeQuery(\n",
        "    [\n",
        "        query_by_uniprot_id,\n",
        "        query_by_deposition_date,\n",
        "        query_by_experimental_method,\n",
        "        query_by_resolution,\n",
        "        query_by_polymer_count,\n",
        "        query_by_ligand_mw,\n",
        "    ],\n",
        "    \"and\",\n",
        ")\n",
        "pdb_ids = rcsb.search(query)\n",
        "print(f\"Number of matches: {len(pdb_ids)}\")\n",
        "print(\"Selected PDB IDs:\")\n",
        "print(*pdb_ids)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f71aL1ZMOVbx",
        "outputId": "77eccde9-9d00-47ba-8e2c-b25940cd8d5f"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of matches: 110\n",
            "Selected PDB IDs:\n",
            "1M14 1M17 1XKK 2EB2 2EB3 2GS2 2ITN 2ITP 2ITQ 2ITT 2ITU 2ITV 2ITW 2ITX 2ITZ 2J5F 2RGP 3BEL 3GOP 3POZ 3UG1 3UG2 3VJN 3VJO 3W2O 3W2P 3W2Q 3W2R 3W2S 3W32 3W33 4G5J 4HJO 4I1Z 4I22 4I23 4JQ7 4JQ8 4JR3 4JRV 4LI5 4LQM 4RJ4 4RJ6 4RJ7 4RJ8 4WKQ 4WRG 4ZAU 5C8K 5C8M 5C8N 5CAL 5CAN 5CAO 5CAP 5CAQ 5CAS 5CAU 5CAV 5EDP 5EDQ 5EDR 5EM5 5EM6 5EM7 5EM8 5FED 5FEE 5GMP 5GNK 5GTZ 5HCX 5HCY 5HCZ 5HG5 5HG7 5HG8 5HG9 5HIB 5HIC 5J9Y 5J9Z 5U8L 5UG8 5UG9 5UGA 5UGB 5UGC 5X26 5X27 5X28 5XDK 5XDL 5XGM 5ZTO 5ZWJ 6D8E 6JRJ 6JRK 6JRX 6JWL 6JX0 6JX4 6JXT 6JZ0 6S89 6S8A 6S9C 6S9D\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "@redo.retriable(attempts=10, sleeptime=2)\n",
        "def describe_one_pdb_id(pdb_id):\n",
        "    \"\"\"Fetch meta information from PDB.\"\"\"\n",
        "    described = pypdb.describe_pdb(pdb_id)\n",
        "    if described is None:\n",
        "        print(f\"! Error while fetching {pdb_id}, retrying ...\")\n",
        "        raise ValueError(f\"Could not fetch PDB id {pdb_id}\")\n",
        "    return described"
      ],
      "metadata": {
        "id": "66fFqCYSOaQu"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pdbs_data = [describe_one_pdb_id(pdb_id) for pdb_id in tqdm(pdb_ids)]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "d9d0bb310e9b4be594e69bbdab25d01d",
            "3af945774a224bb7aeb77f351be0848d",
            "2421cb03b3e1422880598d3563675910",
            "7535d3d910b549efafdb2ca0eddab508",
            "6bae74dfc08f415c935d8c4efa3f7efb",
            "74985a10f1114c9aa8f51d9e19f1279b",
            "36f1956ce61743e1abfd67571f6de8f1",
            "b74582143f4449c19c3741a54b5de83e",
            "1d0bdcbce3274e39836ce5fcbcc57a09",
            "f8bc434b626c4de1a00b54c76fcdbe0c",
            "1f39ba692b834be38d3c0bc59929901f"
          ]
        },
        "id": "8pQeRMecOcwg",
        "outputId": "4c446019-0a73-4085-91f1-ff5906a514b0"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/110 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d9d0bb310e9b4be594e69bbdab25d01d"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
                }
              }
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"\\n\".join(pdbs_data[0].keys()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YAQBWx5HOtrx",
        "outputId": "2b172b7d-1149-4ad7-d098-b58d14d7d27f"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "audit_author\n",
            "cell\n",
            "citation\n",
            "diffrn\n",
            "diffrn_detector\n",
            "diffrn_radiation\n",
            "diffrn_source\n",
            "entry\n",
            "exptl\n",
            "exptl_crystal\n",
            "exptl_crystal_grow\n",
            "pdbx_audit_revision_details\n",
            "pdbx_audit_revision_group\n",
            "pdbx_audit_revision_history\n",
            "pdbx_database_related\n",
            "pdbx_database_status\n",
            "rcsb_accession_info\n",
            "rcsb_entry_container_identifiers\n",
            "rcsb_entry_info\n",
            "rcsb_primary_citation\n",
            "refine\n",
            "refine_analyze\n",
            "refine_hist\n",
            "refine_ls_restr\n",
            "reflns\n",
            "reflns_shell\n",
            "software\n",
            "struct\n",
            "struct_keywords\n",
            "symmetry\n",
            "rcsb_id\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pdbs_data[0][\"entry\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mt-xrtpjOywl",
        "outputId": "313cf279-ce57-479a-9be2-590e679af5ee"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'id': '1M14'}"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pdbs_data[0][\"rcsb_entry_info\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UsRnUR4RO0pq",
        "outputId": "6c163b30-961a-4d8b-b731-5b7567a38757"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'assembly_count': 1,\n",
              " 'branched_entity_count': 0,\n",
              " 'cis_peptide_count': 0,\n",
              " 'deposited_atom_count': 2469,\n",
              " 'deposited_hydrogen_atom_count': 0,\n",
              " 'deposited_model_count': 1,\n",
