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from collections import defaultdict
from dataclasses import dataclass, replace
from typing import Dict, List, Optional, Set, Tuple
import gemmi
import numpy as np
from rdkit import rdBase
import rdkit
from rdkit.Chem import AllChem
from rdkit.Chem.rdchem import Mol
from sklearn.neighbors import KDTree
from boltzgen.data import const
from boltzgen.data.data import (
Atom,
Bond,
Chain,
Coords,
Ensemble,
Interface,
Residue,
Structure,
StructureInfo,
)
from boltzgen.data.mol import load_molecules
from collections import defaultdict
####################################################################################################
# DATACLASSES
####################################################################################################
@dataclass(frozen=True, slots=True)
class ParsedAtom:
"""A parsed atom object."""
name: str
coords: Tuple[float, float, float]
is_present: bool
bfactor: float
plddt: Optional[float] = None
@dataclass(frozen=True, slots=True)
class ParsedBond:
"""A parsed bond object."""
atom_1: int
atom_2: int
type: int
@dataclass(frozen=True, slots=True)
class ParsedResidue:
"""A parsed residue object."""
name: str
type: int
idx: int
atoms: List[ParsedAtom]
bonds: List[ParsedBond]
auth_idx: Optional[int]
atom_center: int
atom_disto: int
is_standard: bool
is_present: bool
@dataclass(frozen=True, slots=True)
class ParsedChain:
"""A parsed chain object."""
name: str
entity: str
type: int
residues: List[ParsedResidue]
sequence: Optional[str] = None
@dataclass(frozen=True, slots=True)
class ParsedConnection:
"""A parsed connection object."""
chain_1: str
chain_2: str
residue_index_1: int
residue_index_2: int
atom_index_1: str
atom_index_2: str
@dataclass(frozen=True, slots=True)
class ParsedStructure:
"""A parsed structure object."""
data: Structure
info: StructureInfo
sequences: Dict[str, str]
####################################################################################################
# HELPERS
####################################################################################################
def get_mol(ccd: str, mols: Dict, moldir: str) -> Mol:
"""Get mol from CCD code.
Return mol with ccd from mols if it is in mols. Otherwise load it from moldir,
add it to mols, and return the mol.
"""
mol = mols.get(ccd)
if mol is None:
# Load molecule
mol = load_molecules(moldir, [ccd])[ccd]
# Add to resource/dict
if isinstance(mols, dict):
mols[ccd] = mol
else:
mols.set(ccd, mol)
return mol
def get_dates(block: gemmi.cif.Block) -> Tuple[str, str, str]:
"""Get the deposited, released, and last revision dates.
Parameters
----------
block : gemmi.cif.Block
The block to process.
Returns
-------
str
The deposited date.
str
The released date.
str
The last revision date.
"""
deposited = "_pdbx_database_status.recvd_initial_deposition_date"
revision = "_pdbx_audit_revision_history.revision_date"
deposit_date = revision_date = release_date = ""
with contextlib.suppress(Exception):
deposit_date = block.find([deposited])[0][0]
release_date = block.find([revision])[0][0]
revision_date = block.find([revision])[-1][0]
return deposit_date, release_date, revision_date
def get_resolution(block: gemmi.cif.Block) -> float:
"""Get the resolution from a gemmi structure.
Parameters
----------
block : gemmi.cif.Block
The block to process.
Returns
-------
float
The resolution.
"""
resolution = 0.0
for res_key in (
"_refine.ls_d_res_high",
"_em_3d_reconstruction.resolution",
"_reflns.d_resolution_high",
):
with contextlib.suppress(Exception):
resolution = float(block.find([res_key])[0].str(0))
break
return resolution
def get_method(block: gemmi.cif.Block) -> str:
"""Get the method from a gemmi structure.
Parameters
----------
block : gemmi.cif.Block
The block to process.
Returns
-------
str
The method.
"""
method = ""
method_key = "_exptl.method"
with contextlib.suppress(Exception):
methods = block.find([method_key])
method = ",".join([m.str(0).lower() for m in methods])
return method
def get_experiment_conditions(
block: gemmi.cif.Block,
) -> Tuple[Optional[float], Optional[float]]:
"""Get temperature and pH.
Parameters
----------
block : gemmi.cif.Block
The block to process.
Returns
-------
Tuple[float, float]
The temperature and pH.
"""
temperature = None
ph = None
keys_t = [
"_exptl_crystal_grow.temp",
"_pdbx_nmr_exptl_sample_conditions.temperature",
]
for key in keys_t:
with contextlib.suppress(Exception):
temperature = float(block.find([key])[0][0])
break
keys_ph = ["_exptl_crystal_grow.pH", "_pdbx_nmr_exptl_sample_conditions.pH"]
with contextlib.suppress(Exception):
for key in keys_ph:
ph = float(block.find([key])[0][0])
break
return temperature, ph
def get_unk_token(dtype: gemmi.PolymerType) -> str:
"""Get the unknown token for a given entity type.
Parameters
----------
dtype : gemmi.EntityType
The entity type.
