binding_affinity / biolip.py
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from mpi4py import MPI
from mpi4py.futures import MPICommExecutor
from openbabel import pybel
from Bio.PDB import *
parser = PDBParser()
import os
molecular_weight_cutoff = 2500
def parse_ligand(fn):
print(fn)
try:
struct = parser.get_structure('lig',fn)
if len(list(struct.get_atoms())) > molecular_weight_cutoff:
raise ValueError
mol = next(pybel.readfile('pdb',fn))
if mol.molwt > molecular_weight_cutoff:
raise ValueError
smi = mol.write('can').split('\t')[0]
return smi
except:
return None
if __name__ == '__main__':
import glob
comm = MPI.COMM_WORLD
with MPICommExecutor(comm, root=0) as executor:
if executor is not None:
import pandas as pd
df = pd.read_table('biolip/data/BioLiP_2013-03-6_nr.txt',sep='\t',header=None,usecols=[0,4,5,6,13,14,15,16,19])
df = df.rename(columns={0:'pdb',4:'chain',5:'l_id',6:'l_chain',
13: 'affinity_lit',14: 'affinity_moad',15: 'affinity_pdbbind-cn',16:'affinity_bindingdb',
19: 'seq'})
base = 'biolip/data/ligand_nr/'
df['ligand_fn'] = base + df['pdb']+'_'+df['chain']+'_'+df['l_id'].astype(str)+'_'+df['l_chain'].astype(str)+'.pdb'
smiles = list(executor.map(parse_ligand, df['ligand_fn']))
df['smiles'] = smiles
df.to_parquet('data/biolip_complex.parquet')