              " 'deposited_modeled_polymer_monomer_count': 307,\n",
              " 'deposited_nonpolymer_entity_instance_count': 0,\n",
              " 'deposited_polymer_entity_instance_count': 1,\n",
              " 'deposited_polymer_monomer_count': 333,\n",
              " 'deposited_solvent_atom_count': 17,\n",
              " 'deposited_unmodeled_polymer_monomer_count': 26,\n",
              " 'diffrn_radiation_wavelength_maximum': 1.008,\n",
              " 'diffrn_radiation_wavelength_minimum': 1.008,\n",
              " 'disulfide_bond_count': 0,\n",
              " 'entity_count': 2,\n",
              " 'experimental_method': 'X-ray',\n",
              " 'experimental_method_count': 1,\n",
              " 'inter_mol_covalent_bond_count': 0,\n",
              " 'inter_mol_metalic_bond_count': 0,\n",
              " 'molecular_weight': 37.88,\n",
              " 'na_polymer_entity_types': 'Other',\n",
              " 'nonpolymer_entity_count': 0,\n",
              " 'polymer_composition': 'homomeric protein',\n",
              " 'polymer_entity_count': 1,\n",
              " 'polymer_entity_count_dna': 0,\n",
              " 'polymer_entity_count_rna': 0,\n",
              " 'polymer_entity_count_nucleic_acid': 0,\n",
              " 'polymer_entity_count_nucleic_acid_hybrid': 0,\n",
              " 'polymer_entity_count_protein': 1,\n",
              " 'polymer_entity_taxonomy_count': 1,\n",
              " 'polymer_molecular_weight_maximum': 37.88,\n",
              " 'polymer_molecular_weight_minimum': 37.88,\n",
              " 'polymer_monomer_count_maximum': 333,\n",
              " 'polymer_monomer_count_minimum': 333,\n",
              " 'resolution_combined': [2.6],\n",
              " 'selected_polymer_entity_types': 'Protein (only)',\n",
              " 'software_programs_combined': ['AMORE',\n",
              "  'CCP4',\n",
              "  'HKL-2000',\n",
              "  'TRUNCATE',\n",
              "  'X-PLOR'],\n",
              " 'solvent_entity_count': 1,\n",
              " 'structure_determination_methodology': 'experimental',\n",
              " 'structure_determination_methodology_priority': 10,\n",
              " 'diffrn_resolution_high': {'provenance_source': 'Depositor assigned',\n",
              "  'value': 2.6}}"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "resolution = pd.DataFrame(\n",
        "    [\n",
        "        [pdb_data[\"entry\"][\"id\"], pdb_data[\"rcsb_entry_info\"][\"resolution_combined\"][0]]\n",
        "        for pdb_data in pdbs_data\n",
        "    ],\n",
        "    columns=[\"pdb_id\", \"resolution\"],\n",
        ").sort_values(by=\"resolution\", ignore_index=True)\n",
        "resolution"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "TNg2qePoO4aq",
        "outputId": "a2f200e0-d055-44c5-d884-f14c2a1e0ca3"
      },
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    pdb_id  resolution\n",
              "0     5UG9       1.330\n",
              "1     5HG8       1.420\n",
              "2     5UG8       1.460\n",
              "3     3POZ       1.500\n",
              "4     5HG5       1.520\n",
              "..     ...         ...\n",
              "105   2ITX       2.980\n",
              "106   5GTZ       2.999\n",
              "107   2J5F       3.000\n",
              "108   4I1Z       3.000\n",
              "109   5C8K       3.000\n",
              "\n",
              "[110 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-4137a790-87d5-4f66-a889-f2df76f161b4\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pdb_id</th>\n",
              "      <th>resolution</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5UG9</td>\n",
              "      <td>1.330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5HG8</td>\n",
              "      <td>1.420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5UG8</td>\n",
              "      <td>1.460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3POZ</td>\n",
              "      <td>1.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5HG5</td>\n",
              "      <td>1.520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>2ITX</td>\n",
              "      <td>2.980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>5GTZ</td>\n",
              "      <td>2.999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2J5F</td>\n",
              "      <td>3.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>4I1Z</td>\n",
              "      <td>3.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>5C8K</td>\n",
