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Required Software __________________ diff --git a/docs/source/Background SIRAH.rst b/docs/source/Background SIRAH.rst new file mode 100644 index 0000000..9546485 --- /dev/null +++ b/docs/source/Background SIRAH.rst @@ -0,0 +1,282 @@ +Background +================== + +Coarse-Grained (CG) models are cost-effective approximations developed to lessen the computational cost associated with MD simulations. CG models consist of effective particles, referred to as beads, that represent groups of corresponding atoms. CG models can vary in resolution, ranging from supra-CG levels where a single bead represents an entire protein, to near-atomistic models that preserve most of the chemical characteristics (see a recent review on CG models [:ref:`1 `]). + +As a CG force field, `SIRAH `_ covers parameters and topologies for aqueous solvent, phospholipids, DNA, metal ions, and proteins. A recent update introduced modifications to bonded and non-bonded parameters, protonation states, post-translational modifications, and compatibility improvements for different force fields (see [:ref:`2 `]). + + +Overview +--------- + +In the SIRAH force field for CG simulations, the mapping from atomistic to CG representations entails strategically placing effective interactive beads at pivotal atoms involved in the structure or at atoms that form crucial intermolecular interactions (**Figure 1**). The distribution of these beads corresponds to intended interactions of functional groups based on size and charge, resulting in a heterogeneous distribution with higher bead density in regions that establish more diverse interactions. + +.. figure:: ../images/mousepad-old.png + :align: center + :width: 100% + + **Figure 1.** SIRAH force field CG representation. + +SIRAH employs a classical two-body Hamiltonian, facilitating its use in various MD engines without the need for extensive learning or format changes. In the following sections, we provide a synopsis of the CG models developed by SIRAH; however, for a more comprehensive material, please refer to our review paper on SIRAH development (see [:ref:`3 `]). + + +DNA model +----------------- + +.. figure:: ../images/mousepad-old-dna.png + :align: center + :width: 80% + + **Figure 2.** SIRAH force field DNA CG representation. + +The SIRAH's DNA model involves six effective beads representing each of the four CG nucleotides (**Figure 2**) (see [:ref:`4 `] and [:ref:`5 `] for more details). The mapping strategy considers the 5' - 3' prime polarity and electrostatic complementarity between A-T and G-C base pairs. The backbone is represented by two beads at the phosphate and C5' Carbon positions, while three beads on the Watson-Crick edge ensure base pair recognition. The five-membered sugar ring is depicted by a single bead situated at the C1' position, linking the backbone to the Watson-Crick edge. + + +Explicit solvent +--------------------- + +.. figure:: ../images/mousepad-old-solvent.png + :align: center + :width: 60% + + **Figure 3.** SIRAH force field Solvent CG representation. + +In tandem with the DNA model development, a CG aqueous solvent was created, featuring CG water (WatFour or WT4) and monovalent electrolytic ions (sodium, potassium, chloride) (**Figure 3**) (see [:ref:`6 `]). The WT4 model resembles a bulkier "water molecule". The monovalent ions are represented by single beads with a net charge of +/- 1e. Supra-CG solvent (WatElse or WLS) is also available (see [:ref:`7 `]) + + +Protein model +--------------------- + +.. figure:: ../images/mousepad-old-amino.png + :align: center + :width: 90% + + **Figure 4.** SIRAH force field amino acids CG representation. + +The CG protein model in SIRAH employs varying bead sizes to reflect different amino acid interactions. The latest version [:ref:`2 `], refined in 2019, has significantly improved the ability to reproduce protein structures. The atomistic to CG mapping of protein side chains follows the DNA model philosophy, with effective beads placed at selected atoms along side chains, representing hydrophobic, aromatic, and polar interactions (**Figure 4**). + + +Phospholipids +------------------ + +.. figure:: ../images/cg-phospholipids.jpg + :align: center + :width: 90% + + **Figure 5.** SIRAH force field phospholipids CG representation. + +Following the completion of DNA, aqueous solvent, and protein models, the SIRAH force field aimed to incorporate a suitable CG lipid representation for simulating membrane proteins (**Figure 5**). Focusing on prototypical phospholipids, including phosphatidyl-choline (PC), -ethanolamine (PE), and –serine (PS) heads, along with myristoyl (M), palmitic (P), and oleic (O) acyl chains, SIRAH enabled simulations of diverse eukaryotic membrane components (see [:ref:`8 `] for more details). + +Accurate representations of the SarcoEndoplasmic Reticulum Calcium (SERCA) pump's tilted orientation in a DMPC bilayer (see [:ref:`8 `]), the electrostatics-driven opening of the Connexin 26 channels (see [:ref:`9 `]), and the Zika Virus-Like Particle (see [:ref:`10 `]) are some examples of SIRAH's phospholipids usage. + + +Divalent cations +--------------------- + +The SIRAH force field offers a set of interaction parameters for Calcium, Magnesium, and Zinc ions, covering over 80% of the metal-bound structures documented in the PDB. Simulations conducted on several proteins and DNA systems demonstrate the feasibility of these parameters (see [:ref:`11 `]) . + + +Protein glycosylations +--------------------------------------- + +We have recently developed a CG representation that can accurately simulate a diverse range of polysaccharides and frequent glycosylation patterns found in proteins. The adaptability of the expanded collection of CG molecules offered by SIRAH is demonstrated by examples of its application to N-glycosylated proteins, such as antibody recognition and calcium-mediated glycan-protein interactions (see [:ref:`12 `]). + + +Multiscale simulations +----------------------- + +.. figure:: ../images/virus-cg.jpg + :align: center + :width: 60% + + **Figure 6.** SIRAH force field Virus-Like Particle CG representation. + +The development of the SIRAH force field in a classical two-body Hamiltonian framework has facilitated multiscale simulations. + +Available multiscale implementations in SIRAH: + +- An all-atoms/CG model covalently linking both resolutions within a nucleic acid chain (see [:ref:`13 `]); + +- A multiresolution solvent model allowing the mixture of fully atomistic solutes with a shell of atomistic solvent surrounded by CG water, applicable to highly solvated systems like viral capsids (see [:ref:`14 `]). + +- A triple solvation scheme, treating water at all-atoms, CG, and supraCG levels, is also available (see [:ref:`14 `]). + +This is particularly useful for complex cellular systems and has been applied to assemble and simulate VLPs systems in an onion-shaped configuration using CG water (WT4) and supra-CG solvent (WLS) (**Figure 6**) (see [:ref:`10 `] and [:ref:`14 `]). + + + +References +------------- + +.. _ref1: + +[1] Borges-Araújo, L.; Patmanidis, I.; Singh, A. P.; Santos, L. H. S.; Sieradzan, A. K.; Vanni, S.; Czaplewski, C.; Pantano, S.; Wataru Shinoda, W.; Monticelli, L.; Liwo, A.; Marrink, S. J.; Souza, P. C. T. Pragmatic Coarse-Graining of Proteins: Models and Applications. Journal of Chemical Theory and Computation. 