I have been using PyMOL, a molecular visualisation program, throughout my PhD and wanted to share some of the things I’ve learned.
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1. Installation<\/strong> 2. Documentation<\/strong> 3. Some of my favourite PyMOL commands\/selections<\/strong><\/p>\n\n\n\n 4. Playing around with visualisations<\/strong><\/p>\n\n\n\n 5. Pymol scripts<\/strong> 6. Python + PyMOL scripts<\/strong>
Open source PyMOL can be installed using conda: conda install -c conda-forge pymol-open-source<\/code>. It does not watermark figures and has full functionality, as far as I have been able to tell.<\/p>\n\n\n\n\n\n\n\n
You can find documentation for PyMOL online (https:\/\/pymol.org\/dokuwiki\/<\/a>), which can be very helpful, although is not entirely complete.
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ray 2000, 2000<\/code>.<\/li>\n\n\n\n
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You can create .pml scripts with PyMOL commands and run these in PyMOL. For example, pml_script.pml:<\/p>\n\n\n\nload 3w2d.pdb\nselect Ab, chain H + chain L\nselect Ag, chain A\n\nhide\nshow cartoon, Ab + Ag\ncolor blue, Ab\ncolor red, Ag<\/code><\/pre>\n\n\n\n
In the command line, you can run: pymol pml_script.pml<\/code>.
To run this script without opening the PyMOL GUI: pymol -c pml_script.pml<\/code><\/code><\/p>\n\n\n\n
PyMOL is compatible with Python! This is incredibly helpful when using PyMOL iteratively, such as for distance or rmsd calculations. There are a few ways Python + PyMOL scripts can be written\/executed, but I typically use the following:
py_script.py:<\/p>\n\n\n\nimport pandas as pd\n\nabs = pd.read_csv(\"antibody_pdbs.csv\")\n\nfor ind, row in abs.iterrows():\n\u00a0 \u00a0 cmd.load(row[\"pdb_path\"])\n\u00a0 \u00a0 cmd.create(\"ab\", f\"chain {row['Hchain']} + chain {row['Lchain']}\")\n\u00a0 \u00a0 print(\"cdrh3_anchor_dist:\", cmd.distance(\"ab & resi 105 & name CA\", \"ab & resi 117 & name CA\"))\n\u00a0 \u00a0 cmd.reinitialize()<\/code><\/pre>\n\n\n\n