Returns
-------
str
The unknown token.
"""
if dtype == gemmi.PolymerType.PeptideL:
unk = const.unk_token["PROTEIN"]
elif dtype == gemmi.PolymerType.Dna:
unk = const.unk_token["DNA"]
elif dtype == gemmi.PolymerType.Rna:
unk = const.unk_token["RNA"]
else:
msg = f"Unknown polymer type: {dtype}"
raise ValueError(msg)
return unk
def compute_covalent_ligands(
connections: List[gemmi.Connection],
subchain_map: Dict[Tuple[str, int], str],
entities: Dict[str, gemmi.Entity],
) -> Set[str]:
"""Compute the covalent ligands from a list of connections.
Parameters
----------
connections: List[gemmi.Connection]
The connections to process.
subchain_map: Dict[Tuple[str, int], str]
The mapping from chain, residue index to subchain name.
entities: Dict[str, gemmi.Entity]
The entities in the structure.
Returns
-------
set
The covalent ligand subchains.
"""
# Get covalent chain ids
covalent_chain_ids = set()
for connection in connections:
if connection.type.name not in {"Covale", "Disulf"}:
continue
# Map to correct subchain
chain_1_name = connection.partner1.chain_name
chain_2_name = connection.partner2.chain_name
res_1_id = connection.partner1.res_id.seqid
res_1_id = str(res_1_id.num) + str(res_1_id.icode).strip()
res_2_id = connection.partner2.res_id.seqid
res_2_id = str(res_2_id.num) + str(res_2_id.icode).strip()
subchain_1 = subchain_map[(chain_1_name, res_1_id)]
subchain_2 = subchain_map[(chain_2_name, res_2_id)]
# If non-polymer or branched, add to set
entity_1 = entities[subchain_1].entity_type.name
entity_2 = entities[subchain_2].entity_type.name
if entity_1 in {"NonPolymer", "Branched"}:
covalent_chain_ids.add(subchain_1)
if entity_2 in {"NonPolymer", "Branched"}:
covalent_chain_ids.add(subchain_2)
return covalent_chain_ids
def compute_interfaces(atom_data: np.ndarray, chain_data: np.ndarray) -> np.ndarray:
"""Compute the chain-chain interfaces from a gemmi structure.
Parameters
----------
atom_data : List[Tuple]
The atom data.
chain_data : List[Tuple]
The chain data.
Returns
-------
List[Tuple[int, int]]
The interfaces.
"""
# Compute chain_id per atom
chain_ids = []
for idx, chain in enumerate(chain_data):
chain_ids.extend([idx] * chain["atom_num"])
chain_ids = np.array(chain_ids)
# Filter to present atoms
coords = atom_data["coords"]
mask = atom_data["is_present"]
coords = coords[mask]
chain_ids = chain_ids[mask]
# Compute the distance matrix
tree = KDTree(coords, metric="euclidean")
query = tree.query_radius(coords, const.atom_interface_cutoff)
# Get unique chain pairs
interfaces = set()
for c1, pairs in zip(chain_ids, query):
chains = np.unique(chain_ids[pairs])
chains = chains[chains != c1]
interfaces.update((c1, c2) for c2 in chains)
# Get unique chain pairs
interfaces = [(min(i, j), max(i, j)) for i, j in interfaces]
interfaces = list({(int(i), int(j)) for i, j in interfaces})
interfaces = np.array(interfaces, dtype=Interface)
return interfaces
####################################################################################################
# PARSING
####################################################################################################
def parse_ccd_residue_from_smiles(
name: str,
ref_mol: Mol,
res_idx: int,
gemmi_mol: Optional[gemmi.Residue] = None,
is_covalent: bool = False,
) -> Optional[ParsedResidue]:
"""Parse a ligand from SMILES instead of CCD."""
