# Copyright 2024 ByteDance and/or its affiliates. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import concurrent.futures import copy import logging import random import warnings from collections import Counter from typing import Any import biotite.structure as struc import numpy as np from biotite.structure import AtomArray from rdkit import Chem from rdkit.Chem import AllChem from protenix.data import ccd logger = logging.getLogger(__name__) DNA_1to3 = { "A": "DA", "G": "DG", "C": "DC", "T": "DT", "X": "DN", "I": "DI", # eg: pdb 114d "N": "DN", # eg: pdb 7r6t-3DR "U": "DU", # eg: pdb 7sd8 } RNA_1to3 = { "A": "A", "G": "G", "C": "C", "U": "U", "X": "N", "I": "I", # eg: pdb 7wv5 "N": "N", } PROTEIN_1to3 = { "A": "ALA", "R": "ARG", "N": "ASN", "D": "ASP", "C": "CYS", "Q": "GLN", "E": "GLU", "G": "GLY", "H": "HIS", "I": "ILE", "L": "LEU", "K": "LYS", "M": "MET", "F": "PHE", "P": "PRO", "S": "SER", "T": "THR", "W": "TRP", "Y": "TYR", "V": "VAL", "X": "UNK", } def add_reference_features(atom_array: AtomArray) -> AtomArray: """ Add reference features of each resiude to atom_array Args: atom_array (AtomArray): biotite AtomArray Returns: AtomArray: biotite AtomArray with reference features - ref_pos: reference conformer atom positions - ref_charge (n): reference conformer atom charges - ref_mask: reference conformer atom masks """ atom_count = len(atom_array) ref_pos = np.zeros((atom_count, 3), dtype=np.float32) ref_charge = np.zeros(atom_count, dtype=int) ref_mask = np.zeros(atom_count, dtype=int) starts = struc.get_residue_starts(atom_array, add_exclusive_stop=True) for start, stop in zip(starts[:-1], starts[1:]): res_name = atom_array.res_name[start] if res_name == "UNL": # UNL is smiles ligand, copy info from atom_array ref_pos[start:stop] = atom_array.coord[start:stop] ref_charge[start:stop] = atom_array.charge[start:stop] ref_mask[start:stop] = 1 continue ref_info = ccd.get_ccd_ref_info(res_name) if ref_info: atom_sub_idx = [ *map(ref_info["atom_map"].get, atom_array.atom_name[start:stop]) ] ref_pos[start:stop] = ref_info["coord"][atom_sub_idx] ref_charge[start:stop] = ref_info["charge"][atom_sub_idx] ref_mask[start:stop] = ref_info["mask"][atom_sub_idx] else: logging.warning(f"no reference info for {res_name}") atom_array.set_annotation("ref_pos", ref_pos) atom_array.set_annotation("ref_charge", ref_charge) atom_array.set_annotation("ref_mask", ref_mask) return atom_array def _remove_non_std_ccd_leaving_atoms(atom_array: AtomArray) -> AtomArray: """ Check polymer connections and remove non-standard leaving atoms Args: atom_array (AtomArray): biotite AtomArray Returns: AtomArray: biotite AtomArray with leaving atoms removed. """ connected = np.zeros(atom_array.res_id[-1], dtype=bool) for i, j, t in atom_array.bonds._bonds: if abs(atom_array.res_id[i] - atom_array.res_id[j]) == 1: connected[atom_array.res_id[[i, j]].min()] = True leaving_atoms = np.zeros(len(atom_array), dtype=bool) for res_id, conn in enumerate(connected): if res_id == 0 or conn: continue # Res_id start from 1 res_name_i = atom_array.res_name[atom_array.res_id == res_id][0] res_name_j = atom_array.res_name[atom_array.res_id == res_id + 1][0] warnings.warn( f"No C-N or O3'-P bond between residue {res_name_i}({res_id}) and residue {res_name_j}({res_id+1}). \n" f"all leaving atoms will be removed for both residues." ) for idx, res_name in zip([res_id, res_id + 1], [res_name_i, res_name_j]): staying_atoms = ccd.get_component_atom_array( res_name, keep_leaving_atoms=False, keep_hydrogens=False ).atom_name if idx == 1 and ccd.get_mol_type(res_name) in ("dna", "rna"): staying_atoms = np.append(staying_atoms, ["OP3"]) if idx == atom_array.res_id[-1] and ccd.get_mol_type(res_name) == "protein": staying_atoms = np.append(staying_atoms, ["OXT"]) leaving_atoms |= (atom_array.res_id == idx) & ( ~np.isin(atom_array.atom_name, staying_atoms) ) return atom_array[~leaving_atoms] def find_range_by_index(starts: np.ndarray, atom_index: int) -> tuple[int, int]: """ Find the residue range of an atom index Args: starts (np.ndarray): Residue starts or Chain starts with exclusive