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import os
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import time
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import json
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import numpy as np
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import re
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import sys
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sys.path.append(".")
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def get_struc_seq(foldseek,
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path,
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chains: list = None,
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process_id: int = 0,
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plddt_mask: bool = False,
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plddt_threshold: float = 70.,
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foldseek_verbose: bool = False) -> dict:
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"""
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Args:
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foldseek: Binary executable file of foldseek
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path: Path to pdb file
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chains: Chains to be extracted from pdb file. If None, all chains will be extracted.
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process_id: Process ID for temporary files. This is used for parallel processing.
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plddt_mask: If True, mask regions with plddt < plddt_threshold. plddt scores are from the pdb file.
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plddt_threshold: Threshold for plddt. If plddt is lower than this value, the structure will be masked.
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foldseek_verbose: If True, foldseek will print verbose messages.
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Returns:
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seq_dict: A dict of structural seqs. The keys are chain IDs. The values are tuples of
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(seq, struc_seq, combined_seq).
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"""
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assert os.path.exists(foldseek), f"Foldseek not found: {foldseek}"
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assert os.path.exists(path), f"PDB file not found: {path}"
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tmp_save_path = f"get_struc_seq_{process_id}_{time.time()}.tsv"
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if foldseek_verbose:
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cmd = f"{foldseek} structureto3didescriptor --threads 1 --chain-name-mode 1 {path} {tmp_save_path}"
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else:
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cmd = f"{foldseek} structureto3didescriptor -v 0 --threads 1 --chain-name-mode 1 {path} {tmp_save_path}"
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os.system(cmd)
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seq_dict = {}
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name = os.path.basename(path)
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with open(tmp_save_path, "r") as r:
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for i, line in enumerate(r):
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desc, seq, struc_seq = line.split("\t")[:3]
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if plddt_mask:
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plddts = extract_plddt(path)
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assert len(plddts) == len(struc_seq), f"Length mismatch: {len(plddts)} != {len(struc_seq)}"
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indices = np.where(plddts < plddt_threshold)[0]
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np_seq = np.array(list(struc_seq))
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np_seq[indices] = "#"
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struc_seq = "".join(np_seq)
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name_chain = desc.split(" ")[0]
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chain = name_chain.replace(name, "").split("_")[-1]
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if chains is None or chain in chains:
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if chain not in seq_dict:
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combined_seq = "".join([a + b.lower() for a, b in zip(seq, struc_seq)])
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seq_dict[chain] = (seq, struc_seq, combined_seq)
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os.remove(tmp_save_path)
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os.remove(tmp_save_path + ".dbtype")
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return seq_dict
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def extract_plddt(pdb_path: str) -> np.ndarray:
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"""
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Extract plddt scores from pdb file.
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Args:
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pdb_path: Path to pdb file.
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Returns:
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plddts: plddt scores.
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"""
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with open(pdb_path, "r") as r:
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plddt_dict = {}
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for line in r:
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line = re.sub(' +', ' ', line).strip()
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splits = line.split(" ")
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if splits[0] == "ATOM":
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if len(splits[4]) == 1:
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pos = int(splits[5])
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else:
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pos = int(splits[4][1:])
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plddt = float(splits[-2])
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if pos not in plddt_dict:
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plddt_dict[pos] = [plddt]
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else:
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plddt_dict[pos].append(plddt)
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plddts = np.array([np.mean(v) for v in plddt_dict.values()])
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return plddts
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if __name__ == '__main__':
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foldseek = "/sujin/bin/foldseek"
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test_path = "/sujin/Datasets/FLIP/meltome/af2_structures/A0A061ACX4.pdb"
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plddt_path = "/sujin/Datasets/FLIP/meltome/af2_plddts/A0A061ACX4.json"
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res = get_struc_seq(foldseek, test_path, plddt_path=plddt_path, plddt_threshold=70.)
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print(res["A"][1].lower()) |