is_present = gemmi_mol is not None
auth_idx = (
str(gemmi_mol.seqid.num) + str(gemmi_mol.seqid.icode).strip()
if is_present
else None
)
ref_mol = AllChem.RemoveHs(ref_mol, sanitize=False)
if ref_mol.GetNumAtoms() == 1:
pos = (0, 0, 0)
bfactor = 0
if is_present:
pos = (
gemmi_mol[0].pos.x,
gemmi_mol[0].pos.y,
gemmi_mol[0].pos.z,
)
bfactor = gemmi_mol[0].b_iso
ref_atom = ref_mol.GetAtoms()[0]
atom_name = f"{ref_atom.GetSymbol()}1"
atom = ParsedAtom(
name=atom_name,
coords=pos,
is_present=is_present,
bfactor=bfactor,
)
unk_prot_id = const.unk_token_ids["PROTEIN"]
return ParsedResidue(
name=name,
type=unk_prot_id,
atoms=[atom],
bonds=[],
idx=res_idx,
auth_idx=auth_idx,
atom_center=0,
atom_disto=0,
is_standard=False,
is_present=is_present,
)
pdb_pos = {}
bfactor = {}
if is_present:
for atom in gemmi_mol:
pos = (atom.pos.x, atom.pos.y, atom.pos.z)
pdb_pos[atom.name] = pos
bfactor[atom.name] = atom.b_iso
atoms = []
atom_idx = 0
idx_map = {}
element_counts = defaultdict(int)
for i, atom in enumerate(ref_mol.GetAtoms()):
symbol = atom.GetSymbol()
element_counts[symbol] += 1
atom_name = f"{symbol}{element_counts[symbol]}"
coords = pdb_pos.get(atom_name, (0, 0, 0))
atom_is_present = atom_name in pdb_pos
atoms.append(
ParsedAtom(
name=atom_name,
coords=coords,
is_present=atom_is_present,
bfactor=bfactor.get(atom_name, 0),
)
)
idx_map[i] = atom_idx
atom_idx += 1
bonds = []
unk_bond = const.bond_type_ids[const.unk_bond_type]
for bond in ref_mol.GetBonds():
idx_1 = bond.GetBeginAtomIdx()
idx_2 = bond.GetEndAtomIdx()
if (idx_1 not in idx_map) or (idx_2 not in idx_map):
continue
start = min(idx_map[idx_1], idx_map[idx_2])
end = max(idx_map[idx_1], idx_map[idx_2])
bond_type = const.bond_type_ids.get(bond.GetBondType().name, unk_bond)
bonds.append(ParsedBond(start, end, bond_type))
unk_prot_id = const.unk_token_ids["PROTEIN"]
return ParsedResidue(
name=name,
type=unk_prot_id,
atoms=atoms,
bonds=bonds,
idx=res_idx,
atom_center=0,
atom_disto=0,
auth_idx=auth_idx,
is_standard=False,
is_present=is_present,
)
def parse_ccd_residue( # noqa: PLR0915
name: str,
ref_mol: Mol,
res_idx: int,
gemmi_mol: Optional[gemmi.Residue] = None,
is_covalent: bool = False,
) -> Optional[ParsedResidue]:
"""Parse an MMCIF ligand.
First tries to get the SMILES string from the RCSB.
Then, tries to infer atom ordering using RDKit.
Parameters
----------
name: str
The name of the molecule to parse.
components : Dict
The preprocessed PDB components dictionary.
res_idx : int
The residue index.
gemmi_mol : Optional[gemmi.Residue]
The PDB molecule, as a gemmi Residue object, if any.
Returns
-------
ParsedResidue, optional
The output ParsedResidue, if successful.
"""
# Check if we have a PDB structure for this residue,
# it could be a missing residue from the sequence
is_present = gemmi_mol is not None
# Save original index (required for parsing connections)
if is_present:
auth_idx = gemmi_mol.seqid
auth_idx = str(auth_idx.num) + str(auth_idx.icode).strip()
else:
auth_idx = None
# Remove hydrogens
ref_mol = AllChem.RemoveHs(ref_mol, sanitize=False)
# Check if this is a single atom CCD residue
if ref_mol.GetNumAtoms() == 1:
pos = (0, 0, 0)
bfactor = 0
if is_present:
pos = (
gemmi_mol[0].pos.x,
gemmi_mol[0].pos.y,
gemmi_mol[0].pos.z,
)
bfactor = gemmi_mol[0].b_iso
ref_atom = ref_mol.GetAtoms()[0]
atom = ParsedAtom(
name=ref_atom.GetProp("name"),
coords=pos,
is_present=is_present,
bfactor=bfactor,
)
unk_prot_id = const.unk_token_ids["PROTEIN"]
residue = ParsedResidue(
name=name,
type=unk_prot_id,
atoms=[atom],
bonds=[],
idx=res_idx,
auth_idx=auth_idx,
atom_center=0, # Placeholder, no center
atom_disto=0, # Placeholder, no center
is_standard=False,
is_present=is_present,
)
return residue
# If multi-atom, start by getting the PDB coordinates
pdb_pos = {}
bfactor = {}
if is_present:
# Match atoms based on names
for atom in gemmi_mol:
atom: gemmi.Atom
pos = (atom.pos.x, atom.pos.y, atom.pos.z)
pdb_pos[atom.name] = pos
bfactor[atom.name] = atom.b_iso
# Parse each atom in order of the reference mol
atoms = []
atom_idx = 0
idx_map = {} # Used for bonds later
for i, atom in enumerate(ref_mol.GetAtoms()):
# Get atom name, charge, element and reference coordinates
atom_name = atom.GetProp("name")
# If the atom is a leaving atom, skip if not in the PDB and is_covalent
if (
atom.HasProp("leaving_atom")
and int(atom.GetProp("leaving_atom")) == 1
and is_covalent