              "      <td>3.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>110 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4137a790-87d5-4f66-a889-f2df76f161b4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-3d27fec2-e11e-48f5-97e1-0e41d0b6a6d7\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3d27fec2-e11e-48f5-97e1-0e41d0b6a6d7')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-3d27fec2-e11e-48f5-97e1-0e41d0b6a6d7 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4137a790-87d5-4f66-a889-f2df76f161b4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4137a790-87d5-4f66-a889-f2df76f161b4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_num = 6  # Number of top structures"
      ],
      "metadata": {
        "id": "nd2I9_7MO9F7"
      },
      "execution_count": 78,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "selected_pdb_ids = resolution[:top_num][\"pdb_id\"].to_list()\n",
        "print(f\"Selected PDB IDs: {selected_pdb_ids}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1aOLG3wpO__K",
        "outputId": "0e6f86f4-35d9-4f08-daae-175d40b5bb80"
      },
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Selected PDB IDs: ['5UG9', '5HG8', '5UG8', '3POZ', '5HG5', '5UGC']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "selected_pdb_ids = [\"5UG9\", \"5HG8\", \"5UG8\", \"5UGC\"]\n",
        "print(f\"Selected PDB IDs (frozen set): {selected_pdb_ids}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gt5C0Pu6PG8o",
        "outputId": "9dc4af42-50fb-4623-c057-7778952822cf"
      },
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Selected PDB IDs (frozen set): ['5UG9', '5HG8', '5UG8', '5UGC']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def get_ligands(pdb_id):\n",
        "    \"\"\"\n",
        "    RCSB has not provided a new endpoint for ligand information yet. As a\n",
        "    workaround we are obtaining extra information from ligand-expo.rcsb.org,\n",
        "    using HTML parsing. Check Talktorial T011 for more info on this technique!\n",
        "    \"\"\"\n",
        "    pdb_info = _fetch_pdb_nonpolymer_info(pdb_id)\n",
        "    ligand_expo_ids = [\n",
        "        nonpolymer_entities[\"pdbx_entity_nonpoly\"][\"comp_id\"]\n",
        "        for nonpolymer_entities in pdb_info[\"data\"][\"entry\"][\"nonpolymer_entities\"]\n",
        "    ]\n",
        "\n",
        "    ligands = {}\n",
        "    for ligand_expo_id in ligand_expo_ids:\n",
        "        ligand_expo_info = _fetch_ligand_expo_info(ligand_expo_id)\n",
        "        ligands[ligand_expo_id] = ligand_expo_info\n",
        "\n",
        "    return ligands\n",
        "\n",
        "\n",
        "def _fetch_pdb_nonpolymer_info(pdb_id):\n",
        "    \"\"\"\n",
        "    Fetch nonpolymer data from rcsb.org.\n",
        "    Thanks @BJWiley233 and Rachel Green for this GraphQL solution.\n",
        "    \"\"\"\n",
        "    query = (\n",
        "        \"\"\"{\n",
        "          entry(entry_id: \"%s\") {\n",
        "            nonpolymer_entities {\n",
        "              pdbx_entity_nonpoly {\n",
        "                comp_id\n",
        "                name\n",
        "                rcsb_prd_id\n",
        "              }\n",
        "            }\n",
        "          }\n",
        "        }\"\"\"\n",
        "        % pdb_id\n",
        "    )\n",
        "\n",
        "    query_url = f\"https://data.rcsb.org/graphql?query={query}\"\n",
        "    response = requests.get(query_url)\n",
        "    response.raise_for_status()\n",
        "    info = response.json()\n",
        "    return info\n",
        "\n",
        "\n",
        "def _fetch_ligand_expo_info(ligand_expo_id):\n",
        "    \"\"\"\n",
        "    Fetch ligand data from ligand-expo.rcsb.org.\n",
        "    \"\"\"\n",
        "    r = requests.get(f\"http://ligand-expo.rcsb.org/reports/{ligand_expo_id[0]}/{ligand_expo_id}/\")\n",
        "    r.raise_for_status()\n",
        "    html = BeautifulSoup(r.text)\n",
        "    info = {}\n",
        "    for table in html.find_all(\"table\"):\n",
        "        for row in table.find_all(\"tr\"):\n",
        "            cells = row.find_all(\"td\")\n",
        "            if len(cells) != 2:\n",
        "                continue\n",
        "            key, value = cells\n",
        "            if key.string and key.string.strip():\n",
        "                info[key.string.strip()] = \"\".join(value.find_all(string=True))\n",
        "\n",
        "    # Postprocess some known values\n",
        "    info[\"Molecular weight\"] = float(info[\"Molecular weight\"].split()[0])\n",
        "    info[\"Formal charge\"] = int(info[\"Formal charge\"])\n",
        "    info[\"Atom count\"] = int(info[\"Atom count\"])\n",
        "    info[\"Chiral atom count\"] = int(info[\"Chiral atom count\"])\n",
        "    info[\"Bond count\"] = int(info[\"Bond count\"])\n",
        "    info[\"Aromatic bond count\"] = int(info[\"Aromatic bond count\"])\n",
        "    return info"
      ],
      "metadata": {
        "id": "X092AMmJPNiH"
      },
      "execution_count": 81,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "columns = [\n",
