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| import copy, time | |
| import numpy as np | |
| from collections import defaultdict | |
| from rdkit import Chem, RDLogger | |
| from rdkit.Chem import AllChem, rdMolTransforms | |
| from rdkit import Geometry | |
| import networkx as nx | |
| from scipy.optimize import differential_evolution | |
| RDLogger.DisableLog('rdApp.*') | |
| """ | |
| Conformer matching routines from Torsional Diffusion | |
| """ | |
| def GetDihedral(conf, atom_idx): | |
| return rdMolTransforms.GetDihedralRad(conf, atom_idx[0], atom_idx[1], atom_idx[2], atom_idx[3]) | |
| def SetDihedral(conf, atom_idx, new_vale): | |
| rdMolTransforms.SetDihedralRad(conf, atom_idx[0], atom_idx[1], atom_idx[2], atom_idx[3], new_vale) | |
| def apply_changes(mol, values, rotatable_bonds, conf_id): | |
| opt_mol = copy.copy(mol) | |
| [SetDihedral(opt_mol.GetConformer(conf_id), rotatable_bonds[r], values[r]) for r in range(len(rotatable_bonds))] | |
| return opt_mol | |
| def optimize_rotatable_bonds(mol, true_mol, rotatable_bonds, probe_id=-1, ref_id=-1, seed=0, popsize=15, maxiter=500, | |
| mutation=(0.5, 1), recombination=0.8): | |
| opt = OptimizeConformer(mol, true_mol, rotatable_bonds, seed=seed, probe_id=probe_id, ref_id=ref_id) | |
| max_bound = [np.pi] * len(opt.rotatable_bonds) | |
| min_bound = [-np.pi] * len(opt.rotatable_bonds) | |
| bounds = (min_bound, max_bound) | |
| bounds = list(zip(bounds[0], bounds[1])) | |
| # Optimize conformations | |
| result = differential_evolution(opt.score_conformation, bounds, | |
| maxiter=maxiter, popsize=popsize, | |
| mutation=mutation, recombination=recombination, disp=False, seed=seed) | |
| opt_mol = apply_changes(opt.mol, result['x'], opt.rotatable_bonds, conf_id=probe_id) | |
| return opt_mol | |
| class OptimizeConformer: | |
| def __init__(self, mol, true_mol, rotatable_bonds, probe_id=-1, ref_id=-1, seed=None): | |
| super(OptimizeConformer, self).__init__() | |
| if seed: | |
| np.random.seed(seed) | |
| self.rotatable_bonds = rotatable_bonds | |
| self.mol = mol | |
| self.true_mol = true_mol | |
| self.probe_id = probe_id | |
| self.ref_id = ref_id | |
| def score_conformation(self, values): | |
| for i, r in enumerate(self.rotatable_bonds): | |
| SetDihedral(self.mol.GetConformer(self.probe_id), r, values[i]) | |
| return AllChem.AlignMol(self.mol, self.true_mol, self.probe_id, self.ref_id) | |
| def get_torsion_angles(mol): | |
| torsions_list = [] | |
| G = nx.Graph() | |
| for i, atom in enumerate(mol.GetAtoms()): | |
| G.add_node(i) | |
| nodes = set(G.nodes()) | |
| for bond in mol.GetBonds(): | |
| start, end = bond.GetBeginAtomIdx(), bond.GetEndAtomIdx() | |
| G.add_edge(start, end) | |
| for e in G.edges(): | |
| G2 = copy.deepcopy(G) | |
| G2.remove_edge(*e) | |
| if nx.is_connected(G2): continue | |
| l = list(sorted(nx.connected_components(G2), key=len)[0]) | |
| if len(l) < 2: continue | |
| n0 = list(G2.neighbors(e[0])) | |
| n1 = list(G2.neighbors(e[1])) | |
| torsions_list.append( | |
| (n0[0], e[0], e[1], n1[0]) | |
| ) | |
| return torsions_list | |