and (atom_name not in pdb_pos)
):
continue
# Get PDB coordinates, if any
coords = pdb_pos.get(atom_name.upper())
if coords is None:
atom_is_present = False
coords = (0, 0, 0)
else:
atom_is_present = True
# Add atom to list
atoms.append(
ParsedAtom(
name=atom_name,
coords=coords,
is_present=atom_is_present,
bfactor=bfactor.get(atom_name, 0),
)
)
idx_map[i] = atom_idx
atom_idx += 1
# Load bonds
bonds = []
unk_bond = const.bond_type_ids[const.unk_bond_type]
for bond in ref_mol.GetBonds():
idx_1 = bond.GetBeginAtomIdx()
idx_2 = bond.GetEndAtomIdx()
# Skip bonds with atoms ignored
if (idx_1 not in idx_map) or (idx_2 not in idx_map):
continue
idx_1 = idx_map[idx_1]
idx_2 = idx_map[idx_2]
start = min(idx_1, idx_2)
end = max(idx_1, idx_2)
bond_type = bond.GetBondType().name
bond_type = const.bond_type_ids.get(bond_type, unk_bond)
bonds.append(ParsedBond(start, end, bond_type))
unk_prot_id = const.unk_token_ids["PROTEIN"]
return ParsedResidue(
name=name,
type=unk_prot_id,
atoms=atoms,
bonds=bonds,
idx=res_idx,
atom_center=0,
atom_disto=0,
auth_idx=auth_idx,
is_standard=False,
is_present=is_present,
)
def parse_polymer( # noqa: C901, PLR0915, PLR0912
polymer: gemmi.ResidueSpan,
polymer_type: gemmi.PolymerType,
sequence: List[str],
chain_id: str,
entity: str,
mols: Dict[str, Mol],
moldir: str,
use_original_res_idx: bool = False,
entity_poly_seq: Optional[List[List]] = None,
) -> Optional[ParsedChain]:
"""Process a gemmi Polymer into a chain object.
Performs alignment of the full sequence to the polymer
residues. Loads coordinates and masks for the atoms in
the polymer, following the ordering in const.atom_order.
Parameters
----------
polymer : gemmi.ResidueSpan
The polymer to process.
polymer_type : gemmi.PolymerType
The polymer type.
sequence : str
The full sequence of the polymer.
chain_id : str
The chain identifier.
entity : str
The entity name.
Returns
-------
ParsedChain, optional
The output chain, if successful.
Raises
------
ValueError
If the alignment fails.
"""
assert entity_poly_seq is not None
# Since the polymer object already contains the global idx, we don't need to perform the alignment
sequence = [_entity[1] for _entity in entity_poly_seq]
i = 0
ref_res = set(const.tokens)
parsed = []
for j, res_name in entity_poly_seq:
res = None
name_to_atom = {}
if i < len(polymer) and j == polymer[i].label_seq: # residue is not missing.
# double check.
assert polymer[i].name == res_name
res = polymer[i]
name_to_atom = {a.name.upper(): a for a in res}
i += 1
# Add residue to parsed list
if res is not None:
auth_idx = res.seqid.num
res_idx = res.label_seq - 1 # convert to 0 indexing
else:
auth_idx = None
res_idx = j
# Map MSE to MET, put the selenium atom in the sulphur column
if res_name == "MSE":
res_name = "MET"
if "SE" in name_to_atom:
name_to_atom["SD"] = name_to_atom["SE"]
# Handle non-standard residues
elif res_name not in ref_res:
modified_mol = get_mol(res_name, mols, moldir)
if modified_mol is not None:
residue = parse_ccd_residue(
name=res_name,
ref_mol=modified_mol,
res_idx=res_idx if use_original_res_idx else j - 1,
gemmi_mol=res,
is_covalent=True,
)
parsed.append(residue)
continue
else: # noqa: RET507
res_name = "UNK"
# Load regular residues
ref_mol = get_mol(res_name, mols, moldir)
ref_mol = AllChem.RemoveHs(ref_mol, sanitize=False)
# Only use reference atoms set in constants
ref_name_to_atom = {a.GetProp("name"): a for a in ref_mol.GetAtoms()}
ref_atoms = [ref_name_to_atom[a] for a in const.ref_atoms[res_name]]
# Iterate, always in the same order
atoms: List[ParsedAtom] = []
for ref_atom in ref_atoms:
# Get atom name
atom_name = ref_atom.GetProp("name")
# Get coordinates from PDB
if atom_name in name_to_atom:
atom: gemmi.Atom = name_to_atom[atom_name]
atom_is_present = True
coords = (atom.pos.x, atom.pos.y, atom.pos.z)
bfactor = atom.b_iso
else:
atom_is_present = False
coords = (0, 0, 0)
bfactor = 0
# Add atom to list
atoms.append(
ParsedAtom(
name=atom_name,
coords=coords,
is_present=atom_is_present,
bfactor=bfactor,
)
)
# Fix naming errors in arginine residues where NH2 is
# incorrectly assigned to be closer to CD than NH1
if (res is not None) and (res_name == "ARG"):
ref_atoms: List[str] = const.ref_atoms["ARG"]
cd = atoms[ref_atoms.index("CD")]
nh1 = atoms[ref_atoms.index("NH1")]
nh2 = atoms[ref_atoms.index("NH2")]
cd_coords = np.array(cd.coords)
nh1_coords = np.array(nh1.coords)