2023. |Review-2| |Review2-cit| + +.. |Review-2| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.3c00733-blue?color=blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.3c00733 + +.. |Review2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.3c00733 + :alt: Citation + :target: https://scholar.google.com.uy/scholar?cites=14982031192725054357 + +.. _ref2: + +[2] Machado, M. R.; Barrera, E. E.; Klein, F.; Soñora, M.; Silva, S.; Pantano, S. The SIRAH 2.0 Force Field: Altius, Fortius, Citius. Journal of Chemical Theory and Computation 2019, 15, 2719–2733. |SIRAH2.0| |SIRAH2.0-cit| + +.. |SIRAH2.0| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.9b00006-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.9b00006 + +.. |SIRAH2.0-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.9b00006 + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=5136612330374064800 + +.. _ref3: + +[3] Klein, F.; Soñora, M.; Santos, L. H.; Frigini, E. N.; Ballesteros-Casallas, A.; Machado, M. R.; Pantano, S. The SIRAH force field: a suite for simulations of complex biological systems at the coarse-grained and multiscale levels. Journal of Structural Biology 2023, 107985. |Review| |Review-cit| + +.. |Review| image:: https://img.shields.io/badge/DOI-10.1016%2Fj.jsb.2023.107985-blue + :alt: Access the paper + :target: https://doi.org/10.1016/j.jsb.2023.107985 + +.. |Review-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1016%2Fj.jsb.2023.107985 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=11014340861876399425 + +.. _ref4: + +[4] Dans, P. D.; Zeida, A.; Machado, M. R.; Pantano, S. A Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit Electrostatics. Journal of Chemical Theory and Computation 2010, 6, 1711–1725. |DNA| |DNA-cit| + +.. |DNA| image:: https://img.shields.io/badge/DOI-10.1021%2Fct900653p-blue + :alt: Access the paper + :target: https://doi.org/10.1021/ct900653p + +.. |DNA-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Fct900653p + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=12499613729973955498 + +.. _ref5: + +[5] Zeida, A.; Machado, M. R.; Dans, P. D.; Pantano, S. Breathing, bubbling, and bending: DNA flexibility from multimicrosecond simulations. Physical Review E, 2012, 86. |DNA-2| |DNA-2-cit| + +.. |DNA-2| image:: https://img.shields.io/badge/DOI-10.1103%2FPhysRevE.86.021903-blue + :alt: Access the paper + :target: https://doi.org/10.1103/PhysRevE.86.021903 + +.. |DNA-2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1103%2FPhysRevE.86.021903 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=9768293008048576462 + + +.. _ref6: + +[6] Darré, L.; Machado, M. R.; Dans, P. D.; Herrera, F. E.; Pantano, S. Another Coarse Grain Model for Aqueous Solvation: WAT FOUR? Journal of Chemical Theory and Computation 2010, 6, 3793–3807. |Solvent| |Solvent-cit| + +.. |Solvent| image:: https://img.shields.io/badge/DOI-10.1021%2Fct100379f-blue + :alt: Access the paper + :target: https://doi.org/10.1021/ct100379f + +.. |Solvent-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Fct100379f + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=11533073503238221292 + +.. _ref7: + +.. |VLP1| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.7b00659-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.7b00659 + +.. |VLP1-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.7b00659 + :alt: Access the paper + :target: https://scholar.google.com/scholar?cites=16637391138490147245 + +[7] Machado, M. R.; González, H. C.; Pantano, S. MD Simulations of Virus like Particles with Supra CG Solvation Affordable to Desktop Computers. Journal of Chemical Theory and Computation 2017, 13, 5106–5116. |VLP1| |VLP1-cit| + +.. _ref8: + +[8] Barrera, E. E.; Machado, M. R.; Pantano, S. Fat SIRAH: Coarse-Grained Phospholipids To Explore Membrane–Protein Dynamics. Journal of Chemical Theory and Computation 2019, 15, 5674–5688. |FatSirah| |FatSirah-cit| + +.. |FatSirah| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.9b00435-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.9b00435 + +.. |FatSirah-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.9b00435 + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=13191972720970339574 + +.. _ref9: + +[9] Zonta, F.; Buratto, D.; Crispino, G.; Carrer, A.; Bruno, F.; Yang, G.; Mammano, F.; Pantano, S. Cues to Opening Mechanisms From in Silico Electric Field Excitation of Cx26 Hemichannel and in Vitro Mutagenesis Studies in HeLa Transfectans. Frontiers in Molecular Neuroscience 2018, 11, 170. |MemProt-1| |MemProt-cit| + +.. |MemProt-1| image:: https://img.shields.io/badge/DOI-10.3389%2Ffnmol.2018.00170-blue + :alt: Access the paper + :target: https://doi.org/10.3389/fnmol.2018.00170 + +.. |MemProt-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.3389%2Ffnmol.2018.00170 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=7027056542531206464&as_sdt=2005&sciodt=0,5&hl + + +.. _ref10: + +[10] Soñora, M.; Martínez, L.; Pantano, S.; Machado, M. R. Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus. Journal of Chemical Information and Modeling 2021, 61, 408–422. |VLP2| |VLP2-cit| + +.. |VLP2| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jcim.0c01205-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jcim.0c01205 + +.. |VLP2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jcim.0c01205 + :alt: Access the paper + :target: https://scholar.google.com/scholar?cites=8645160591236740149 + + +.. _ref11: + +[11] Klein, F.; Cáceres, D.; Carrasco, M. A.; Tapia, J. C.; Caballero, J.; Alzate-Morales, J.; Pantano, S. Coarse-Grained Parameters for Divalent Cations within the SIRAH Force Field. Journal of Chemical Information and Modeling 2020, 60, 3935–3943. |Metal| |Metal-cit| + +.. |Metal| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jcim.0c00160-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jcim.0c00160 + +.. |Metal-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jcim.0c00160 + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=2583810250614166915 + + +.. _ref12: + +[12] Garay, P. G.; Machado, M. R.; Verli, H.; Pantano, S. SIRAH late harvest: coarse-grained models for protein glycosylation. Journal of Chemical Theory and Computation 2024. |GLY| |GLY-cit| + +.. |GLY| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.3c00783-blue + :alt: Access the paper + :target: https://pubs.acs.org/doi/10.1021/acs.jctc.3c00783 + +.. |GLY-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.3c00783 + :alt: Citation + + +.. _ref13: + +[13] Machado, M. R.; Zeida, A.; Darré, L.; Pantano, S. From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field. Interface Focus 2019, 9, 20180085. |MC2| |MC2-cit| + +.. |MC2| image:: https://img.shields.io/badge/DOI-10.1098%2Frsfs.2018.0085-blue?label=DOI + :alt: Access the paper + :target: https://doi.org/10.1098/rsfs.2018.0085 + +.. |MC2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1098%2Frsfs.2018.0085 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=5473055142318037579 + +.. _ref14: + +[14] Machado, M. R.; González, H. C.; Pantano, S. MD Simulations of Virus like Particles with Supra CG Solvation Affordable to Desktop Computers. Journal of Chemical Theory and Computation 2017, 13, 5106–5116. |MC1| |MC1-cit| + +.. |MC1| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.7b00659-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.7b00659 + +.. |MC1-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.7b00659 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=16637391138490147245 + diff --git a/docs/source/Background SIRAH_complete.rst b/docs/source/Background SIRAH_complete.rst new file mode 100644 index 0000000..255f38f --- /dev/null +++ b/docs/source/Background SIRAH_complete.rst @@ -0,0 +1,266 @@ +Background +================== + +In recent decades, the field of molecular dynamics (MD) simulations has undergone significant progress and development, allowing for the investigation of biological systems at nanoseconds to microsecond scales. However, complex systems involving millions of atoms or large-size protein assemblies are still too computationally expensive to be studied in atomistic detail without the aid of specialized supercomputers. Thus, the computational cost associated with MD simulations has driven the development of cost-effective approximations, particularly Coarse-Grained (CG) models, which attempt to increase system complexity and spatiotemporal sampling. The resolution of CG models has become essential for investigating molecular processes at the nano and meso dimensions and addressing mechanisms that have been previously inaccessible to traditional modeling methods. CG models consist of effective particles, referred to as beads, that represent groups of corresponding atoms. CG models can vary in resolution, ranging from supra-CG levels where a single bead represents an entire protein, to near-atomistic models that preserve most of the chemical characteristics [:ref:`1 `]. + +Currently, one of the most prominent CG models is the `SIRAH `_ (Southamerican Initiative for a Rapid and Accurate Hamiltonian) force field, which was developed by the `Biomolecular Simulations Group `_ `Institut Pasteur de Montevideo `_. It covers parameters and topologies for aqueous solvent, phospholipids, DNA, metal ions, and proteins. A recent update introduced modifications to bonded and non-bonded parameters, protonation states, post-translational modifications, and compatibility improvements for different force fields [:ref:`2 `]. + + +The SIRAH force field for CG simulations +----------------------------------------- + +The distinguishing features of the SIRAH force field for CG simulations lie in its approach to mapping from atomistic to CG representations and its strategic selection of interaction potentials. The mapping procedure entails strategically placing effective interactive beads at pivotal atoms involved in the structure or at atoms that form crucial intermolecular interactions (**Figure 1**). The distribution of these beads corresponds to intended interactions of functional groups based on size and charge, resulting in a heterogeneous distribution with higher bead density in regions that establish more diverse interactions. + +.. figure:: ../images/mousepad-old.png + :align: center + :width: 100% + + **Figure 1.