Last active
February 20, 2019 01:05
-
-
Save PatWalters/432c369ff33767b800faa99efcbe2fef to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/usr/bin/env python | |
import sys | |
from rdkit import Chem | |
from tqdm import tqdm | |
import pandas as pd | |
import math | |
def in_place_rmsd(mol_1, mol_2): | |
tmp_mol = Chem.RemoveHs(mol_2) | |
conf_1 = mol_1.GetConformer() | |
conf_2 = mol_2.GetConformer() | |
heavy_atom_idx = [x.GetIdx() for x in mol_1.GetAtoms() if x.GetAtomicNum() > 1] | |
ref_coords = [conf_1.GetAtomPosition(x) for x in heavy_atom_idx] | |
matches = mol_1.GetSubstructMatches(tmp_mol, uniquify=False) | |
rms_list = [] | |
for m in matches: | |
fit_coords = [conf_2.GetAtomPosition(x) for x in m] | |
delta_list = [(x - y).LengthSq() for x, y in zip(ref_coords, fit_coords)] | |
max_dev = math.sqrt(max(delta_list)) | |
rms_list.append([math.sqrt(sum(delta_list) / len(delta_list)),max_dev]) | |
rms_list.sort() | |
return rms_list[0] | |
def pairwise_rmsd(mol_list, rms_cutoff, dev_cutoff, in_place): | |
is_dupe = [False] * len(mol_list) | |
for i in range(0, len(mol_list)): | |
for j in range(0, i): | |
in_place_rmsd(mol_list[i], mol_list[j]) | |
rms, max_dev = in_place_rmsd(mol_list[i], mol_list[j]) | |
if rms < rms_cutoff and max_dev < dev_cutoff: | |
is_dupe[i] = True | |
break | |
return is_dupe | |
def remove_dupe_confs(infile, outfile, rms_cutoff, dev_cutoff, in_place): | |
suppl = Chem.SDMolSupplier(infile, removeHs=False) | |
writer = Chem.SDWriter(outfile) | |
data = [] | |
for mol in tqdm(suppl, desc="Reading"): | |
name = mol.GetProp("_Name") | |
data.append([name, mol]) | |
df = pd.DataFrame(data, columns=["Name", "Mol"]) | |
initial_rows, _ = df.shape | |
dupe_list = [] | |
for k, v in tqdm(df.groupby("Name"), desc="Removing Dupes"): | |
dupe_list += pairwise_rmsd(v["Mol"].values, rms_cutoff, dev_cutoff, in_place) | |
df["dupe"] = dupe_list | |
df = df.query("dupe == False") | |
final_rows, _ = df.shape | |
for mol in df.Mol.values: | |
writer.write(mol) | |
print("read %d conformers, wrote %d conformers" % (initial_rows, final_rows)) | |
if __name__ == "__main__": | |
if len(sys.argv) != 5: | |
print("usage: %s infile.sdf outfile.sdf rms_cutoff max_deviation" % (sys.argv[0])) | |
else: | |
remove_dupe_confs(sys.argv[1], sys.argv[2], float(sys.argv[3]), float(sys.argv[4]), in_place=True) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment