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from mpi4py import MPI
from mpi4py.futures import MPICommExecutor
import warnings
from Bio.PDB import PDBParser, PPBuilder, CaPPBuilder
from Bio.PDB.NeighborSearch import NeighborSearch
from Bio.PDB.Selection import unfold_entities
import numpy as np
import dask.array as da
from rdkit import Chem
import os
import re
import sys
# all punctuation
punctuation_regex = r"""(\(|\)|\.|=|#|-|\+|\\|\/|:|~|@|\?|>>?|\*|\$|\%[0-9]{2}|[0-9])"""
# tokenization regex (Schwaller)
molecule_regex = r"""(\[[^\]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|\(|\)|\.|=|#|-|\+|\\|\/|:|~|@|\?|>>?|\*|\$|\%[0-9]{2}|[0-9])"""
cutoff = int(sys.argv[1])
max_seq = 2046 # = 2048 - 2 (accounting for [CLS] and [SEP])
max_smiles = 510 # = 512 - 2
chunk_size = '1G'
def parse_complex(fn):
try:
name = os.path.basename(fn)
# parse protein sequence and coordinates
parser = PDBParser()
with warnings.catch_warnings():
warnings.simplefilter("ignore")
structure = parser.get_structure('protein',fn+'/'+name+'_protein.pdb')
# ppb = PPBuilder()
ppb = CaPPBuilder()
seq = []
for pp in ppb.build_peptides(structure):
seq.append(str(pp.get_sequence()))
seq = ''.join(seq)
# parse ligand, convert to SMILES and map atoms
suppl = Chem.SDMolSupplier(fn+'/'+name+'_ligand.sdf')
mol = next(suppl)
smi = Chem.MolToSmiles(mol)
# position of atoms in SMILES (not counting punctuation)
atom_order = [int(s) for s in list(filter(None,re.sub(r'[\[\]]','',mol.GetProp("_smilesAtomOutputOrder")).split(',')))]
# tokenize the SMILES
tokens = list(filter(None, re.split(molecule_regex, smi)))
# remove punctuation
masked_tokens = [re.sub(punctuation_regex,'',s) for s in tokens]
k = 0
token_pos = []
token_id = []
for i,token in enumerate(masked_tokens):
if token != '':
token_pos.append(tuple(mol.GetConformer().GetAtomPosition(atom_order[k])))
token_id.append(i)
k += 1
# query protein for ligand contacts
atoms = unfold_entities(structure, 'A')
neighbor_search = NeighborSearch(atoms)
close_residues = [neighbor_search.search(center=t, level='R', radius=cutoff) for t in token_pos]
first_residue = next(structure.get_residues()).get_id()[1]
residue_id = [[c.get_id()[1]-first_residue for c in query if not c.get_id()[0].startswith(('H','W'))]
for query in close_residues] # zero-based, exclude hetero atoms
# contact map
contact_map = np.zeros((max_seq, max_smiles),dtype=np.float32)
for query,t in zip(residue_id,token_id):
for r in query:
contact_map[r,t] = 1
return name, seq, smi, contact_map
except Exception as e:
print(e)
return None
if __name__ == '__main__':
import glob
filenames = glob.glob('data/pdbbind/v2020-other-PL/*')
filenames.extend(glob.glob('data/pdbbind/refined-set/*'))
filenames = sorted(filenames)
comm = MPI.COMM_WORLD
with MPICommExecutor(comm, root=0) as executor:
if executor is not None:
result = executor.map(parse_complex, filenames)
result = list(result)
names = [r[0] for r in result if r is not None]
seqs = [r[1] for r in result if r is not None]
all_smiles = [r[2] for r in result if r is not None]
all_contacts = [r[3] for r in result if r is not None]
import pandas as pd
df = pd.DataFrame({'name': names, 'seq': seqs, 'smiles': all_smiles})
all_contacts = da.from_array(all_contacts, chunks=chunk_size)
da.to_npy_stack('data/pdbbind_contacts_{}/'.format(cutoff), all_contacts)
df.to_parquet('data/pdbbind_complex_{}.parquet'.format(cutoff))
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