AbFlex

AbFlex is a CDR design method with a given antibody-antigen complex.

Preparation

The below Python libraries are needed to run AbFlex. The dependencies below are verified.

1. PyTorch: 1.9.1+cu102
2. egnn-pytorch: the latest version from https://github.com/lucidrains/egnn-pytorch
3. pandas: 1.3.5
4. numpy: 1.18.5
5. scikit-learn: 1.0
6. scipy: 1.7.1
7. PDBFixer: the latest version from https://github.com/openmm/pdbfixer
8. OpenMM: 7.6 or the latest version from https://github.com/openmm/openmm
9. PyMOL: 2.4.0 Open-Source or https://github.com/schrodinger/pymol-open-source
10. BioPython: 1.77

For binding energy calculation, you'll need to install Rosetta or FoldX. Otherwise, AbFlex will generate designed PDB files only.

11. FoldX (https://foldxsuite.crg.eu/)
12. Rosetta (https://new.rosettacommons.org/demos/latest/tutorials/install_build/install_build)

Demo

1. Edit the configuration file "config.json" for your purpose. The configuration file describes information about which cdr to design. All the directories should be entered as an absolute path.

config.json
{
    "pdb_id": "7bz5",            # str. PDB ID of antibody-antigen complex
    "ab_chain_list": ["H", "L"], # list. Antibody chains in the input complex.
                                   It should contain all the antibody chains in the input PDB file.
    "ag_chain_list": ["A"],      # list. Antigen chains in the input complex.
                                   It should contain all the antigen chains in the input PDB file.
    "Design_chain": "H",         # str. One antibody chain to be designed
    "cdr_type": "H3",            # str. CDR type to be designed
    "cdr_seq": "EAYGMDV",        # str. The original sequence of the CDR is to be designed in the input PDB file.
    "out_dir": "/_absolute-path-to_/AbFlex/_your-working-dir_/",
                                 # str. The working directory. Output files will be generated here. **The directory should be an absolute path.**
    "FoldX_dir": "",             # str. If you wish to utilize FoldX, please input the location of
                                   the executable FoldX file. If not, you may leave it blank.
    "IA_dir": "",                # str. If you wish to utilize Rosetta InterfaceAnalyzer, please input
                                   the location of the executable InterfaceAnalyzer file.
                                   e.g., "/where-the-rosetta-install/bin/InterfaceAnalyzer.linuxgccrelease"
                                   If not, you may leave it blank.
    "n_sample": 1,               # int. The number of CDR structure samples to be generated from the predicted results.
                                   The samples will have different CDR sequences from each other.
    "n_relax": 1,                # int. The number of relaxations by openMM. If you use FoldX or Rosetta InterfaceAnalyer,
                                   then use 1~10. Otherwise, please set it to 1.
}

2. Locate the "config.json" file in the same location as the "run.py" file.
3. run "run.py" file

Output file description

Whether or not to use FoldX and Rosetta InterfaceAnalyzer, the file below will be generated as default.

1. {pdb_id}_{chain_id}_{CDR_type}_{sample#}_openmm.pdb: The relaxed full-atom model built with the predicted CDR C alpha coordinates and samples sequences.
2. {pdb_id}_{chain_id}_{CDR_type}_sequence_samples.fasta: The file of generated antibody chain sequences that were sampled from the predicted probability distribution.

If you use Rosetta InterfaceAnalzer or FoldX to evaluate the binding energy and n_relax>1, the below files will be generated additionally. 3. {pdb_id}_{chain_id}_{CDR_type}_{sample#}_best_{Foldx or IA}.pdb: The best binding energy structure through the relaxation 4. {pdb_id}_*_energy_scores.xlsx: Calculated binding energies of the generated samples.