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Code for generating movies of the most relevant movement modes of proteins from their PDB files, using rigidity clustering analysis

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RudoRoemer/pdb2movie

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pdb2movie

Code for generating movies of the most relevant movement modes of proteins from their PDB files, using rigidity clustering analysis

Requirements:
PyMOL or VMD
Python libraries: argparse
ffmpeg

Instructions:

Recompiling FIRST and diagstd is necessary!

  1. Go to FIRST-190916-SAW/src and run 'make'.
  2. You should be ready to go!

(Note that if your C++/Fortran compilers are not the ones we use, you might need to edit some Makefiles.)

Usage:

python pdb2movie.py FILE [options]
FILE is your desired PDB file

Options:

--keep MOLECULE LIST - Stops the cleaning routine from removing the listed molecules from the PDB file
--output PATH - Sets the output location for the simulations and videos
--waters - Keeps water molecules in the PDB file (equivalent to --keep HOH)
--confs CONFS - Total number of configurations to be calculated
--freq FREQ - Frequency of saving intermediate configurations
--step STEP - Size of random step
--dstep DSTEP - Size of directed step
--res WID HEI - Video resolution (width, height), range [16, 8192]
--modes MODE LIST - Movement modes to be investigated
--ecuts ECUTS LIST - Energy cutoff values
--video FILE - Python file with PyMOL commands to be run before generating video
--threed - Generates anaglyph stereo videos
--combi - Creates videos combining positive and negative directions for each mode/cutoff energy
--multiple - Keeps multiple chains from the original PDB file (default: uses only chain A)
--videocodec - Use 'mp4' or 'hevc' to enode the videos, resulting in .mp4 or .mov files (defaults to mp4)
--drawingengine - Use 'vmd' or 'pymol' to render pdb files to frames (defaults to pymol for now) --fps - Frames per second of the videos, range [1, 240]

See also the web-server-based implementation at https://pdb2movie.warwick.ac.uk.

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Code for generating movies of the most relevant movement modes of proteins from their PDB files, using rigidity clustering analysis

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