        "    \"@structureId\",\n",
        "    \"@chemicalID\",\n",
        "    \"@type\",\n",
        "    \"@molecularWeight\",\n",
        "    \"chemicalName\",\n",
        "    \"formula\",\n",
        "    \"InChI\",\n",
        "    \"InChIKey\",\n",
        "    \"smiles\",\n",
        "]\n",
        "rows = []\n",
        "for pdb_id in selected_pdb_ids:\n",
        "    ligands = get_ligands(pdb_id)\n",
        "    # If several ligands contained, take largest (first in results)\n",
        "    ligand_id, properties = max(ligands.items(), key=lambda kv: kv[1][\"Molecular weight\"])\n",
        "    rows.append(\n",
        "        [\n",
        "            pdb_id,\n",
        "            ligand_id,\n",
        "            properties[\"Component type\"],\n",
        "            properties[\"Molecular weight\"],\n",
        "            properties[\"Name\"],\n",
        "            properties[\"Formula\"],\n",
        "            properties[\"InChI descriptor\"],\n",
        "            properties[\"InChIKey descriptor\"],\n",
        "            properties[\"Stereo SMILES (OpenEye)\"],\n",
        "        ]\n",
        "    )"
      ],
      "metadata": {
        "id": "UaiNgd6FPP35"
      },
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# NBVAL_CHECK_OUTPUT\n",
        "# Change the format to DataFrame\n",
        "ligands = pd.DataFrame(rows, columns=columns)\n",
        "ligands"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "URP73kZrPTpB",
        "outputId": "a8882f03-1645-459d-97ce-3749662b05d0"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  @structureId @chemicalID        @type  @molecularWeight  \\\n",
              "0         5UG9         8AM  NON-POLYMER           445.494   \n",
              "1         5HG8         634  NON-POLYMER           377.400   \n",
              "2         5UG8         8BP  NON-POLYMER           415.468   \n",
              "3         5UGC         8BS  NON-POLYMER           417.441   \n",
              "\n",
              "                                        chemicalName          formula  \\\n",
              "0  N-[(3R,4R)-4-fluoro-1-{6-[(3-methoxy-1-methyl-...  C20 H28 F N9 O2   \n",
              "1  N-[3-({2-[(1-methyl-1H-pyrazol-4-yl)amino]-7H-...    C19 H19 N7 O2   \n",
              "2  N-[(3R,4R)-4-fluoro-1-{6-[(1-methyl-1H-pyrazol...   C19 H26 F N9 O   \n",
              "3  N-[(3R,4R)-4-fluoro-1-{6-[(3-methoxy-1-methyl-...  C18 H24 F N9 O2   \n",
              "\n",
              "                                               InChI  \\\n",
              "0  InChI=1S/C20H28FN9O2/c1-6-15(31)23-13-9-29(7-1...   \n",
              "1  InChI=1S/C19H19N7O2/c1-3-16(27)22-12-5-4-6-14(...   \n",
              "2  InChI=1S/C19H26FN9O/c1-5-15(30)24-14-9-28(8-13...   \n",
              "3  InChI=1S/C18H24FN9O2/c1-5-13(29)21-11-8-28(6-1...   \n",
              "\n",
              "                      InChIKey  \\\n",
              "0  MJLFLAORJNTNDV-CHWSQXEVSA-N   \n",
              "1  YWNHZBNRKJYHTR-UHFFFAOYSA-N   \n",
              "2  CGULPICMFDDQRH-ZIAGYGMSSA-N   \n",
              "3  XWNKXCUQRQRAFF-GHMZBOCLSA-N   \n",
              "\n",
              "                                              smiles  \n",
              "0  CCC(=O)N[C@@H]1CN(C[C@H]1F)c2nc(c3c(n2)n(cn3)C...  \n",
              "1   CCC(=O)Nc1cccc(c1)Oc2c3cc[nH]c3nc(n2)Nc4cnn(c4)C  \n",
              "2  CCC(=O)N[C@@H]1CN(C[C@H]1F)c2nc(c3c(n2)n(cn3)C...  \n",
              "3  CCC(=O)N[C@@H]1CN(C[C@H]1F)c2nc(c3c(n2)n(cn3)C...  "
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-e7c01a5e-0a36-4c0a-a706-236ed5bf3229\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>@structureId</th>\n",
              "      <th>@chemicalID</th>\n",
              "      <th>@type</th>\n",
              "      <th>@molecularWeight</th>\n",
              "      <th>chemicalName</th>\n",
              "      <th>formula</th>\n",
              "      <th>InChI</th>\n",
              "      <th>InChIKey</th>\n",
              "      <th>smiles</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5UG9</td>\n",
              "      <td>8AM</td>\n",
              "      <td>NON-POLYMER</td>\n",
              "      <td>445.494</td>\n",
              "      <td>N-[(3R,4R)-4-fluoro-1-{6-[(3-methoxy-1-methyl-...</td>\n",
              "      <td>C20 H28 F N9 O2</td>\n",
              "      <td>InChI=1S/C20H28FN9O2/c1-6-15(31)23-13-9-29(7-1...</td>\n",
              "      <td>MJLFLAORJNTNDV-CHWSQXEVSA-N</td>\n",
              "      <td>CCC(=O)N[C@@H]1CN(C[C@H]1F)c2nc(c3c(n2)n(cn3)C...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5HG8</td>\n",
              "      <td>634</td>\n",
              "      <td>NON-POLYMER</td>\n",
              "      <td>377.400</td>\n",
              "      <td>N-[3-({2-[(1-methyl-1H-pyrazol-4-yl)amino]-7H-...</td>\n",
              "      <td>C19 H19 N7 O2</td>\n",
