| import os |
| import pandas as pd |
| from Bio.PDB import PDBParser |
| from Bio.SeqUtils import seq1 |
| from Bio.PDB.Polypeptide import is_aa |
| from rdkit import Chem |
| from tqdm import tqdm |
|
|
| PDBBIND_PATH = "refined-set" |
| INDEX_NAME = "INDEX_refined_data.2020" |
|
|
|
|
| def get_ligand_smiles(pdb_id, pdb_dir_path): |
| """ |
| Get the SMILES representation of the ligand. |
| """ |
|
|
| sdf_path = os.path.join(pdb_dir_path, f"{pdb_id}_ligand.sdf") |
| mol2_path = os.path.join(pdb_dir_path, f"{pdb_id}_ligand.mol2") |
| if os.path.exists(sdf_path): |
| try: |
| sfd_file = Chem.SDMolSupplier(sdf_path) |
| if sfd_file: |
| mol = sfd_file[0] |
| except Exception: |
| mol = None |
|
|
| if mol is None and os.path.exists(mol2_path): |
| try: |
| mol = Chem.MolFromMol2File(mol2_path) |
| except Exception: |
| mol = None |
| if mol is not None: |
| smiles = Chem.MolToSmiles(mol) |
| return smiles |
| else: |
| return None |
|
|
|
|
| def get_protein_sequence(pdb_id, pdb_dir_path): |
| """ |
| Get the protein sequence of the protein. |
| """ |
| protein_path = os.path.join(pdb_dir_path, f"{pdb_id}_protein.pdb") |
| pdbparser = PDBParser() |
| structure = pdbparser.get_structure(pdb_id, protein_path) |
| sequences = [] |
|
|
| for model in structure: |
| for chain in model: |
| sequence = "" |
| for residue in chain: |
| if residue.get_id()[0] == " " and is_aa( |
| residue.get_resname(), standard=True |
| ): |
| sequence += seq1(residue.get_resname()) |
|
|
| sequences.append(sequence) |
| longest_sequence = max(sequences, key=len) |
| return longest_sequence |
|
|
|
|
| def main(): |
| final_data = [] |
|
|
| index_data = {} |
|
|
| index_file_path = os.path.join(PDBBIND_PATH, "index", INDEX_NAME) |
| with open(index_file_path, "r") as f: |
| for line in f: |
| if line.startswith("#"): |
| continue |
| parts = line.split() |
| pdb_id = parts[0] |
| print(pdb_id) |
| affinity = parts[3] |
|
|
| index_data[pdb_id] = affinity |
| print(f"Loaded index data for {len(index_data)} entries") |
|
|
| for pdb_id, affinity in tqdm(index_data.items()): |
| pdb_id_path = os.path.join(PDBBIND_PATH, pdb_id) |
|
|
| smiles = get_ligand_smiles(pdb_id, pdb_id_path) |
| sequence = get_protein_sequence(pdb_id, pdb_id_path) |
| if smiles is not None or sequence is not None: |
| final_data.append( |
| { |
| "pdb_id": pdb_id, |
| "smiles": smiles, |
| "sequence": sequence, |
| "affinity": affinity, |
| } |
| ) |
|
|
| df = pd.DataFrame(final_data) |
| df.to_csv("pdbbind_refined_dataset.csv", index=False) |
|
|
|
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| |
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| |
|
|
| if __name__ == "__main__": |
| main() |
|
|