** SIRAH force field CG representation. + +SIRAH employs a classical two-body Hamiltonian, facilitating its use in various MD engines without the need for extensive learning or format changes. This choice enables anyone familiar with standard all-atoms MD simulations in engines like AMBER or GROMACS to run CG simulations using SIRAH seamlessly. The classical Hamiltonian requires the determination of numerous parameters, but SIRAH's mapping strategy significantly reduces this burden. Equilibrium distances are derived directly from statistical data, quantum-level calculations, or canonical conformations, minimizing the number of parameters to be determined. + +The initial CG model for DNA served as the foundation for SIRAH, with force constants, partial charges, and Lennard-Jones (LJ) parameters derived through trial and error simulations on DNA segments. The approach of transferring and adapting parameters based on similar functional groups ensures analogous interaction parameters for diverse molecular moieties. SIRAH's versatility is exemplified through its CG models for different biomolecular families. In the following sections, we provide a synopsis of the CG models developed by SIRAH; however, for a more comprehensive material, please refer to [:ref:`3 `]. + + +The CG DNA model +----------------- + +The SIRAH's DNA model involves six effective beads representing each of the four CG nucleotides (**Figure 2**) [:ref:`4 `]. The mapping strategy considers the 5' - 3' prime polarity and electrostatic complementarity between A-T and G-C base pairs. The backbone is represented by two beads at the phosphate and C5' Carbon positions, while three beads on the Watson-Crick edge ensure base pair recognition. The five-membered sugar ring is depicted by a single bead situated at the C1' position, linking the backbone to the Watson-Crick edge. + +.. figure:: ../images/mousepad-old-dna.png + :align: center + :width: 80% + + **Figure 2.** SIRAH force field DNA CG representation. + +By selecting this mapping option, the specific base-pair recognition of the B-form DNA is maintained, and the distortion effects of mismatches are captured precisely. However, it has limitations, since it excludes less frequent inter-nucleotide interactions, such as sugar edge or Hoogsteen base pairs. + +In SIRAH's DNA model, bead sizes determined by LJ parameters are heterogeneous, maintaining correct stacking distances in a double-stranded configuration. The effective beads representing bases adopt LJ sizes from the Barcelona force field, while those representing the backbone have larger sizes. The partial charges, assigned to ensure electrostatic recognition, are determined to reproduce the electrostatic potential of the force field in the grooves of a double-stranded structure. The initial mass distribution allows MD simulations with a timestep of 5 fs. + +This CG DNA model reproduces the structure and dynamics of double-stranded DNA comparable to atomistic force fields and demonstrates spontaneous formation of large "bubbles" within DNA, fraying, rehybridization, and matches experimentally determined persistence lengths of single-stranded filaments [:ref:`4 `]. + + +The WatFour model for CG explicit solvent +------------------------------------------------ + +In tandem with the DNA model development, a CG aqueous solvent was created, featuring CG water and monovalent electrolytic ions (sodium, potassium, chloride) (**Figure 3**) [:ref:`5 `]. + +.. figure:: ../images/mousepad-old-solvent.png + :align: center + :width: 60% + + **Figure 3.** SIRAH force field Solvent CG representation. + +Unlike typical CG water, SIRAH's WatFour (WT4) model aimed to replicate the structure of an elementary water cluster, including a central water surrounded by four identical molecules forming a tetrahedron. Hydrogen atoms were removed, and only the oxygen atoms at the tetrahedron's vertices were retained, connected by harmonic bonds. This flexible tetrahedral structure generated its own dielectric permittivity and electrostatic screening by adding partial charges to the four beads, creating a quadrupole with two positively and two negatively charged beads. The partial charges were adopted from the SPC water model to ensure compatibility with fully atomistic water models for multiscale simulations [:ref:`5 `]. + +Iterative fitting was performed on the LJ energy well depth, which corresponded to the experimental diffusion coefficient of pure water at 300 K, and the bead size, which mirrored the second solvation peak of water. The mass of the beads was set to achieve a density of 1 kg/dl. The WT4 model, which resembled a bulkier "water molecule," corresponded to the second apex of the radial distribution function for atomistic water. + +Monovalent ions in SIRAH, represented by single beads with a net charge of +/- 1e, were developed based on neutron scattering data, reflecting the chemical identity of sodium, potassium, and chloride ions [:ref:`5 `]. The ions' depth of the LJ well matched that of the WT4 beads, offering the flexibility to adjust ionic strength by modifying added salt in the simulation box. The incorporation of electrolytic ions and accurate electrostatic description using the Particle Mesh Ewald summation methods contribute to the relevant features of SIRAH. + + +The CG protein model +--------------------- + +The CG protein model in SIRAH employs varying bead sizes to reflect different amino acid interactions. The latest version [:ref:`2 `], refined in 2019, has significantly improved the ability to reproduce protein structures. The atomistic to CG mapping of protein side chains follows the DNA model philosophy, with effective beads placed at selected atoms along side chains, representing hydrophobic, aromatic, and polar interactions (**Figure 4**). + +.. figure:: ../images/mousepad-old-amino.png + :align: center + :width: 90% + + **Figure 4.** SIRAH force field amino acids CG representation. + +Hydrophobic amino acids are neutral beads at specific positions with an LJ diameter of 0.42 nm. Aromatic amino acids use smaller beads, 0.35 nm, for stacking-like interactions, with partial charges on certain residues to preserve Hydrogen bond possibilities. Polar amino acids retain beads in functional groups, while acidic and basic amino acids have partial charges which add up to a net charge of +/- 1e. + +The aminoacidic backbone is represented with three beads for Nitrogen, Cα Carbon, and carboxylic Oxygen positions, facilitating easy transformation between all-atoms and CG. Bonded parameters for amino acids follow the rules outlined for DNA, with force constants for bond and angular stretching adapted from the same set of parameters. This approach has been found to be effective and time-efficient. + +In version 2.2 [:ref:`2 `], all bead masses are set to 50 a.u., and common post-translational modifications, including phosphorylation and acetylation, and different protonation states are available. In addition, divalent ion parameters for Zinc, Magnesium, and Calcium, derived from statistical analyses and validated through multiple CG simulations, enable SIRAH simulations of a wide range of metal-bound macromolecules. + + +CG models for phospholipids +--------------------------------------- + +Following the completion of DNA, aqueous solvent, and protein models, the SIRAH force field aimed to incorporate