nh2_coords = np.array(nh2.coords)
if all(atom.is_present for atom in (cd, nh1, nh2)) and (
np.linalg.norm(nh1_coords - cd_coords)
> np.linalg.norm(nh2_coords - cd_coords)
):
atoms[ref_atoms.index("NH1")] = replace(nh1, coords=nh2.coords)
atoms[ref_atoms.index("NH2")] = replace(nh2, coords=nh1.coords)
atom_center = const.res_to_center_atom_id[res_name]
atom_disto = const.res_to_disto_atom_id[res_name]
parsed.append(
ParsedResidue(
name=res_name,
type=const.token_ids[res_name],
atoms=atoms,
bonds=[],
idx=res_idx if use_original_res_idx else j - 1,
atom_center=atom_center,
atom_disto=atom_disto,
is_standard=True,
is_present=res is not None,
auth_idx=auth_idx,
)
)
res_indices = [r.idx for r in parsed]
assert len(set(res_indices)) == len(res_indices), (
"There was an instance where the residue index of a present residue is the same as the assigned residue index for a missing residue (which only has its residue type in the seq_res)"
)
# Get polymer class
if polymer_type == gemmi.PolymerType.PeptideL:
chain_type = const.chain_type_ids["PROTEIN"]
elif polymer_type == gemmi.PolymerType.Dna:
chain_type = const.chain_type_ids["DNA"]
elif polymer_type == gemmi.PolymerType.Rna:
chain_type = const.chain_type_ids["RNA"]
# Return polymer object
return ParsedChain(
name=chain_id,
entity=entity,
residues=parsed,
type=chain_type,
sequence=gemmi.one_letter_code(sequence),
)
def parse_connection(
connection: gemmi.Connection,
chains: List[ParsedChain],
subchain_map: Dict[Tuple[str, int], str],
) -> ParsedConnection:
"""Parse (covalent) connection from a gemmi Connection.
Parameters
----------
connections : gemmi.ConnectionList
The connection list to parse.
chains : List[Chain]
The parsed chains.
subchain_map : Dict[Tuple[str, int], str]
The mapping from chain, residue index to subchain name.
Returns
-------
List[Connection]
The parsed connections.
"""
# Map to correct subchains
chain_1_name = connection.partner1.chain_name
chain_2_name = connection.partner2.chain_name
res_1_id = connection.partner1.res_id.seqid
res_1_id = str(res_1_id.num) + str(res_1_id.icode).strip()
res_2_id = connection.partner2.res_id.seqid
res_2_id = str(res_2_id.num) + str(res_2_id.icode).strip()
subchain_1 = subchain_map[(chain_1_name, res_1_id)]
subchain_2 = subchain_map[(chain_2_name, res_2_id)]
# Get chain indices
chain_1 = next(chain for chain in chains if (chain.name == subchain_1))
chain_2 = next(chain for chain in chains if (chain.name == subchain_2))
# Get residue indices
res_1_idx, res_1 = next(
(idx, res)
for idx, res in enumerate(chain_1.residues)
if (str(res.auth_idx) == res_1_id)
)
res_2_idx, res_2 = next(
(idx, res)
for idx, res in enumerate(chain_2.residues)
if (str(res.auth_idx) == res_2_id)
)
# Get atom indices
atom_index_1 = next(
idx
for idx, atom in enumerate(res_1.atoms)
if atom.name == connection.partner1.atom_name
)
atom_index_2 = next(
idx
for idx, atom in enumerate(res_2.atoms)
if atom.name == connection.partner2.atom_name
)
conn = ParsedConnection(
chain_1=subchain_1,
chain_2=subchain_2,
residue_index_1=res_1_idx,
residue_index_2=res_2_idx,
atom_index_1=atom_index_1,
atom_index_2=atom_index_2,
)
return conn
def parse_mmcif( # noqa: C901, PLR0915, PLR0912
path: str,
mols: Optional[Dict[str, Mol]] = None,
moldir: Optional[str] = None,
use_assembly: bool = True,
use_original_res_idx: bool = False,
) -> ParsedStructure:
"""Parse a structure in MMCIF format.
Parameters
----------
mmcif_file : PathLike
Path to the MMCIF file.
use_original_res_idx : bool
Uses the res_idx for the res_idx in the Residues in the returned structure
that was in the mmcif file for each residue instead of using the index in the
seqres that is obtained after aligning the seqres to the sequence of amino acids from the present residues.
Returns
-------
ParsedStructure
The parsed structure.
"""
# Set mols
mols = {} if mols is None else mols
# Parse MMCIF input file
block = gemmi.cif.read(str(path))[0]
try:
parsed = mmcif_from_block(
block,
mols=mols,
moldir=moldir,
use_assembly=use_assembly,
use_original_res_idx=use_original_res_idx,
)
except Exception as e:
print(f"\n\nFailed parsing mmcif: {path} \n\n\n")
raise e
return parsed
def mmcif_from_block( # noqa: C901, PLR0915, PLR0912
block,
mols: Dict[str, Mol],
moldir: Optional[str] = None,
use_assembly: bool = True,
use_original_res_idx: bool = False,
) -> ParsedStructure:
"""Parse a structure in MMCIF format.
