| import requests |
| from joblib import Parallel, delayed |
| import os |
| import argparse |
| import sys |
| import json |
| import pandas as pd |
| from tqdm import tqdm |
|
|
| def parse_args(): |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--data_file", help="data file", type=str, required=True) |
| parser.add_argument("--alphafold_dir", help="directory where alphafold models are stroed", type=str, required=True) |
| parser.add_argument("--esm_dir", help="directory where to store esm models", type=str, required=True) |
| parser.add_argument("--out_file", help="out file", type=str, required=True) |
| |
| args, unparsed = parser.parse_known_args() |
| parser = argparse.ArgumentParser() |
|
|
| return args |
|
|
| args = parse_args() |
|
|
| def _is_empty_model(modelpath): |
| try: |
| structure = esm.inverse_folding.util.load_structure(modelpath, 'A') |
| return False |
| except: |
| return True |
|
|
| import ipdb |
| ipdb.set_trace() |
| alphafold_models = os.listdir(args.alphafold_dir) |
| esm_models = os.listdir(args.esm_dir) |
|
|
| af_model_path = lambda uni: args.alphafold_dir + f'/AF-{uni}-F1-model_v4.pdb' |
| esm_model_path = lambda uni: args.esm_dir + f'/ESMFold-{uni}-v1.pdb' |
|
|
| df = pd.read_csv(args.data_file) |
|
|
| modelpaths = [] |
| for uni in tqdm(df.uniprot): |
| modelpath = af_model_path(uni) |
| modelpath2 = esm_model_path(uni) |
| if not _is_empty_model(modelpath): modelpaths.append(modelpath) |
| elif not _is_empty_model(modelpath2): modelpaths.append(modelpath2) |
| else: modelpaths.append(None) |
| df['pdbpath'] = modelpaths |
|
|
| df.info() |
| df.dropna(subset=['pdbpath'],inplace=True) |
| df.reset_index(inplace=True,drop=True) |
| df.to_csv(args.out_file) |