a suitable CG lipid representation for simulating membrane proteins. Focusing on prototypical phospholipids, including phosphatidyl-choline (PC), -ethanolamine (PE), and –serine (PS) heads, along with myristoyl (M), palmitic (P), and oleic (O) acyl chains, SIRAH enabled simulations of diverse eukaryotic membrane components [:ref:`6 `]. Utilizing the existing functional groups in the force field, parameterization of these lipids required minimal modifications, ensuring compatibility and accurate replication of lipid bilayer mechanical properties such as thickness, areas per lipid, order parameter, etc., and their dependence with the temperature. + +During protein simulations embedded in lipid bilayers, spurious insertions of acyclic tails into the protein core were observed. To address this, specific interactions between hydrophobic protein side chains and acyl chains were set outside Lorentz-Berthelot combination rules, yielding accurate representations of the SarcoEndoplasmic Reticulum Calcium (SERCA) pump's tilted orientation in a DMPC bilayer [:ref:`6 `]. This modification facilitated simulations of electrostatics-driven opening of Connexin 26 channels, demonstrating predictive power in identifying mutations inhibiting channel opening [:ref:`7 `]. The approach was also employed for cost-effective simulations of entire viral capsids and envelopes, allowing construction and simulation of a Zika Virus-Like Particles on a multi-microsecond time scale [:ref:`8 `]. + + +Multiscale simulations +----------------------- + +The development of the SIRAH force field in a classical two-body Hamiltonian framework has facilitated multiscale simulations, eliminating the need for non-Hamiltonian interaction terms and ensuring efficiency without communication delays between software modules. + +Two multiscale implementations in SIRAH are emphasized: first, an all-atoms/CG model covalently linking both resolutions within a nucleic acid chain [:ref:`9 `]; second, a multiresolution solvent model allowing the mixture of fully atomistic solutes with a shell of atomistic solvent surrounded by CG water, applicable to highly solvated systems like viral capsids [:ref:`10 `]. + +A triple solvation scheme, treating water at all-atoms, CG, and supraCG levels, is also available. This is particularly useful for complex cellular systems and has been applied to assemble and simulate VLPs systems in an onion-shaped configuration using CG water (WT4) and supra-CG solvent (WLS) [:ref:`10 `]. MD simulations of entire VLPs, such as those studying Flaviviruses with membranes and proteinaceous envelopes, offer crucial insights into their dynamics and are vital for understanding biological systems at a level accessible only through computer simulations [:ref:`8 `]. + + +Overwriting combination rules +-------------------------------- + +The SIRAH force field introduces a modification in the calculation of LJ interactions to address issues with electrolytic ions in proteins and DNA. Unlike traditional MD packages using Lorentz-Berthelot (LB) combination rules, SIRAH employs an "outside-of-LB trick" that allows specific LJ parameters for certain bead pairs, enabling the fine-tuning of interactions. This approach provides adaptability to regulate interactions applying only to specific bead pairs, in accordance with various physicochemical settings [:ref:`3 `]. + +SIRAH comprises 56 different bead types, with 197 interactions defined outside LB combination rules among 1540 possible pair combinations [:ref:`3 `]. The modifications include cation-π interactions between aromatic residues and Lysine, methylated Lysine, and zwitterionic N-terminal beads. The force field corrects the size of backbone beads, crucial for forming α helices and Hydrogen bonds, ensuring compatibility with compact structures. It facilitates the formation of secondary structure elements and enhances interactions with other force field components. + + +Performance +------------ + +The latest version of the SIRAH force field leverages GPU implementations in GROMACS and AMBER, enabling CG simulations on desktop computers at a rate of a few microseconds per day for medium-sized systems. Larger systems of around a million particles can achieve speeds of hundreds of nanoseconds per day [:ref:`2 `]. + +Recently, to illustrate SIRAH's performance, a comparison was made between a SIRAH CG simulation and an atomistic simulation (Amber's FF14SB) of the SARS-CoV-2 Spike protein's receptor binding domain (RBD) with human ACE2 and the amino acid transporter B0AT1 (see [:ref:`3 `]). The CG model exhibited a 60-fold speedup, simulating approximately 660 ns per day with a 20 fs time step, compared to the atomistic model's 11 ns per day with a 2 fs time step, using the same system. + +Nevertheless, it is essential to take into account the constraints of the force field beyond its speed implications, as various force fields may possess distinct capabilities. Thus, exercise caution when making direct comparisons between CG force fields, considering their distinct strengths and drawbacks. + + +Limitations +------------ + +Although the SIRAH force field offers speed, efficiency, and multiscale capabilities for simulating biomolecular systems, it has some limitations such as: + +* It potentially compromises precision in both structural and energetic aspects. SIRAH, similar to other CG force fields, faces limitations in scenarios that demand atomic-level precision, such as interactions mediated by single water molecules or ligands with specific binding sites. Examples like potassium channels or aquaporins, where individual water molecules play a crucial role, may be challenging for CG models that combine multiple water molecules into a single effective bead. + +* Protein folding simulations are not extensively explored. Although SIRAH is successful in reproducing spontaneous aggregation and small peptide folding, the unbiased formation of large helical segments remains challenging. + +* The molecular diversity in biological systems is vast, making it nearly impossible to encompass all relevant biomolecules. Establishing a generally valid methodology for creating arbitrary molecular topologies involves converting new topologies from all-atom to CG, relying on experimental data, organic chemistry knowledge, and physicochemical intuition. + + +Perspectives +------------- + +The rapid advancement of computer power has established MD as a valuable tool in biomedical sciences for understanding intricate processes and vast biological systems. Developing force fields that are universally applicable to all biological molecular families and enable communication at different levels of molecular resolution is a crucial and complex task. Recently, the SIRAH force field expanded its scope by incorporating glycans to simulate polysaccharide chains and protein glycosylation (see [:ref:`11 `]). In addition, the lipid diversity will be enhanced by including sphingomyelins, ceramides, and cholesterol, crucial components of endoplasmic reticulum membranes and flaviviral envelopes. Additionally, testing parameters for POPG, a lipid found in bacterial membranes, is underway to improve the realism of antibiotic peptide mode of action descriptions. In the medium term, there are plans to introduce a coarse-grained model for RNA, which is crucial for the description of viral particles and a major area of focus for the group's ongoing research. + + +References +------------- + +.. _ref1: + +[1] Borges-Araújo, L.; Patmanidis, I.; Singh, A. P.; Santos, L. H. S.; Sieradzan, A. K.; Vanni, S.; Czaplewski, C.; Pantano, S.; Wataru Shinoda, W.; Monticelli, L.; Liwo, A.; Marrink, S. J.; Souza, P. C. T. Pragmatic Coarse-Graining of Proteins: Models and Applications. Journal of Chemical Theory and Computation. 