stop. atom_index (int): Atom index. Returns: tuple[int, int]: range (start, stop). """ for start, stop in zip(starts[:-1], starts[1:]): if start <= atom_index < stop: return start, stop raise ValueError(f"atom_index {atom_index} not found in starts {starts}") def remove_leaving_atoms(atom_array: AtomArray, bond_count: dict) -> AtomArray: """ Remove leaving atoms based on ccd info Args: atom_array (AtomArray): Biotite Atom array. bond_count (dict): atom index -> Bond count. Returns: AtomArray: Biotite Atom array with leaving atoms removed. """ remove_indices = [] res_starts = struc.get_residue_starts(atom_array, add_exclusive_stop=True) for centre_idx, b_count in bond_count.items(): res_name = atom_array.res_name[centre_idx] centre_name = atom_array.atom_name[centre_idx] comp = ccd.get_component_atom_array( res_name, keep_leaving_atoms=True, keep_hydrogens=False ) if comp is None: continue leaving_groups = comp.central_to_leaving_groups.get(centre_name) if leaving_groups is None: continue if b_count > len(leaving_groups): warnings.warn( f"centre atom {centre_name=} {res_name=} {centre_idx=} has {b_count} inter residue bonds, greater than number of leaving groups:{leaving_groups}, remove all leaving atoms.\n" f"atom info: {atom_array[centre_idx]=}" ) remove_groups = leaving_groups else: remove_groups = random.sample(leaving_groups, b_count) start, stop = find_range_by_index(res_starts, centre_idx) # Find leaving atom indices for group in remove_groups: for atom_name in group: leaving_idx = np.where(atom_array.atom_name[start:stop] == atom_name)[0] if len(leaving_idx) == 0: logging.info(f"{atom_name=} not found in residue {res_name}, ") continue remove_indices.append(leaving_idx[0] + start) if not remove_indices: return atom_array keep_mask = np.ones(len(atom_array), dtype=bool) keep_mask[remove_indices] = False return atom_array[keep_mask] def _add_bonds_to_terminal_residues(atom_array: AtomArray) -> AtomArray: """ Add bonds to terminal residues (eg: ACE, NME) Args: atom_array (AtomArray): Biotite AtomArray Returns: AtomArray: Biotite AtomArray with non-standard polymer bonds """ if atom_array.res_name[0] == "ACE": term_res_idx = atom_array.res_id[0] next_res_idx = term_res_idx + 1 term_atom_idx = np.where( (atom_array.res_id == term_res_idx) & (atom_array.atom_name == "C") )[0] next_atom_idx = np.where( (atom_array.res_id == next_res_idx) & (atom_array.atom_name == "N") )[0] if len(term_atom_idx) > 0 and len(next_atom_idx) > 0: atom_array.bonds.add_bond(term_atom_idx[0], next_atom_idx[0], 1) if atom_array.res_name[-1] == "NME": term_res_idx = atom_array.res_id[-1] prev_res_idx = term_res_idx - 1 term_atom_idx = np.where( (atom_array.res_id == term_res_idx) & (atom_array.atom_name == "N") )[0] prev_atom_idx = np.where( (atom_array.res_id == prev_res_idx) & (atom_array.atom_name == "C") )[0] if len(prev_atom_idx) > 0 and len(term_atom_idx) > 0: atom_array.bonds.add_bond(prev_atom_idx[0], term_atom_idx[0], 1) return atom_array def _build_polymer_atom_array(ccd_seqs: list[str]) -> tuple[AtomArray, struc.BondList]: """ Build polymer atom_array from ccd codes, but not remove leaving atoms Args: ccd_seqs: a list of ccd code in sequence, ["MET", "ALA"] or ["DA", "DT"] Returns: AtomArray: Biotite AtomArray of chain BondList: Biotite BondList of polymer bonds (C-N or O3'-P) """ chain = struc.AtomArray(0) for res_id, res_name in enumerate(ccd_seqs): # Keep all leaving atoms, will remove leaving atoms later residue = ccd.get_component_atom_array( res_name, keep_leaving_atoms=True, keep_hydrogens=False ) residue.res_id[:] = res_id + 1 chain += residue res_starts = struc.get_residue_starts(chain, add_exclusive_stop=True) polymer_bonds = ccd._connect_inter_residue(chain, res_starts) if chain.bonds is None: chain.bonds = polymer_bonds else: chain.bonds = chain.bonds.merge(polymer_bonds) chain = _add_bonds_to_terminal_residues(chain) bond_count = {} for i, j, t in polymer_bonds._bonds: bond_count[i] = bond_count.get(i, 0) + 1 bond_count[j] = bond_count.get(j, 0) + 1 chain = remove_leaving_atoms(chain, bond_count) chain = _remove_non_std_ccd_leaving_atoms(chain) return