Parameters
----------
block :
Gemmi Block.
use_original_res_idx : bool
Uses the res_idx for the res_idx in the Residues in the returned structure that was in the mmcif file for each residue instead of using the index in the seqres that is obtained after aligning the seqres to the sequence of amino acids from the present residues.
Returns
-------
ParsedStructure
The parsed structure.
"""
# Disable rdkit warnings
blocker = rdBase.BlockLogs() # noqa: F841
# Extract medatadata
deposit_date, release_date, revision_date = get_dates(block)
resolution = get_resolution(block)
method = get_method(block)
temperature, ph = get_experiment_conditions(block)
# We can parse the "_entity_poly_seq" directly from the block.
# [[[index_id, mon_id], ...], [[index_id, mon_id], ...], ..]
entity_poly_seq_block_idx = block.get_index("_entity_poly_seq.entity_id")
eps_loop = block[entity_poly_seq_block_idx].loop
eps_label_id_idx = eps_loop.tags.index("_entity_poly_seq.num")
eps_entity_id_idx = eps_loop.tags.index("_entity_poly_seq.entity_id")
eps_mon_id_idx = eps_loop.tags.index("_entity_poly_seq.mon_id")
entity_poly_seq, curr_seqid_mon = {}, []
curr_entity_id = eps_loop[0, eps_entity_id_idx]
for i in range(eps_loop.length()):
entity_id = eps_loop[i, eps_entity_id_idx]
num = eps_loop[i, eps_label_id_idx]
mon_id = eps_loop[i, eps_mon_id_idx]
if entity_id != curr_entity_id:
entity_poly_seq[str(curr_entity_id)] = curr_seqid_mon
curr_entity_id = entity_id
curr_seqid_mon = []
curr_seqid_mon.append([int(num), mon_id])
entity_poly_seq[str(curr_entity_id)] = curr_seqid_mon
# Load structure object
structure = gemmi.make_structure_from_block(block)
# Clean up the structure
structure.merge_chain_parts()
structure.remove_waters()
structure.remove_hydrogens()
structure.remove_alternative_conformations()
structure.remove_empty_chains()
# Expand assembly 1
if use_assembly and structure.assemblies:
how = gemmi.HowToNameCopiedChain.AddNumber
assembly_name = structure.assemblies[0].name
structure.transform_to_assembly(assembly_name, how=how)
# Parse entities
# Create mapping from subchain id to entity
entities: Dict[str, gemmi.Entity] = {}
entity_ids: Dict[str, int] = {}
for entity_id, entity in enumerate(structure.entities):
entity: gemmi.Entity
if entity.entity_type.name == "Water":
continue
for subchain_id in entity.subchains:
entities[subchain_id] = entity
entity_ids[subchain_id] = entity_id
# Create mapping from chain, residue to subchains
# since a Connection uses the chains and not subchains
subchain_map = {}
for chain in structure[0]:
for residue in chain:
seq_id = residue.seqid
seq_id = str(seq_id.num) + str(seq_id.icode).strip()
subchain_map[(chain.name, seq_id)] = residue.subchain
# Find covalent ligands
covalent_chain_ids = compute_covalent_ligands(
connections=structure.connections,
subchain_map=subchain_map,
entities=entities,
)
# Parse chains
chains: List[ParsedChain] = []
for raw_chain in structure[0].subchains():
# Check chain type
subchain_id = raw_chain.subchain_id()
entity: gemmi.Entity = entities[subchain_id]
entity_type = entity.entity_type.name
# Parse a polymer
if entity_type == "Polymer":
# Skip PeptideD, DnaRnaHybrid, Pna, Other
if entity.polymer_type.name not in {
"PeptideL",
"Dna",
"Rna",
}:
continue
# Add polymer if successful
parsed_polymer = parse_polymer(
polymer=raw_chain,
polymer_type=entity.polymer_type,
sequence=entity.full_sequence,
chain_id=subchain_id,
entity=entity.name,
mols=mols,
moldir=moldir,
use_original_res_idx=use_original_res_idx,
entity_poly_seq=entity_poly_seq[entity.name],
)
if parsed_polymer is not None:
chains.append(parsed_polymer)
# Parse a non-polymer
elif entity_type in {"NonPolymer", "Branched"}:
# Skip UNL
if any(lig.name == "UNL" for lig in raw_chain):
continue
residues = []
for lig_idx, ligand in enumerate(raw_chain):
# Check if ligand is covalent
if entity_type == "Branched":
is_covalent = True
else:
is_covalent = subchain_id in covalent_chain_ids
ligand: gemmi.Residue
ligand_mol = get_mol(ligand.name, mols, moldir)
residue = parse_ccd_residue(
name=ligand.name,
ref_mol=ligand_mol,
res_idx=lig_idx,
gemmi_mol=ligand,
is_covalent=is_covalent,
)
residues.append(residue)
if residues:
chains.append(
ParsedChain(
name=subchain_id,
entity=entity.name,
residues=residues,
type=const.chain_type_ids["NONPOLYMER"],
)
)
# If no chains parsed fail
if not chains:
msg = "No chains parsed!"