2023. |Review-2| |Review2-cit| + +.. |Review-2| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.3c00733-blue?color=blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.3c00733 + +.. |Review2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.3c00733 + :alt: Citation + :target: https://scholar.google.com.uy/scholar?cites=14982031192725054357 + +.. _ref2: + +[2] Machado, M. R.; Barrera, E. E.; Klein, F.; Soñora, M.; Silva, S.; Pantano, S. The SIRAH 2.0 Force Field: Altius, Fortius, Citius. Journal of Chemical Theory and Computation 2019, 15, 2719–2733. |SIRAH2.0| |SIRAH2.0-cit| + +.. |SIRAH2.0| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.9b00006-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.9b00006 + +.. |SIRAH2.0-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.9b00006 + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=5136612330374064800 + +.. _ref3: + +[3] Klein, F.; Soñora, M.; Santos, L. H.; Frigini, E. N.; Ballesteros-Casallas, A.; Machado, M. R.; Pantano, S. The SIRAH force field: a suite for simulations of complex biological systems at the coarse-grained and multiscale levels. Journal of Structural Biology 2023, 107985. |Review| |Review-cit| + +.. |Review| image:: https://img.shields.io/badge/DOI-10.1016%2Fj.jsb.2023.107985-blue + :alt: Access the paper + :target: https://doi.org/10.1016/j.jsb.2023.107985 + +.. |Review-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1016%2Fj.jsb.2023.107985 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=11014340861876399425 + +.. _ref4: + +[4] Dans, P. D.; Zeida, A.; Machado, M. R.; Pantano, S. A Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit Electrostatics. Journal of Chemical Theory and Computation 2010, 6, 1711–1725. |DNA| |DNA-cit| + +.. |DNA| image:: https://img.shields.io/badge/DOI-10.1021%2Fct900653p-blue + :alt: Access the paper + :target: https://doi.org/10.1021/ct900653p + +.. |DNA-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Fct900653p + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=12499613729973955498 + +.. _ref5: + +[5] Darré, L.; Machado, M. R.; Dans, P. D.; Herrera, F. E.; Pantano, S. Another Coarse Grain Model for Aqueous Solvation: WAT FOUR? Journal of Chemical Theory and Computation 2010, 6, 3793–3807. |Solvent| |Solvent-cit| + +.. |Solvent| image:: https://img.shields.io/badge/DOI-10.1021%2Fct100379f-blue + :alt: Access the paper + :target: https://doi.org/10.1021/ct100379f + +.. |Solvent-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Fct100379f + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=11533073503238221292 + +.. _ref6: + +[6] Barrera, E. E.; Machado, M. R.; Pantano, S. Fat SIRAH: Coarse-Grained Phospholipids To Explore Membrane–Protein Dynamics. Journal of Chemical Theory and Computation 2019, 15, 5674–5688. |FatSirah| |FatSirah-cit| + +.. |FatSirah| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.9b00435-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.9b00435 + +.. |FatSirah-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.9b00435 + :alt: Citation + :target: https://scholar.google.com/scholar?oi=bibs&hl=es&cites=13191972720970339574 + +.. _ref7: + +[7] Zonta, F.; Buratto, D.; Crispino, G.; Carrer, A.; Bruno, F.; Yang, G.; Mammano, F.; Pantano, S. Cues to Opening Mechanisms From in Silico Electric Field Excitation of Cx26 Hemichannel and in Vitro Mutagenesis Studies in HeLa Transfectans. Frontiers in Molecular Neuroscience 2018, 11, 170. |MemProt-1| |MemProt-cit| + +.. |MemProt-1| image:: https://img.shields.io/badge/DOI-10.3389%2Ffnmol.2018.00170-blue + :alt: Access the paper + :target: https://doi.org/10.3389/fnmol.2018.00170 + +.. |MemProt-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.3389%2Ffnmol.2018.00170 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=7027056542531206464&as_sdt=2005&sciodt=0,5&hl + + +.. _ref8: + +[8] Soñora, M.; Martínez, L.; Pantano, S.; Machado, M. R. Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus. Journal of Chemical Information and Modeling 2021, 61, 408–422. |VLP2| |VLP2-cit| + +.. |VLP2| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jcim.0c01205-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jcim.0c01205 + +.. |VLP2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jcim.0c01205 + :alt: Access the paper + :target: https://scholar.google.com/scholar?cites=8645160591236740149 + +.. _ref9: + +[9] Machado, M. R.; Zeida, A.; Darré, L.; Pantano, S. From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field. Interface Focus 2019, 9, 20180085. |MC2| |MC2-cit| + +.. |MC2| image:: https://img.shields.io/badge/DOI-10.1098%2Frsfs.2018.0085-blue?label=DOI + :alt: Access the paper + :target: https://doi.org/10.1098/rsfs.2018.0085 + +.. |MC2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1098%2Frsfs.2018.0085 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=5473055142318037579 + +.. _ref10: + +[10] Machado, M. R.; González, H. C.; Pantano, S. MD Simulations of Virus like Particles with Supra CG Solvation Affordable to Desktop Computers. Journal of Chemical Theory and Computation 2017, 13, 5106–5116. |MC1| |MC1-cit| + +.. |MC1| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.7b00659-blue + :alt: Access the paper + :target: https://doi.org/10.1021/acs.jctc.7b00659 + +.. |MC1-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.7b00659 + :alt: Citation + :target: https://scholar.google.com/scholar?cites=16637391138490147245 + +.. _ref11: + +[11] Garay, P. G.; Machado, M. R.; Verli, H.; Pantano, S. SIRAH late harvest: coarse-grained models for protein glycosylation. Journal of Chemical Theory and Computation 2024. |GLY| |GLY-cit| + +.. |GLY| image:: https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.3c00783-blue + :alt: Access the paper + :target: https://pubs.acs.org/doi/10.1021/acs.jctc.3c00783 + +.. |GLY-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.3c00783 + :alt: Citation diff --git a/docs/source/FAQ.rst b/docs/source/FAQ.rst index 1e691eb..371df11 100644 --- a/docs/source/FAQ.rst +++ b/docs/source/FAQ.rst @@ -139,7 +139,7 @@ General questions .. _g21: -- **sirah_ss assign some residues as coil, does it means they are unfold or randomly moving?** .. _g21: +- **sirah_ss assign some residues as coil, does it means they are unfold or randomly moving?** Not necessarily, the strict definition of coil used by *sirah_ss* is *“not helix nor extended sheet”*, which means a residue that can not satisfy either condition. Importantly, the secondary structure is assigned according to the Ramachandran and the hydrogen bond network. Particularly, the later is very sensitive to small fluctuation around the distance criteria used to define the interaction. Hence, transient coil states may be more likely to point the lost of hydrogen bonds in well folded proteins, rather that shifts in the conformational space. diff --git a/docs/source/Further reading.rst b/docs/source/Further reading.rst index 9c964dd..a877c24 100644 --- a/docs/source/Further reading.rst +++ b/docs/source/Further reading.rst @@ -26,6 +26,7 @@ SIRAH Applications .. |Review2-cit| image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fapi.juleskreuer.eu%2Fcitation-badge.php%3Fshield%26doi%3D10.1021%2Facs.jctc.3c00733 :alt: Citation + :target: https://scholar.google.com.uy/scholar?cites=14982031192725054357 * **Protein-DNA complexes** and **Membrane Proteins**: diff --git a/docs/source/GROMACS/Tutorial-3.rst b/docs/source/GROMACS/Tutorial-3.rst index 5c8fc7e..5370681 100644 --- a/docs/source/GROMACS/Tutorial-3.rst +++ b/docs/source/GROMACS/Tutorial-3.rst @@ -223,7 +223,7 @@ Generate restraint files for the backbone *GN* and *GO* beads: When prompted, choose the group *GN_GO* -Add restraints to ``topol.top`` +Add the restraints to ``topol.top``: .. list-table:: :align: center @@ -305,7 +305,7 @@ Make a new folder for the run: .. code-block:: bash - gmx grompp -f ../sirah.ff/tutorial/3/GPU/eq1_CGPROT.mdp -p ../topol.top -po eq1.mdp -n ./1CRN_cg_ion.ndx -c 1CRN_cg_em2.gro -r 1CRN_cg_em2.gro -o 1CRN_cg_eq1.tpr + gmx grompp -f ../sirah.ff/tutorial/3/GPU/eq1_CGPROT.mdp -p ../topol.top -po eq1.mdp -n ../1CRN_cg_ion.ndx -c 1CRN_cg_em2.gro -r 1CRN_cg_em2.gro -o 1CRN_cg_eq1.tpr .. code-block:: bash @@ -388,8 +388,10 @@ When prompted, choose *Protein* as both the group for calculation and the output gmx sasa -surface 'group "A"' -output '"Hydrophobic" group "A" and charge {-0.2 to 0.2}; "Hydrophilic" group "B" and not charge {-0.2 to 0.2}; "Total" group "B"' -Use Grace to plot the results:: - +Use Xmgrace to plot the results: + +.. code-block:: bash + xmgrace -nxy area.xvg .. diff --git a/docs/source/GROMACS/Tutorial-6.rst b/docs/source/GROMACS/Tutorial-6.rst index f43cb4c..a5f9ae1 100644 --- a/docs/source/GROMACS/Tutorial-6.rst +++ b/docs/source/GROMACS/Tutorial-6.rst @@ -48,7 +48,7 @@ The input file ``-i`` 2kyv.pqr contains the atomistic representation of `2KYV `. -6.5. Generate position restraint