              "      <td>InChI=1S/C19H19N7O2/c1-3-16(27)22-12-5-4-6-14(...</td>\n",
              "      <td>YWNHZBNRKJYHTR-UHFFFAOYSA-N</td>\n",
              "      <td>CCC(=O)Nc1cccc(c1)Oc2c3cc[nH]c3nc(n2)Nc4cnn(c4)C</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5UG8</td>\n",
              "      <td>8BP</td>\n",
              "      <td>NON-POLYMER</td>\n",
              "      <td>415.468</td>\n",
              "      <td>N-[(3R,4R)-4-fluoro-1-{6-[(1-methyl-1H-pyrazol...</td>\n",
              "      <td>C19 H26 F N9 O</td>\n",
              "      <td>InChI=1S/C19H26FN9O/c1-5-15(30)24-14-9-28(8-13...</td>\n",
              "      <td>CGULPICMFDDQRH-ZIAGYGMSSA-N</td>\n",
              "      <td>CCC(=O)N[C@@H]1CN(C[C@H]1F)c2nc(c3c(n2)n(cn3)C...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>5UGC</td>\n",
              "      <td>8BS</td>\n",
              "      <td>NON-POLYMER</td>\n",
              "      <td>417.441</td>\n",
              "      <td>N-[(3R,4R)-4-fluoro-1-{6-[(3-methoxy-1-methyl-...</td>\n",
              "      <td>C18 H24 F N9 O2</td>\n",
              "      <td>InChI=1S/C18H24FN9O2/c1-5-13(29)21-11-8-28(6-1...</td>\n",
              "      <td>XWNKXCUQRQRAFF-GHMZBOCLSA-N</td>\n",
              "      <td>CCC(=O)N[C@@H]1CN(C[C@H]1F)c2nc(c3c(n2)n(cn3)C...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e7c01a5e-0a36-4c0a-a706-236ed5bf3229')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-99e48626-74c0-465b-8013-8c05ce4936ba\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-99e48626-74c0-465b-8013-8c05ce4936ba')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-99e48626-74c0-465b-8013-8c05ce4936ba button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e7c01a5e-0a36-4c0a-a706-236ed5bf3229 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e7c01a5e-0a36-4c0a-a706-236ed5bf3229');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ligands.to_csv(\"PDB_top_ligands.csv\", header=True, index=False)"
      ],
      "metadata": {
        "id": "_7D87fevPYdR"
      },
      "execution_count": 84,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PandasTools.AddMoleculeColumnToFrame(ligands, \"smiles\")\n",
        "Draw.MolsToGridImage(\n",
        "    mols=list(ligands.ROMol),\n",
        "    legends=list(ligands[\"@chemicalID\"] + \", \" + ligands[\"@structureId\"]),\n",
        "    molsPerRow=top_num,\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 189
        },
        "id": "aW61ZpLUPbiJ",
        "outputId": "6d5729d4-2851-4bc4-ac68-ee15017d545a"
      },
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# NBVAL_CHECK_OUTPUT\n",
        "pairs = collections.OrderedDict(zip(ligands[\"@structureId\"], ligands[\"@chemicalID\"]))\n",
        "pairs"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9EArgAcGPfEc",
        "outputId": "0cbdf228-5502-4b91-cc49-77f1d8a2d283"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "OrderedDict([('5UG9', '8AM'),\n",
              "             ('5HG8', '634'),\n",
              "             ('5UG8', '8BP'),\n",
              "             ('5UGC', '8BS')])"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install mdanalysis"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 674
        },
        "id": "pijv3AmtgIk6",
        "outputId": "5d0e056a-2561-4030-cc52-bef90af88e37"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: mdanalysis in /usr/local/lib/python3.10/dist-packages (2.5.0)\n",
            "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (1.23.5)\n",
            "Collecting biopython>=1.80 (from mdanalysis)\n",
            "  Using cached biopython-1.81-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB)\n",
            "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (3.1)\n",
            "Requirement already satisfied: GridDataFormats>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (1.0.1)\n",
            "Requirement already satisfied: mmtf-python>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (1.1.3)\n",
            "Requirement already satisfied: joblib>=0.12 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (1.3.2)\n",
            "Requirement already satisfied: scipy>=1.5.0 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (1.10.1)\n",
            "Requirement already satisfied: matplotlib>=1.5.1 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (3.7.1)\n",
            "Requirement already satisfied: tqdm>=4.43.0 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (4.66.0)\n",
            "Requirement already satisfied: threadpoolctl in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (3.2.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (23.1)\n",
            "Requirement already satisfied: fasteners in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (0.18)\n",
            "Requirement already satisfied: gsd>=1.9.3 in /usr/local/lib/python3.10/dist-packages (from mdanalysis) (3.1.1)\n",