chain def build_polymer(entity_info: dict) -> dict: """ Build a polymer from a polymer info dict example: { "name": "polymer", "sequence": "GPDSMEEVVVPEEPPKLVSALATYVQQERLCTMFLSIANKLLPLKP", "count": 1 } Args: item (dict): polymer info dict Returns: dict: {"atom_array": biotite_AtomArray_object} """ poly_type, info = list(entity_info.items())[0] if poly_type == "proteinChain": ccd_seqs = [PROTEIN_1to3[x] for x in info["sequence"]] if modifications := info.get("modifications"): for m in modifications: index = m["ptmPosition"] - 1 mtype = m["ptmType"] if mtype.startswith("CCD_"): ccd_seqs[index] = mtype[4:] else: raise ValueError(f"unknown modification type: {mtype}") if glycans := info.get("glycans"): logging.warning(f"glycans not supported: {glycans}") chain_array = _build_polymer_atom_array(ccd_seqs) elif poly_type in ("dnaSequence", "rnaSequence"): map_1to3 = DNA_1to3 if poly_type == "dnaSequence" else RNA_1to3 ccd_seqs = [map_1to3[x] for x in info["sequence"]] if modifications := info.get("modifications"): for m in modifications: index = m["basePosition"] - 1 mtype = m["modificationType"] if mtype.startswith("CCD_"): ccd_seqs[index] = mtype[4:] else: raise ValueError(f"unknown modification type: {mtype}") chain_array = _build_polymer_atom_array(ccd_seqs) else: raise ValueError( "polymer type must be proteinChain, dnaSequence or rnaSequence" ) chain_array = add_reference_features(chain_array) return {"atom_array": chain_array} def rdkit_mol_to_atom_array(mol: Chem.Mol, removeHs: bool = True) -> AtomArray: """ Convert rdkit mol to biotite AtomArray Args: mol (Chem.Mol): rdkit mol removeHs (bool): whether to remove hydrogens in atom_array Returns: AtomArray: biotite AtomArray """ atom_count = mol.GetNumAtoms() atom_array = AtomArray(atom_count) atom_array.hetero[:] = True atom_array.res_name[:] = "UNL" atom_array.add_annotation("charge", int) conf = mol.GetConformer() coord = conf.GetPositions() element_count = Counter() for i, atom in enumerate(mol.GetAtoms()): element = atom.GetSymbol().upper() element_count[element] += 1 atom_name = f"{element}{element_count[element]}" atom.SetProp("name", atom_name) atom_array.atom_name[i] = atom_name atom_array.element[i] = element atom_array.charge[i] = atom.GetFormalCharge() atom_array.coord[i, :] = coord[i, :] bonds = [] for bond in mol.GetBonds(): bonds.append([bond.GetBeginAtomIdx(), bond.GetEndAtomIdx()]) atom_array.bonds = struc.BondList(atom_count, np.array(bonds)) if removeHs: atom_array = atom_array[atom_array.element != "H"] return atom_array def rdkit_mol_to_atom_info(mol: Chem.Mol) -> dict[str, Any]: """ Convert RDKit Mol to atom_info dict. Args: mol (Chem.Mol): rdkit mol Returns: dict: info of atoms example: { "atom_array": biotite_AtomArray_object, "atom_map_to_atom_name": {1: "C2"}, # only for smiles } """ atom_info = {} atom_map_to_atom_name = {} atom_idx_to_atom_name = {} element_count = Counter() for atom in mol.GetAtoms(): element = atom.GetSymbol().upper() element_count[element] += 1 atom_name = f"{element}{element_count[element]}" atom.SetProp("name", atom_name) if atom.GetAtomMapNum() != 0: atom_map_to_atom_name[atom.GetAtomMapNum()] = atom_name atom_idx_to_atom_name[atom.GetIdx()] = atom_name if atom_map_to_atom_name: # Atom map for input SMILES atom_info["atom_map_to_atom_name"] = atom_map_to_atom_name else: # Atom index for input file atom_info["atom_map_to_atom_name"] = atom_idx_to_atom_name # Atom_array without hydrogens atom_info["atom_array"] = rdkit_mol_to_atom_array(mol, removeHs=True) return atom_info def lig_file_to_atom_info(lig_file_path: str) -> dict[str, Any]: """ Convert ligand file to biotite AtomArray. Args: lig_file_path (str): ligand file path with one of the following suffixes: [mol, mol2, sdf, pdb] Returns: dict: info of atoms example: { "atom_array": biotite_AtomArray_object, "atom_map_to_atom_name": {1: "C2"}, # only for smiles } """ if lig_file_path.endswith(".mol"): mol = Chem.MolFromMolFile(lig_file_path) elif lig_file_path.endswith(".sdf"): suppl = Chem.SDMolSupplier(lig_file_path) mol = next(suppl) elif lig_file_path.endswith(".pdb"): mol = Chem.MolFromPDBFile(lig_file_path) elif lig_file_path.endswith(".mol2"): mol = Chem.MolFromMol2File(lig_file_path) else: raise ValueError(f"Invalid ligand file type: .