raise ValueError(msg)
# Want to traverse subchains in same order as reference structure
ref_chain_map = {ref_chain.name: i for i, ref_chain in enumerate(chains)}
all_ensembles = [chains]
# Loop through different structures in model
for struct in list(structure)[1:]:
struct: gemmi.Model
ensemble_chains = {}
for raw_chain in struct.subchains():
# Check chain type
subchain_id = raw_chain.subchain_id()
entity: gemmi.Entity = entities[subchain_id]
entity_type = entity.entity_type.name
# Parse a polymer
if entity_type == "Polymer":
# Skip PeptideD, DnaRnaHybrid, Pna, Other
if entity.polymer_type.name not in {
"PeptideL",
"Dna",
"Rna",
}:
continue
# Add polymer if successful
parsed_polymer = parse_polymer(
polymer=raw_chain,
polymer_type=entity.polymer_type,
sequence=entity.full_sequence,
chain_id=subchain_id,
entity=entity.name,
mols=mols,
moldir=moldir,
use_original_res_idx=use_original_res_idx,
entity_poly_seq=entity_poly_seq[entity.name],
)
if parsed_polymer is not None:
ensemble_chains[ref_chain_map[subchain_id]] = parsed_polymer
# Parse a non-polymer
elif entity_type in {"NonPolymer", "Branched"}:
# Skip UNL
if any(lig.name == "UNL" for lig in raw_chain):
continue
residues = []
for lig_idx, ligand in enumerate(raw_chain):
# Check if ligand is covalent
if entity_type == "Branched":
is_covalent = True
else:
is_covalent = subchain_id in covalent_chain_ids
ligand: gemmi.Residue
ligand_mol = get_mol(ligand.name, mols, moldir)
residue = parse_ccd_residue(
name=ligand.name,
ref_mol=ligand_mol,
res_idx=lig_idx,
gemmi_mol=ligand,
is_covalent=is_covalent,
)
residues.append(residue)
if residues:
parsed_non_polymer = ParsedChain(
name=subchain_id,
entity=entity.name,
residues=residues,
type=const.chain_type_ids["NONPOLYMER"],
)
ensemble_chains[ref_chain_map[subchain_id]] = parsed_non_polymer
# Ensure ensemble chains are in the same order as reference structure
ensemble_chains = [ensemble_chains[idx] for idx in range(len(ensemble_chains))]
all_ensembles.append(ensemble_chains)
# Parse covalent connections
connections: List[ParsedConnection] = []
for connection in structure.connections:
# Skip non-covalent connections
connection: gemmi.Connection
if connection.type.name not in {"Covale", "Disulf"}:
continue
try:
parsed_connection = parse_connection(
connection=connection,
chains=chains,
subchain_map=subchain_map,
)
except Exception: # noqa: S112, BLE001
continue
connections.append(parsed_connection)
# Create tables
atom_data = []
bond_data = []
res_data = []
chain_data = []
ensemble_data = []
coords_data = defaultdict(list)
# Convert parsed chains to tables
atom_idx = 0
res_idx = 0
sym_count = {}
chain_to_idx = {}
res_to_idx = {}
chain_to_seq = {}
for asym_id, chain in enumerate(chains):
# Compute number of atoms and residues
res_num = len(chain.residues)
atom_num = sum(len(res.atoms) for res in chain.residues)
# Get same chain across models in ensemble
ensemble_chains = [ensemble[asym_id] for ensemble in all_ensembles]
assert len(ensemble_chains) == len(all_ensembles)
for ensemble_chain in ensemble_chains:
assert len(ensemble_chain.residues) == res_num
assert sum(len(res.atoms) for res in ensemble_chain.residues) == atom_num
# Find all copies of this chain in the assembly
entity_id = entity_ids[chain.name]
sym_id = sym_count.get(entity_id, 0)
chain_data.append(
(
chain.name,
chain.type,
entity_id,
sym_id,
asym_id,
atom_idx,
atom_num,
res_idx,
res_num,
0, # cyclic period
0, # symmetric_group (default, can be overridden via YAML)
)
)
chain_to_idx[chain.name] = asym_id
sym_count[entity_id] = sym_id + 1
if chain.sequence is not None:
chain_to_seq[chain.name] = chain.sequence
# Add residue, atom, bond, data
for i, res in enumerate(chain.residues):
# Get same residue across models in ensemble
ensemble_residues = [
ensemble_chain.residues[i] for ensemble_chain in ensemble_chains
]
assert len(ensemble_residues) == len(all_ensembles)
for ensemble_res in ensemble_residues:
assert ensemble_res.name == res.name
atom_center = atom_idx + res.atom_center
atom_disto = atom_idx + res.atom_disto
res_data.append(
(
res.name,