            "Requirement already satisfied: mrcfile in /usr/local/lib/python3.10/dist-packages (from GridDataFormats>=0.4.0->mdanalysis) (1.4.3)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (1.1.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (0.11.0)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (4.42.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (1.4.4)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (3.1.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=1.5.1->mdanalysis) (2.8.2)\n",
            "Requirement already satisfied: msgpack>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from mmtf-python>=1.0.0->mdanalysis) (1.0.5)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=1.5.1->mdanalysis) (1.16.0)\n",
            "Installing collected packages: biopython\n",
            "  Attempting uninstall: biopython\n",
            "    Found existing installation: biopython 1.77\n",
            "    Uninstalling biopython-1.77:\n",
            "      Successfully uninstalled biopython-1.77\n",
            "Successfully installed biopython-1.81\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "Bio"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from opencadd.structure.core import Structure"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0WaZ7spgf876",
        "outputId": "965139ad-ab3b-4375-9824-f5bb10034a96"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:MDAnalysis.coordinates.AMBER:netCDF4 is not available. Writing AMBER ncdf files will be slow.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Download PDB structures\n",
        "structures = [Structure.from_pdbid(pdb_id) for pdb_id in pairs]\n",
        "structures"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hveZnDkoPpU_",
        "outputId": "2ce094de-399d-46d7-c833-b27f5041ad49"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<Universe with 2664 atoms>,\n",
              " <Universe with 2716 atoms>,\n",
              " <Universe with 2632 atoms>,\n",
              " <Universe with 2542 atoms>]"
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "complexes = [\n",
        "    Structure.from_atomgroup(structure.select_atoms(f\"protein or resname {ligand}\"))\n",
        "    for structure, ligand in zip(structures, pairs.values())\n",
        "]\n",
        "complexes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OnRMUHGkgebJ",
        "outputId": "f9189677-98ca-4388-ca01-dd0d53cb1348"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<Universe with 2330 atoms>,\n",
              " <Universe with 2491 atoms>,\n",
              " <Universe with 2319 atoms>,\n",
              " <Universe with 2320 atoms>]"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Write complex to file\n",
        "for complex_, pdb_id in zip(complexes, pairs.keys()):\n",
        "    complex_.write(f\"{pdb_id}.pdb\")"
      ],
      "metadata": {
        "id": "IYTNB_zjgXza"
      },
      "execution_count": 89,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from opencadd.structure.superposition.api import align, METHODS\n"
      ],
      "metadata": {
        "id": "gdKMcn3FgnqR"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install biopython==1.77\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 345
        },
        "id": "8CY70cKXLNWd",
        "outputId": "ab9688e4-19d1-4873-905f-584ed12a7c52"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting biopython==1.77\n",
            "  Using cached biopython-1.77-cp310-cp310-linux_x86_64.whl\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from biopython==1.77) (1.23.5)\n",
            "Installing collected packages: biopython\n",
            "  Attempting uninstall: biopython\n",
            "    Found existing installation: biopython 1.81\n",
            "    Uninstalling biopython-1.81:\n",
            "      Successfully uninstalled biopython-1.81\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "mdanalysis 2.5.0 requires biopython>=1.80, but you have biopython 1.77 which is incompatible.\n",
            "bio 1.5.9 requires biopython>=1.80, but you have biopython 1.77 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed biopython-1.77\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "Bio"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import Bio; print(Bio.__version__)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cCYz3_sOL6h8",
        "outputId": "0549689b-b6c0-4db8-d3b2-4249e915d541"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1.77\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "results = align(complexes, method=METHODS[\"mda\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 341
        },
        "id": "TzDJxuhBgiMo",