files +6.4. Generate position restraint files _______________________________________ To achive a proper interaction between the protein and bilayer, we will perform a equilibration step applying restraints over the protein backbone and lipids' phosphate groups. @@ -408,7 +408,7 @@ Edit ``topol_Lipid_chain_F.itp`` to include the new position restraints and defi | #include "posre_Pz.itp" | #endif -6.6. Run the simulation +6.5. Run the simulation ________________________ .. important:: @@ -416,7 +416,7 @@ ________________________ By default in this tutorial we will use input files for GROMACS on GPU (``sirah.ff/tutorial/6/GPU``). Example input files for using GROMACS on CPU can be found at: ``sirah.ff/tutorial/6/CPU``. The folder ``sirah.ff/tutorial/6/GPU/`` contains typical input files for energy minimization -(``em_CGLIPROT.mdp``), equilibration (``eq_CGLIPROT.mdp``) and production (``md_CGLIPROT.mdp``) runs. Please +(``em1_CGLIPROT.mdp`` and ``em2_CGLIPROT.mdp``), equilibration (``eq1_CGLIPROT.mdp`` and ``eq2_CGLIPROT.mdp``) and production (``md_CGLIPROT.mdp``) runs. Please check carefully the input flags therein. Make a new folder for the run: @@ -447,7 +447,7 @@ Make a new folder for the run: **Equilibration 1**: -Position restraints are defined in ``eq_CGLIPROT.mdp`` file for protein backbone in xyz and phosphate groups (BFO beads) in z coordinate by setting keywords ``-DPOSREBB`` and ``-DPOSREZ``, respectively. +Position restraints are defined in ``eq1_CGLIPROT.mdp`` file for protein backbone in xyz and phosphate groups (BFO beads) in z coordinate by setting keywords ``-DPOSREBB`` and ``-DPOSREZ``, respectively. .. code-block:: bash @@ -477,7 +477,7 @@ Position restraints are defined in ``eq_CGLIPROT.mdp`` file for protein backbone gmx mdrun -deffnm 2kyv_DMPC_cg_md &> MD.log & -6.7. Visualizing the simulation +6.6. Visualizing the simulation ________________________________ That’s it! Now you can analyze the trajectory. diff --git a/docs/source/GROMACS/Tutorial-7.rst b/docs/source/GROMACS/Tutorial-7.rst new file mode 100644 index 0000000..258073f --- /dev/null +++ b/docs/source/GROMACS/Tutorial-7.rst @@ -0,0 +1,684 @@ +.. note:: + + Please report bugs, errors or enhancement requests through `Issue Tracker `_ or if you have a question about SIRAH open a `New Discussion `_. + +This tutorial shows how to apply the multiscale solvation approach of SIRAH force field in Steered Molecular Dynamics (SMD) simulations. In this tutorial, an immunoglobulin domain known as `I10 `_ derived from Titin is enclosed by CG waters referred to as WatFour (WT4). These waters are further embedded within supra-coarse-grained (SCG) molecules called WatElse (WLS), which serve as a representation of bulk water. The main references for this tutorial are: `Darré et al. `_ and `Machado et al. `__. + +.. note:: + + We strongly advise you to read and complete :ref:`Tutorial 2 ` and :ref:`Tutorial 3 ` before starting. We also recommend you to perform the `Umbrella Sampling `__ tutorial of GROMACS to get familiar with pulling simulations parameters. + + +.. important:: + + Check the :ref:`Setting up SIRAH ` section for download and set up details before starting this tutorial. + Since this is **Tutorial 7**, remember to replace ``X.X``, the files corresponding to this tutorial can be found in: ``sirah.ff/tutorial/7/`` + + +7.1. Setting pulling direction +________________________________ + +.. caution:: + + The basic idea behind SMD is to apply an external force or mechanical perturbation to a specific part of the biomolecular system under study and observe its response. This external force is applied to one atom or groups of atoms as a "steering" force, guiding or pulling the atoms along a predefined path or direction. Thus, prior to proceeding, we need to remember to prepare the PDB file to specify the pulling direction. In this example, the **Z-axis** was employed to orient the protein terminus and to determine the box size. + +In ``sirah_[version].ff/tutorial/7/`` you will find the I10 domain (PDB code: `4QEG `__) already aligned along the Z-axis, ``I10_z.pdb`` file. + +.. figure:: /../images/TutorialSMD1.png + :align: center + :width: 100% + + **Figure 1.** I10 domain N-terminal (blue) and C-terminal (red) aligned to the Z-axis from ``I10_z.pdb``. + +To get the protein aligned along the Z-axis, we used the following commands in VMD's *Tk Console* (*Extensions* > *Tk Console*): + +.. code-block:: console + + #Select the protein + set all [atomselect top "protein"] + + #Change protein coordinates to align to its center + $all moveby [vecinvert [measure center $all]] + + #Rotate around x-axis 50 degrees + $all move [transaxis x 50] + + #Rotate around y-axis -11 degrees + $all move [transaxis y -11] + + #Write PDB file with the protein aligned to z-axis + $all writepdb I10_z.pdb + +.. note:: + + For setting up your own system you can open your own PDB in VMD and probe different alternatives to get the correct direction. + + + +7.2. Build CG representations +______________________________ + +.. caution:: + + The mapping to CG requires the correct protonation state of each residue at a given pH. We recommend using the `CHARMM-GUI server `_ and use the **PDB Reader & Manipulator** to prepare your system. An account is required to access any of the CHARMM-GUI Input Generator modules, and it can take up to 24 hours to obtain one. + + Other option is the `PDB2PQR server `_ and choosing the output naming scheme of AMBER for best compatibility. This server was utilized to generate the *PQR* file featured in this tutorial. Be aware that modified residues lacking parameters such as: MSE (seleno MET), TPO (phosphorylated THY), SEP (phosphorylated SER) or others are deleted from the PQR file by the server. In that case, mutate the residues to their unmodified form before submitting the structure to the server. + + See :ref:`Tutorial 3 ` for cautions while preparing and mapping atomistic proteins to SIRAH. + +Map the atomistic structure of the I10 domain to its CG representation: + +.. code-block:: bash + + ./sirah.ff/tools/CGCONV/cgconv.pl -i sirah.ff/tutorial/7/I10_z.pqr -o I10_cg.pdb + +The input file ``-i`` I10_z.pqr contains the atomistic representation of `4QEG `__ structure at pH **7.0** and aligned to the **Z-axis**, while the output ``-o`` I10_cg.pdb is its SIRAH CG representation. + +.. tip:: + + This is the basic usage of the script **cgconv.pl**, you can learn other capabilities from its help by typing: + + .. code-block:: bash + + ./sirah.ff/tools/CGCONV/cgconv.pl -h + + +Please check both PDB and PQR structures using VMD: + +.. code-block:: bash + + vmd -m sirah.ff/tutorial/7/I10_z.pqr I10_cg.pdb + +From now on it is just normal GROMACS stuff! + + +7.3. PDB to GROMACS format +__________________________ + +Use ``pdb2gmx`` to convert your PDB file into GROMACS format: + +.. code-block:: bash + + gmx pdb2gmx -f I10_cg.pdb -o I10_cg.gro + +When prompted, choose *SIRAH force field* and then *SIRAH solvent models*. +In this specific case, the charge of the system is -5.000 e; this will be addressed later. + +.. note:: + + By default charged terminal are used but it is possible to set them neutral with option ``-ter`` + +.. note:: + + Warning messages about long, triangular or square bonds are fine and expected due to the CG topology of some residues. + +.. caution:: + + However, missing atom messages are errors which probably trace back to the + mapping step. In that case, check your atomistic and mapped structures and do not carry on the + simulation until the problem is solved. + + +7.4. Solvate the system +_______________________ + +.. danger:: + + Since we are doing a SMD simulation, we need to carefully set the box dimensions to provide enough solvent to the "stretched" protein and keep a good separation between the surfaces of periodic images. + + In this system, I10 has 88 amino acids and the maximum extension size of each amino acid is 0.34 nm. Thus, "stretched" protein will be 88 * 0.34 = 29.92 nm (~ 30.0 nm) long. In order to accommodate the pulling, GROMACS stipulates a minimum box size double this value, i.e. 60 nm for the Z-axis. However, for optimal results, it is recommended that the dimensions of the box be 2.5 to 3 times greater than the maximum length of the protein when in its extended conformation. Therefore, for this tutorial the box used is 10 10 90 nm. + + .. figure:: /../images/TutorialSMD2.png + :align: center + :width: 100% + + **Figure 2.** Dimensions of the multiscale solvation box used in this tutorial. + +In order to have a multiscale solvent approach using WT4 and WLS, two steps are needed to solvate the systems. + +First, define the simulation region of the system to be enclosed by WT4 (pink in **Figure 2**) + +.. code-block:: bash + + gmx editconf -f I10_cg.gro -o I10_cg_box.gro -box 10 10 20 -bt triclinic -c + +.. note:: + + At this step, if you don't want to use a multiscale solvent method, the whole box dimension (10 10 90 nm) can be used to add only WT4 molecules. + +Add WT4 molecules: + +.. code-block:: bash + + gmx solvate -cp I10_cg_box.gro -cs sirah.ff/wt416.gro -o I10_cg_solv1.gro + +.. note:: + + Before GROMACS version 5.x, the command *gmx solvate* was called *genbox*. + +Edit the [ molecules ] section in ``topol.top`` to include the number of added WT4 molecules: + +.. list-table:: + :align: center + :widths: 50 50 + :header-rows: 1 + + * - Topology before editing + - Topology after editing + * - | [ molecules ] + | ; Compound #mols + | Protein_chain_A 1 + | + + + - | [ molecules ] + | ; Compound #mols + | Protein_chain_A 1 + | WT4 6281 + +.. hint:: + + If you forget to read the number of added WT4 molecules from the output of *solvate*, then use the following command line to get it + + .. code-block:: console + + grep -c WP1 I10_cg_solv1.gro + +.. caution:: + + The number of added WT4 molecules, **6281**, may change according to the software version. + +Remove misplaced WT4 molecules within 0.3 nm of protein: + +.. code-block:: bash + + echo q | gmx make_ndx -f I10_cg_sol1.gro -o I10_cg_sol1.ndx + +.. code-block:: bash + + gmx grompp -f sirah.ff/tutorial/7/GPU/em1_CGPROT.mdp -p topol.top -po delete1.mdp -c I10_cg_sol1.gro -o I10_cg_sol1.tpr -maxwarn 2 + +.. caution:: + + New GROMACS versions may complain about the non-neutral charge of the system, aborting the generation of the TPR file by command grompp. We will neutralize the system later, so to overcame this issue, just allow warning messages by adding the following keyword to the grompp command line: ``-maxwarn 2`` + +.. code-block:: bash + + gmx select -f I10_cg_sol1.gro -s I10_cg_sol1.tpr -n I10_cg_sol1.ndx -on rm_close_wt4.ndx -select 'not (same residue as (resname WT4 and within 0.3 of group Protein))' + +.. code-block:: bash + + gmx editconf -f I10_cg_sol1.gro -o I10_cg_sol2.gro -n rm_close_wt4.ndx + + +Edit the [ molecules ] section in ``topol.top`` to correct the number of WT4 molecules, **6261**. + +.. hint:: + + If you forget to read the number of added WT4 molecules from the output of *solvate*, then use the following command line to get it + + .. code-block:: console + + grep -c WP1 I10_cg_solv2.gro + + +Now, we include the second solvent layer of solvent with WLS molecules (green in **Figure 2**): + +.. code-block:: bash + + gmx editconf -f I10_cg_sol2.gro -o I10_cg_box2.gro -box 10 10 90 -bt triclinic -c + +.. hint:: + + We can check the final box dimensions with VMD: + + .. code-block:: bash + + vmd I10_cg_box2.gro + + In the *Tk Console* (*Extensions* > *Tk Console*) use the command: + + .. code-block:: bash + + pbc box + + +Add WLS molecules: + +.. code-block:: bash + + gmx solvate -cp I10_cg_box2.gro -cs sirah.ff/wlsbox.gro -o I10_cg_sol3.gro + +.. note:: + + Before GROMACS version 5.x, the command *gmx solvate* was called *genbox*. + + +Edit the [ molecules ] section in ``topol.top`` to include the number of added WLS molecules: + +.. list-table:: + :align: center + :widths: 50 50 + :header-rows: 1 + + * - Topology before editing + - Topology after editing + * - | [ molecules ] + | ; Compound #mols + | Protein_chain_A 1 + | WT4 6261 + | + + + - | [ molecules ] + | ; Compound #mols + | Protein_chain_A 1 + | WT4 6261 + | WLS 4697 + +.. hint:: + + If you forget to read the number of added WLS molecules from the output of *solvate*, then use the following command line to get it + + .. code-block:: console + + grep -c LN1 I10_cg_solv3.gro + +.. caution:: + + The number of added WLS molecules, **4697**, may change according to the software version. + +Remove misplaced WLS molecules within 7.8 nm of protein: + +.. code-block:: bash + + echo q | gmx make_ndx -f I10_cg_sol3.gro -o I10_cg_sol3.ndx + +.. code-block:: bash + + gmx grompp -f sirah.ff/tutorial/7/GPU/em1_CGPROT.mdp -p topol.top -po delete3.mdp -c I10_cg_sol3.gro -o I10_cg_sol3.tpr -maxwarn 2 + +.. caution:: + + New GROMACS versions may complain about the non-neutral charge of the system, aborting the generation of the TPR file by command grompp. We will neutralize the system later, so to overcame this issue, just allow warning messages by adding the following keyword to the grompp command line: ``-maxwarn 2`` + +.. code-block:: bash + + gmx select -f I10_cg_sol3.gro -s I10_cg_sol3.tpr -n I10_cg_sol3.ndx -on rm_close_wls.ndx -select 'not (same residue as (resname WLS and within 7.8 of group Protein))' + +.. code-block:: bash + + gmx editconf -f I10_cg_sol3.gro -o I10_cg_sol4.gro -n rm_close_wls.ndx + +Edit the [ molecules ] section in ``topol.top`` to correct the number of WLS molecules, **4582**. + +.. hint:: + + If you forget to read the number of added WLS molecules from the output of *solvate*, then use the following command line to get it + + .. code-block:: console + + grep -c LN1 I10_cg_solv4.gro + + +.. note:: + + Consult ``sirah.ff/0ISSUES`` and :doc:`FAQs <../FAQ>` for information on known solvation issues. + + +Add CG counterions and 0.15M NaCl: + +.. code-block:: bash + + gmx grompp -f sirah.ff/tutorial/7/GPU/em1_CGPROT.mdp -p topol.top -po delete4.mdp -c I10_cg_sol4.gro -o I10_cg_sol4.tpr -maxwarn 3 + +.. caution:: + + New GROMACS versions may complain about the non-neutral charge of the system, aborting the generation of the TPR file by command grompp. We are about to neutralize the system, so to overcame this issue, just allow warning messages by adding the following keyword to the grompp command line: ``-maxwarn 3`` + +.. code-block:: bash + + gmx genion -s I10_cg_sol4.tpr -o I10_cg_ion.gro -np 187 -pname NaW -nn 182 -nname ClW + +When prompted, choose to substitute *WT4* molecules by *ions*. + +.. note:: + + The available electrolyte species in SIRAH force field are: ``Na⁺`` (NaW), ``K⁺`` (KW) and ``Cl⁻`` (ClW) which represent solvated ions in solution. One ion pair (e.g., NaW-ClW) each 34 WT4 molecules results in a salt concentration of ~0.15M (see :ref:`Appendix ` for details). Counterions were added according to `Machado et al. `_. + +Edit the [ molecules ] section in ``topol.top`` to include the CG ions and the correct number of WT4, WLS, and ions. + +.. list-table:: + :align: center + :widths: 50 50 + :header-rows: 1 + + * - Topology before editing + - Topology after editing + * - | [ molecules ] + | ; Compound #mols + | Protein_chain_A 1 + | WT4 6261 + | WLS 4582 + | + | + + + - | [ molecules ] + | ; Compound #mols + | Protein_chain_A 1 + | WT4 5892 + | NaW 187 + | ClW 182 + | WLS 4582 + +.. caution:: + + Following the above order is important: the number of WT4 comes first, then the number of ions, and finally WLS. + +Before running the simulation it may be a good idea to visualize your molecular system. CG molecules are not recognized by molecular visualizers and will not display correctly. To fix this problem you may +generate a PSF file of the system using the script ``g_top2psf.pl``: + +.. code-block:: bash + + ./sirah.ff/tools/g_top2psf.pl -i topol.top -o I10_cg_ion.psf + +.. note:: + + This is the basic usage of the script ``g_top2psf.pl``, you can learn other capabilities from its help: + + .. code-block:: bash + + ./sirah.ff/tools/g_top2psf.pl -h + + +Use VMD to check how the CG system looks like: + +.. code-block:: + + vmd I10_cg_ion.psf I10_cg_ion.gro -e sirah.ff/tools/sirah_vmdtk.tcl + +.. tip:: + + VMD assigns default radius to unknown atom types, the script ``sirah_vmdtk.tcl`` sets the right ones, according to the CG representation. It also provides a kit of useful selection macros, coloring methods and backmapping utilities. + Use the command ``sirah_help`` in the Tcl/Tk console of VMD to access the manual pages. To learn about SIRAH Tools' capabilities, you can also go to the :ref:`SIRAH Tools tutorial `. + + +To achive a proper interaction between the protein and solvent, we will perform a