res.type,
res.idx,
atom_idx,
len(res.atoms),
atom_center,
atom_disto,
res.is_standard,
res.is_present,
)
)
res_to_idx[(chain.name, i)] = (res_idx, atom_idx)
for bond in res.bonds:
chain_1 = asym_id
chain_2 = asym_id
res_1 = res_idx
res_2 = res_idx
atom_1 = atom_idx + bond.atom_1
atom_2 = atom_idx + bond.atom_2
bond_data.append(
(
chain_1,
chain_2,
res_1,
res_2,
atom_1,
atom_2,
bond.type,
)
)
for a_idx, atom in enumerate(res.atoms):
# Get same atom across models in ensemble
ensemble_atoms = [
ensemble_res.atoms[a_idx] for ensemble_res in ensemble_residues
]
assert len(ensemble_atoms) == len(all_ensembles)
for e_idx, ensemble_atom in enumerate(ensemble_atoms):
assert ensemble_atom.name == atom.name
assert atom.is_present == ensemble_atom.is_present
coords_data[e_idx].append(ensemble_atom.coords)
atom_data.append(
(
atom.name,
atom.coords,
atom.is_present,
atom.bfactor,
1.0, # plddt is 1 for real data
)
)
atom_idx += 1
res_idx += 1
# Create coordinates table
coords_data_ = []
for e_idx in range(len(coords_data)):
ensemble_data.append((e_idx * atom_idx, atom_idx))
coords_data_.append(coords_data[e_idx])
coords_data = [(x,) for xs in coords_data_ for x in xs]
# Convert connections to tables
for conn in connections:
chain_1_idx = chain_to_idx[conn.chain_1]
chain_2_idx = chain_to_idx[conn.chain_2]
res_1_idx, atom_1_offset = res_to_idx[(conn.chain_1, conn.residue_index_1)]
res_2_idx, atom_2_offset = res_to_idx[(conn.chain_2, conn.residue_index_2)]
atom_1_idx = atom_1_offset + conn.atom_index_1
atom_2_idx = atom_2_offset + conn.atom_index_2
bond_data.append(
(
chain_1_idx,
chain_2_idx,
res_1_idx,
res_2_idx,
atom_1_idx,
atom_2_idx,
const.bond_type_ids["COVALENT"],
)
)
if (
conn.chain_1 == conn.chain_2
and conn.residue_index_1 == 0
and conn.residue_index_2
== len(chains[chain_to_idx[conn.chain_1]].residues) - 1
) or (
conn.chain_1 == conn.chain_2
and conn.residue_index_1
== len(chains[chain_to_idx[conn.chain_1]].residues) - 1
and conn.residue_index_2 == 0
):
if atom_data[atom_1_idx][0] == "SG" and atom_data[atom_2_idx][0] == "SG":
continue
temp = list(chain_data[chain_1_idx])
temp[9] = len(chains[chain_to_idx[conn.chain_1]].residues)
chain_data[chain_1_idx] = tuple(temp)
# Convert into datatypes
atoms = np.array(atom_data, dtype=Atom)
bonds = np.array(bond_data, dtype=Bond)
residues = np.array(res_data, dtype=Residue)
chains = np.array(chain_data, dtype=Chain)
mask = np.ones(len(chain_data), dtype=bool)
ensemble = np.array(ensemble_data, dtype=Ensemble)
coords = np.array(coords_data, dtype=Coords)
interfaces = np.array([], dtype=Interface)
# Return parsed structure
info = StructureInfo(
deposited=deposit_date,
revised=revision_date,
released=release_date,
resolution=resolution,
method=method,
num_chains=len(chains),
num_interfaces=len(interfaces),
temperature=temperature,
pH=ph,
)
data = Structure(
atoms=atoms,
bonds=bonds,
residues=residues,
chains=chains,
interfaces=interfaces,
mask=mask,
ensemble=ensemble,
coords=coords,
)
return ParsedStructure(
data=data,
info=info,
sequences=chain_to_seq,
)
def compute_3d(mol: Mol, version: str = "v3") -> bool:
"""Generate 3D coordinates using EKTDG method.
Taken from `pdbeccdutils.core.component.Component`.
Parameters
----------
mol: Mol
The RDKit molecule to process
version: str, optional
The ETKDG version, defaults ot v3
Returns
-------
bool
Whether computation was successful.
"""
if version == "v3":
options = rdkit.Chem.AllChem.ETKDGv3()
elif version == "v2":
options = rdkit.Chem.AllChem.ETKDGv2()
else:
options = rdkit.Chem.AllChem.ETKDGv2()
options.clearConfs = False
conf_id = -1
try:
conf_id = rdkit.Chem.AllChem.EmbedMolecule(mol, options)
rdkit.Chem.AllChem.UFFOptimizeMolecule(mol, confId=conf_id, maxIters=1000)
except RuntimeError:
pass # Force field issue here
except ValueError:
pass # sanitization issue here
if conf_id != -1:
conformer = mol.GetConformer(conf_id)
conformer.SetProp("name", ConformerType.Computed.name)
conformer.SetProp("coord_generation", f"ETKDG{version}")
return True
return False
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