add RF2 scoring for testing
Browse files- .gitattributes +1 -0
- data/dcoid_rf2.parquet +3 -0
- dcoid_combine.py +4 -3
- dcoid_rf2.py +77 -0
- dcoid_rf2.slurm +10 -0
.gitattributes
CHANGED
@@ -816,3 +816,4 @@ data/dude/part.713.parquet filter=lfs diff=lfs merge=lfs -text
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data/dude/part.82.parquet filter=lfs diff=lfs merge=lfs -text
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data/dude_predict.parquet filter=lfs diff=lfs merge=lfs -text
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data/dcoid.parquet filter=lfs diff=lfs merge=lfs -text
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data/dude/part.82.parquet filter=lfs diff=lfs merge=lfs -text
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data/dude_predict.parquet filter=lfs diff=lfs merge=lfs -text
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data/dcoid.parquet filter=lfs diff=lfs merge=lfs -text
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data/dcoid_rf2.parquet filter=lfs diff=lfs merge=lfs -text
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data/dcoid_rf2.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f22bcc4300a2c97a7346b9dfa8e072de088a3c6e5ac4d955c1ab2a89cc6d2ab
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size 148055
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dcoid_combine.py
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import pandas as pd
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if __name__ == '__main__':
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import glob
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df_actives = pd.read_parquet(
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df_decoys = pd.read_parquet(
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df_actives['active'] = pd.Series([True]*len(df_actives))
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df_decoys['active'] = pd.Series([False]*len(df_decoys))
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pd.concat([df_actives,df_decoys]).to_parquet(
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import pandas as pd
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import sys
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if __name__ == '__main__':
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import glob
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df_actives = pd.read_parquet(sys.argv[1])
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df_decoys = pd.read_parquet(sys.argv[2])
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df_actives['active'] = pd.Series([True]*len(df_actives))
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df_decoys['active'] = pd.Series([False]*len(df_decoys))
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pd.concat([df_actives,df_decoys]).to_parquet(sys.argv[3])
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dcoid_rf2.py
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from mpi4py import MPI
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from mpi4py.futures import MPICommExecutor
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from oddt.scoring.functions import RFScore
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import oddt
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from Bio.PDB import PDBParser, PDBIO, Select
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import tempfile
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import os
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import sys
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import pandas as pd
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scorer = RFScore.rfscore.load(version=2)
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def is_het(residue):
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res = residue.id[0]
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return res != " " and res != "W"
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class ResidueSelect(Select):
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def __init__(self, het):
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self.het = het
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def accept_residue(self, residue):
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""" Recognition of heteroatoms - Remove water molecules """
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return (self.het and is_het(residue) or not self.het and not is_het(residue))
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def get_complex(fn):
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try:
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io = PDBIO()
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parser = PDBParser()
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structure = parser.get_structure('complex',fn)
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io.set_structure(structure)
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with tempfile.NamedTemporaryFile(mode='w',delete=False) as f:
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name_receptor = f.name
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with tempfile.NamedTemporaryFile(mode='w',delete=False) as f:
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name_ligand = f.name
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io.save(name_receptor,ResidueSelect(het=False))
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io.save(name_ligand,ResidueSelect(het=True))
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receptor = next(oddt.toolkit.readfile('pdb',name_receptor))
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ligand = next(oddt.toolkit.readfile('pdb',name_ligand))
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scorer.set_protein(receptor)
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scorer.predict_ligand(ligand)
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os.unlink(name_ligand)
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os.unlink(name_receptor)
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return float(ligand.data['rfscore_v2'])
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except Exception as e:
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print(e)
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pass
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if __name__ == '__main__':
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import glob
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filenames = glob.glob(sys.argv[2])
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comm = MPI.COMM_WORLD
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with MPICommExecutor(comm, root=0) as executor:
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if executor is not None:
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result = executor.map(get_complex, filenames)
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names = []
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scores = []
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for n,r in zip(filenames,result):
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try:
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scores.append(r)
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names.append(os.path.basename(n))
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except:
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pass
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df = pd.DataFrame({'name': names, 'rf2': scores})
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df.to_parquet(sys.argv[1])
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dcoid_rf2.slurm
ADDED
@@ -0,0 +1,10 @@
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#!/bin/bash
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#SBATCH -J dcoid_rf2
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#SBATCH -p batch
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#SBATCH -A STF006
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#SBATCH -t 1:00:00
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#SBATCH -N 8
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#SBATCH --ntasks-per-node=32
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srun python dcoid_rf2.py data/dcoid_rf2_actives.parquet "/gpfs/alpine/world-shared/bip214/binding_affinity/dcoid/actives/*pdb"
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srun python dcoid_rf2.py data/dcoid_rf2_decoys.parquet "/gpfs/alpine/world-shared/bip214/binding_affinity/dcoid/decoys/*pdb"
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