{lig_file_path.split('.')[-1]}") assert ( mol is not None ), f"Failed to retrieve molecule from file, invalid ligand file: {lig_file_path}. \ Please provide a file with one of the following suffixes: [mol, mol2, sdf, pdb]." assert ( mol.GetConformer().Is3D() ), f"3D conformer not found in ligand file: {lig_file_path}" atom_info = rdkit_mol_to_atom_info(mol) return atom_info def smiles_to_atom_info(smiles: str) -> dict: """ Convert smiles to atom_array, and atom_map_to_atom_name Args: smiles (str): smiles string, like "CCCC", or "[C:1]NC(=O)" (use num to label covalent bond atom.) Returns: dict: info of atoms example: { "atom_array": biotite_AtomArray_object, "atom_map_to_atom_name": {1: "C2"}, # only for smiles } """ atom_info = {} mol = Chem.MolFromSmiles(smiles) mol = Chem.AddHs(mol) with concurrent.futures.ThreadPoolExecutor() as executor: future = executor.submit(AllChem.EmbedMolecule, mol) try: ret_code = future.result(timeout=90) except concurrent.futures.TimeoutError as exc: raise TimeoutError( 'Conformer generation timed out. \ Please change the "ligand" input format to "CCD_" or "FILE_".' ) from exc if ret_code != 0: # retry with random coords ret_code = AllChem.EmbedMolecule(mol, useRandomCoords=True) assert ret_code == 0, f"Conformer generation failed for input SMILES: {smiles}" atom_info = rdkit_mol_to_atom_info(mol) return atom_info def build_ligand(entity_info: dict) -> dict: """ Build a ligand from a ligand entity info dict example1: { "ligand": { "ligand": "CCD_ATP", "count": 1 } }, example2:{ "ligand": { "ligand": "CCC=O", # smiles "count": 1 } }, example3:{ "ion": { "ion": "NA", "count": 3 } }, Args: entity_info (dict): ligand entity info Returns: dict: info of atoms example: { "atom_array": biotite_AtomArray_object, "index_to_atom_name": {1: "C2"}, # only for smiles } """ if info := entity_info.get("ion"): ccd_code = [info["ion"]] elif info := entity_info.get("ligand"): ligand_str = info["ligand"] if ligand_str.startswith("CCD_"): ccd_code = ligand_str[4:].split("_") else: ccd_code = None atom_info = {} if ccd_code is not None: atom_array = AtomArray(0) res_ids = [] for idx, code in enumerate(ccd_code): ccd_atom_array = ccd.get_component_atom_array( code, keep_leaving_atoms=True, keep_hydrogens=False ) atom_array += ccd_atom_array res_id = idx + 1 res_ids += [res_id] * len(ccd_atom_array) atom_info["atom_array"] = atom_array atom_info["atom_array"].res_id[:] = res_ids else: if info["ligand"].startswith("FILE_"): lig_file_path = ligand_str[5:] atom_info = lig_file_to_atom_info(lig_file_path) else: atom_info = smiles_to_atom_info(ligand_str) atom_info["atom_array"].res_id[:] = 1 atom_info["atom_array"] = add_reference_features(atom_info["atom_array"]) return atom_info def add_entity_atom_array(single_job_dict: dict) -> dict: """ Add atom_array to each entity in single_job_dict Args: single_job_dict (dict): input job dict Returns: dict: deepcopy and updated job dict with atom_array """ single_job_dict = copy.deepcopy(single_job_dict) sequences = single_job_dict["sequences"] smiles_ligand_count = 0 for entity_info in sequences: if info := entity_info.get("proteinChain"): atom_info = build_polymer(entity_info) elif info := entity_info.get("dnaSequence"): atom_info = build_polymer(entity_info) elif info := entity_info.get("rnaSequence"): atom_info = build_polymer(entity_info) elif info := entity_info.get("ligand"): atom_info = build_ligand(entity_info) if not info["ligand"].startswith("CCD_"): smiles_ligand_count += 1 assert smiles_ligand_count <= 99, "too many smiles ligands" # use lower case res_name (l01, l02, ..., l99) to avoid conflict with CCD code atom_info["atom_array"].res_name[:] = f"l{smiles_ligand_count:02d}" elif info := entity_info.get("ion"): atom_info = build_ligand(entity_info) else: raise ValueError( "entity type must be proteinChain, dnaSequence, rnaSequence, ligand or ion" ) info.update(atom_info) return single_job_dict