AlphaFold3 generate_chain_data_cache 腳本在源代碼的scripts文件夾下。該腳本從指定目錄中批量解析 mmCIF/PDB 文件的工具，并將每個鏈的基本信息（序列、分辨率、是否屬于聚類等）提取并寫入 JSON 文件，主要用于后續蛋白質建模、過濾或訓練數據準備。
源代碼：
import argparse
from functools import partial
import json
import logging
from multiprocessing import Pool
import os
import string
from collections import defaultdict
from tqdm import tqdm
from src.data.mmcif_parsing import parse
from src.common import protein, residue_constants
import sys
sys.path.append("../../../Downloads") # an innocent hack to get this to run from the top leveldef parse_file(f, args,chain_cluster_size_dict
):file_id, ext = os.path.splitext(f)if ext == ".cif":with open(os.path.join(args.data_dir, f), "r") as fp:mmcif_string = fp.read()mmcif = parse(file_id=file_id, mmcif_string=mmcif_string)if mmcif.mmcif_object is None:logging.info(f"Could not parse {f}. Skipping...")return {}else:mmcif = mmcif.mmcif_objectout = {}for chain_id, seq in mmcif.chain_to_seqres.items():full_name = "_".join([file_id, chain_id])out[full_name] = {}local_data = out[full_name]local_data["release_date"] = mmcif.header["release_date"]local_data["seq"] = seqlocal_data["resolution"] = mmcif.header["resolution"]if chain_cluster_size_dict is not None:cluster_size = chain_cluster_size_dict.get(full_name.upper(), -1)local_data["cluster_size"] = cluster_sizeelif ext == ".pdb":with open(os.path.join(args.data_dir, f), "r") as fp:pdb_string = fp.read()protein_object = protein.from_pdb_string(pdb_string, None)aatype = pr
)