equilibration step applying restraints over the protein backbone. + +Create an index file including a group for the backbone GN and GO beads: + +.. code-block:: bash + + echo -e "a GN GO\n\nq" | gmx make_ndx -f I10_cg_ion.gro -o I10_cg_ion.ndx + +.. note:: + + WT4 and CG ions (NaW, ClW) are automatically set to the group *SIRAH-Solvent*. + +Generate restraint files for the backbone *GN* and *GO* beads: + +.. code-block:: bash + + gmx genrestr -f I10_cg.gro -n I10_cg_ion.ndx -o bkbres.itp + +.. code-block:: bash + + gmx genrestr -f I10_cg.gro -n I10_cg_ion.ndx -o bkbres_soft.itp -fc 100 100 100 + +When prompted, choose the group *GN_GO* + +Add the restraints to ``topol.top``: + +.. list-table:: + :align: center + :widths: 50 50 + :header-rows: 1 + + * - Topology before editing + - Topology after editing + * - | ; Include Position restraint file + | #ifdef POSRES + | #include "posre.itp" + | #endif + + | ; Include water topology + | #include"../sirah.ff/solv.itp" + | + + | #ifdef POSRES_WATER + | ; Position restraint for each water oxygen + | [ position_restraints ] + | ; i funct fcx fcy fcz + | 1 1 1000 1000 1000 + | #endif + + | + | + + | + | + | + | + | + | + + | + | + | + | + + + - | ; Include Position restraint file + | #ifdef POSRES + | #include "posre.itp" + | #endif + + | ; Backbone restraints + | #ifdef GN_GO + | #include "bkbres.itp" + | #endif + + | ; Backbone soft restrains + | #ifdef GN_GO_SOFT + | #include "bkbres_soft.itp" + | #endif + + | ; Include water topology + | #include"../sirah.ff/solv.itp" + + | #ifdef POSRES_WATER + | ; Position restraint for each water oxygen + | [ position_restraints ] + | ; i funct fcx fcy fcz + | 1 1 1000 1000 1000 + | #endif + + | ; Solvent restrains + | #ifdef Sirah_solvent + | #include "posre_sirah_solvent.itp" + | #endif + | + + +7.5. Run the simulation +________________________ + +.. important:: + + By default in this tutorial we will use input files for GROMACS on GPU (``sirah.ff/tutorial/7/GPU``). + +The folder ``sirah.ff/tutorial/7/GPU/`` contains typical input files for energy minimization (``em1_CGPROT.mdp``, ``em2_CGPROT.mdp``, and ``em3_CGPROT.mdp``), equilibration (``eq1_CGPROT.mdp`` and ``eq2_CGPROT.mdp``), production (``md_CGPROT.mdp``) and SMD (``SMD_Force_CGPROT.mdp`` and ``SMD_Velocity_CGPROT.mdp``) runs. Please check carefully the input flags therein. + +Make a new folder for the run: + +.. code-block:: bash + + mkdir run; cd run + +**Energy Minimization of side chains by restraining the backbone and Sirah-solvent**: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/em1_CGPROT.mdp -p ../topol.top -po em1.mdp -n ../I10_cg_ion.ndx -c ../I10_cg_ion.gro -r ../I10_cg_ion.gro -o I10_cg_em1.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_em1 &> EM1.log & + +**Energy Minimization of side chains by restraining the backbone**: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/em2_CGPROT.mdp -p ../topol.top -po em2.mdp -n ../I10_cg_ion.ndx -c I10_cg_em1.gro -o I10_cg_em2.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_em2 &> EM2.log & + +**Energy Minimization of whole system**: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/em3_CGPROT.mdp -p ../topol.top -po em3.mdp -n ../I10_cg_ion.ndx -c I10_cg_em2.gro -o I10_cg_em3.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_em3 &> EM3.log & + +**Solvent equilibration**: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/eq1_CGPROT.mdp -p ../topol.top -po eq1.mdp -n ./I10_cg_ion.ndx -c I10_cg_em2.gro -r I10_cg_em2.gro -o I10_cg_eq1.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_eq1 &> EQ1.log & + +**Soft equilibration to improve side chain solvation**: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/eq2_CGPROT.mdp -p ../topol.top -po eq2.mdp -n ../I10_cg_ion.ndx -c I10_cg_eq1.gro -r I10_cg_eq1.gro -o I10_cg_eq2.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_eq2 &> EQ2.log & + + +**SMD Force or velocity**: + +Here, we need to modify the index file to add the "Pull" groups, before running SMD force or velocity simulations. + +Copy the ``I10_cg_ion.ndx`` with a new name: + +.. code-block:: bash + + cp ../I10_cg_ion.ndx ../I10_cg_ion_pull.ndx + +Open the ``I10_cg_ion_pull.ndx`` in any text editor and manually add to the end of the ``I10_cg_ion_pull.ndx`` file these two new groups: + ++-----------------+ +| Groups to add | ++=================+ +| | [ pull1 ] | +| | 4 | +| | [ pull2 ] | +| | 437 | ++-----------------+ + +In this tutorial we are going to run only the **SMD Force** simulation: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/SMD_Force_CGPROT.mdp -p ../topol.top -po md.mdp -n ../I10_cg_ion_pull.ndx -c I10_cg_eq2.gro -o I10_cg_SMD_F.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_SMD_F &> SMD_F.log & + +However, you can also run a **SMD Velocity** simulation: + +.. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/SMD_Velocity_CGPROT.mdp -p ../topol.top -po md.mdp -n ../I10_cg_ion_pull.ndx -c I10_cg_eq2.gro -o I10_cg_SMD_V.tpr + +.. code-block:: bash + + gmx mdrun -deffnm I10_cg_SMD_V &> SMD_V.log & + +.. note:: + + It is also possible to use the files you made to run a MD simulation of your system: + + **Production (1000ns)**: + + .. code-block:: bash + + gmx grompp -f ../sirah.ff/tutorial/7/GPU/md_CGPROT.mdp -p ../topol.top -po md.mdp -n ../I10_cg_ion.ndx -c I10_cg_eq2.gro -o I10_cg_md.tpr + + .. code-block:: bash + + gmx mdrun -deffnm I10_cg_md &> MD.log & + + +7.6. Visualizing the simulation +________________________________ + +That’s it! Now you can analyze the trajectory. + +GROMACS automatically creates plot results to the SMD simulations. The position versus simulation time is saved as ``I10_cg_md_pullx.xvg``, and the force versus simulation time is saved as ``I10_cg_md_pullf.xvg``. + +You can plot the results using Xmgrace. + +.. code-block:: bash + + xmgrace I10_cg_md_pullx.xvg + +For ``I10_cg_md_pullx.xvg``, a plot similar to **Figure 3** will appear: + +.. figure:: /../images/Fuerza_100pN.png + :align: center + :width: 100% + + **Figure 3.** Position vs Time plot created by GROMACS from the SMD simulation. + + +In addition, you can process the output trajectory at folder ``run/`` to account for the Periodic Boundary Conditions (PBC). + +For **SMD Force**: + +.. code-block:: bash + + gmx trjconv -s I10_cg_em1.tpr -f I10_cg_SMD_F.xtc -o I10_cg_SMD_F_pbc.xtc -n ../I10_cg_ion_pull.ndx -ur compact -center -pbc mol + +For **SMD Velocity**: + +.. code-block:: bash + + gmx trjconv -s I10_cg_em1.tpr -f I10_cg_SMD_V.xtc -o I10_cg_SMD_V_pbc.xtc -n ../I10_cg_ion_pull.ndx -ur compact -center -pbc mol + +When prompted, choose *Protein* for centering and *System* for output. + +.. note:: + + If you had also run a MD simulation, you could use the following commands to account for PBC: + + .. code-block:: bash + + gmx trjconv -s I10_cg_em1.tpr -f I10_cg_md.xtc -o I10_cg_md_pbc.xtc -n ../I10_cg_ion.ndx -ur compact -center -pbc mol + + +Now you can check the simulation using VMD: + +.. code-block:: bash + + vmd ../I10_cg_ion.psf ../I10_cg_ion.gro I10_cg_SMD_F_pbc.xtc -e ../sirah.ff/tools/sirah_vmdtk.tcl + +.. note:: + + The file ``sirah_vmdtk.tcl`` is a Tcl script that is part of SIRAH Tools and contains the macros to properly visualize the coarse-grained structures in VMD. Use the command ``sirah-help`` in the Tcl/Tk console of VMD to access the manual pages. To learn about SIRAH Tools' capabilities, you can also go to the :ref:`SIRAH Tools tutorial `. + + + diff --git a/docs/source/Tutorials gromacs.rst b/docs/source/Tutorials gromacs.rst index 96f67ca..91a13d2 100644 --- a/docs/source/Tutorials gromacs.rst +++ b/docs/source/Tutorials gromacs.rst @@ -50,4 +50,11 @@ Setting up SIRAH 6. Membrane proteins in explicit solvent -------------------------------------------------------------------- -.. include:: /GROMACS/Tutorial-6.rst \ No newline at end of file +.. include:: /GROMACS/Tutorial-6.rst + +.. _Tutorial 7 G: + +7. SMD with multiscale solvent +-------------------------------------------------------------------- + +.. include:: /GROMACS/Tutorial-7.rst \ No newline at end of file diff --git a/docs/source/index.rst b/docs/source/index.rst index 40efc97..959fcfe 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -69,6 +69,7 @@ Follow us in our social media profiles: |google-sirah| |youtube-sirah| |twitter- :caption: Manual About SIRAH + Background SIRAH Citation Further reading FAQ