        "outputId": "9a87d47f-980f-466f-a29f-c77f05e72005"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-90-75600e02e635>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0malign\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomplexes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mMETHODS\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"mda\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/opencadd/structure/superposition/api.py\u001b[0m in \u001b[0;36malign\u001b[0;34m(structures, user_select, method, **kwargs)\u001b[0m\n\u001b[1;32m     92\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mmobile\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmobiles\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     93\u001b[0m             \u001b[0mmobile\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_universe_to_atomgroup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmobile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 94\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maligner\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalculate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstructures\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mreference\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmobile\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselections\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     95\u001b[0m             \u001b[0;31m# size of whole structures\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     96\u001b[0m             \u001b[0mreference_size\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreference\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresidues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/opencadd/structure/superposition/engines/base.py\u001b[0m in \u001b[0;36mcalculate\u001b[0;34m(self, structures, selections, *args, **kwargs)\u001b[0m\n\u001b[1;32m     35\u001b[0m         \u001b[0;32massert\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstructures\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmessage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 37\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_calculate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstructures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselections\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     38\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_calculate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstructures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselections\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/opencadd/structure/superposition/engines/mda.py\u001b[0m in \u001b[0;36m_calculate\u001b[0;34m(self, structures, selections, *args, **kwargs)\u001b[0m\n\u001b[1;32m    136\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    137\u001b[0m         \u001b[0;31m# Get matching atoms of selection\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 138\u001b[0;31m         \u001b[0mselection\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malignment\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatching_selection\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mselections\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    139\u001b[0m         \u001b[0mref_atoms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mref_selection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mselect_atoms\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselection\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"reference\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    140\u001b[0m         \u001b[0mmobile_atoms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmob_selection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mselect_atoms\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselection\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"mobile\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/opencadd/structure/superposition/engines/mda.py\u001b[0m in \u001b[0;36mmatching_selection\u001b[0;34m(self, ref_selection, mob_selection)\u001b[0m\n\u001b[1;32m    229\u001b[0m                 \u001b[0mfasta\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"ref\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfasta\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"mob\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0m_empty\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0malignment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_gapped_sequences\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    230\u001b[0m                 \u001b[0mfasta\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"temp.fasta\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 231\u001b[0;31m                 selection = fasta2select(\n\u001b[0m\u001b[1;32m    232\u001b[0m                     \u001b[0;34m\"temp.fasta\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    233\u001b[0m                     \u001b[0mref_resids\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mref_resids\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/opencadd/structure/superposition/sequences.py\u001b[0m in \u001b[0;36mfasta2select\u001b[0;34m(fastafilename, ref_resids, ref_segids, target_resids, target_segids, backbone_selection)\u001b[0m\n\u001b[1;32m    113\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m     \"\"\"\n\u001b[0;32m--> 115\u001b[0;31m     \u001b[0mprotein_gapped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAlphabet\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAlphabet\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mIUPAC\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprotein\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    116\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfastafilename\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfasta\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    117\u001b[0m         \u001b[0malignment\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAlignIO\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfasta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"fasta\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malphabet\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprotein_gapped\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: module 'Bio' has no attribute 'Alphabet'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ligands = [\n",
        "    Structure.from_atomgroup(complex_.select_atoms(f\"resname {ligand}\"))\n",
        "    for complex_, ligand in zip(complexes, pairs.values())\n",
        "]\n",
        "ligands"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D2YW2kGUMrXZ",
        "outputId": "2f357d8f-5bc1-43b1-c380-131ff83506ab"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<Universe with 32 atoms>,\n",
              " <Universe with 28 atoms>,\n",
              " <Universe with 30 atoms>,\n",
              " <Universe with 30 atoms>]"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pathlib import Path"
      ],
      "metadata": {
        "id": "WPP8PfBXYr2S"
      },
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Define paths\n",
        "HERE = pathlib.Path(_dh[-1])\n",
        "DATA = HERE / \"data\""
      ],
      "metadata": {
        "id": "BZDdfmKkazJ7"
      },
      "execution_count": 103,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for ligand, pdb_id in zip(ligands, pairs.keys()):\n",
        "    ligand.write(DATA / f\"{pdb_id}_lig.pdb\")"
      ],
      "metadata": {
        "id": "QSmjwI0gMtUB"
      },
      "execution_count": 104,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ligand_files = []\n",
        "for file in \"*_lig.pdb\":\n",
        "    ligand_files.append(file)\n",
        "ligand_files"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wA7mnIvwMwzR",
        "outputId": "92555b8e-e7c1-44d5-b7fb-15a37c7b772a"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['*', '_', 'l', 'i', 'g', '.', 'p', 'd', 'b']"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "view = nglview.NGLWidget()\n",
        "for component_id, ligand in enumerate(ligands):\n",
        "    view.add_component(ligand.atoms)\n",
        "    view.remove_ball_and_stick(component=component_id)\n",
        "    view.add_licorice(component=component_id)\n",
        "view"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317,
          "referenced_widgets": [
            "ca2a51b78dd64358af22c9fb7a431f76",
            "02a76b26e79c49bb903e89cdf2c521ce",
            "75817411ad774133890c5e5a3574373a",
            "abbbf582d6634035929f1c58548eb78c",
            "2fbb88fe740645b6b425fc04f6b4c072",
            "f3e3626f16df4985b120bd0725668e01",
            "84f30a7b8e874c7ba25f1e091a97212f",
            "1bf6a17f1c884600a1411354d0135d30",
            "f584524bfd3c4aabb0126e63d1f0d793",
            "ca55c46275854c79bc2b1a9981be5cdb",
            "22a58bd8e695438ca4df3ff403bb0b8a",
            "355ab8a08d1340a58440e85e200c5427",
            "2df161c84a824dce86b955dc906a540a"
          ]
        },
        "id": "9oefQXduNNZL",
        "outputId": "242d475a-0015-4c6e-dcbd-e35fdd224b25"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "NGLWidget()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ca2a51b78dd64358af22c9fb7a431f76"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
                }
              }
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "view.render_image(trim=True, factor=2, transparent=True);"
      ],
      "metadata": {
        "id": "GHYk82dQNV2K"
      },
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "view._display_image()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "qbqOTx55NaXq",
        "outputId": "a3d344c0-86c2-4447-8c20-7d6a5ceaa518"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    }
  ]
}