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Pseudocycle_small_molecule_binder

Key references:

  1. Pyrosetta: https://www.pyrosetta.org/
  2. pseudocycle: https://github.com/LAnAlchemist/Psedocycles_NSMB.git
  3. silent tools: git@github.com:bcov77/silent_tools.git
  4. AF2: https://github.com/google-deepmind/alphafold.git
  5. ProteinMPNN: https://github.com/dauparas/ProteinMPNN.git
  6. ligandMPNN: https://github.com/dauparas/LigandMPNN

Pre-installation requirements

  1. Rifgen/RifDock: Klima, J.C., Doyle, L.A., Lee, J.D. et al. Incorporation of sensing modalities into de novo designed fluorescence-activating proteins. Nat Commun 12, 856 (2021). https://doi.org/10.1038/s41467-020-18911-w
  2. LigandMPNN: see above (or you can also use the customized version in this repo, they are the same, just minor script change to fit in automatic design instead of only return sequences)
  3. ProteinMPNN: https://github.com/dauparas/ProteinMPNN.git
  4. AF2: see above

note

LA made minor change for all above scripts, to make the pipeline easy to use for people who are interested in the pseudocycle method, LA uploaded all the dependent packages for ease of use. However, the users can pull from the original repo and use all abovementioned scripts as it is with simple dependency/arguments modification. These 2 methods will not yield any differences for results.

How to use this script?

environment

steps:

  1. generate rotamers to use, follow 1_ligand_conformer_generation_with_rdkit.ipynb
  2. dock to pseudocycles and design using pssm-based rosetta design, follow 2a_first_step_shape_complimentary_screening.ipynb
  3. design using iterative ligandMPNN 2b_first_step_ligMPNN.ipynb.
  4. do your wet, find binder
  5. resample based on your hits, generate new sequences based on hit scaffolds, fold them, keep those folded within 3 A, plddt > 90, ptm > 0.65
  6. redo docking and design, you can use scripts in step 2-3.