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, rotable_bonds, conf_id): opt_mol = copy.copy(mol) [SetDihedral(opt_mol.GetConformer(conf_id), rotable_bonds[r], values[r]) for r in range(len(rotable_bonds))] return opt_mol def optimize_rotatable_bonds(mol, true_mol, rotable_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, rotable_bonds, seed=seed, probe_id=probe_id, ref_id=ref_id) max_bound = [np.pi] * len(opt.rotable_bonds) min_bound = [-np.pi] * len(opt.rotable_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.rotable_bonds, conf_id=probe_id) return opt_mol class OptimizeConformer: def __init__(self, mol, true_mol, rotable_bonds, probe_id=-1, ref_id=-1, seed=None): super(OptimizeConformer, self).__init__() if seed: np.random.seed(seed) self.rotable_bonds = rotable_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.rotable_bonds): SetDihedral(self.mol.GetConformer(self.probe_id), r, values[i]) return RMSD(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 # GeoMol def get_torsions(mol_list): print('USING GEOMOL GET TORSIONS FUNCTION') atom_counter = 0 torsionList = [] for m in mol_list: torsionSmarts = '[!$(*#*)&!D1]-&!@[!$(*#*)&!D1]' torsionQuery = Chem.MolFromSmarts(torsionSmarts) matches = m.GetSubstructMatches(torsionQuery) for match in matches: idx2 = match[0] idx3 = match[1] bond = m.GetBondBetweenAtoms(idx2, idx3) jAtom = m.GetAtomWithIdx(idx2) kAtom = m.GetAtomWithIdx(idx3) for b1 in jAtom.GetBonds(): if (b1.GetIdx() == bond.GetIdx()): continue idx1 = b1.GetOtherAtomIdx(idx2) for b2 in kAtom.GetBonds(): if ((b2.GetIdx() == bond.GetIdx()) or (b2.GetIdx() == b1.GetIdx())): continue idx4 = b2.GetOtherAtomIdx(idx3) # skip 3-membered rings if (idx4 == idx1): continue if m.GetAtomWithIdx(idx4).IsInRing(): torsionList.append( (idx4 + atom_counter, idx3 + atom_counter, idx2 + atom_counter, idx1 + atom_counter)) break else: torsionList.append( (idx1 + atom_counter, idx2 + atom_counter, idx3 + atom_counter, idx4 + atom_counter)) break break atom_counter += m.GetNumAtoms() return torsionList def A_transpose_matrix(alpha): return np.array([[np.cos(alpha), np.sin(alpha)], [-np.sin(alpha), np.cos(alpha)]], dtype=np.double) def S_vec(alpha): return np.array([[np.cos(alpha)], [np.sin(alpha)]], dtype=np.double) def GetDihedralFromPointCloud(Z, atom_idx): p = Z[list(atom_idx)] b = p[:-1] - p[1:] b[0] *= -1 v = np.array([v - (v.dot(b[1]) / b[1].dot(b[1])) * b[1] for v in [b[0], b[2]]]) # Normalize vectors v /= np.sqrt(np.einsum('...i,...i', v, v)).reshape(-1, 1) b1 = b[1] / np.linalg.norm(b[1]) x = np.dot(v[0], v[1]) m = np.cross(v[0], b1) y = np.dot(m, v[1]) return np.arctan2(y, x) def get_dihedral_vonMises(mol, conf, atom_idx, Z): Z = np.array(Z) v = np.zeros((2, 1)) iAtom = mol.GetAtomWithIdx(atom_idx[1]) jAtom = mol.GetAtomWithIdx(atom_idx[2]) k_0 = atom_idx[0] i = atom_idx[1] j = atom_idx[2] l_0 = atom_idx[3] for b1 in iAtom.GetBonds(): k = b1.GetOtherAtomIdx(i) if k == j: continue for b2 in jAtom.GetBonds(): l = b2.GetOtherAtomIdx(j) if l == i: continue assert k != l s_star = S_vec(GetDihedralFromPointCloud(Z, (k, i, j, l))) a_mat = A_transpose_matrix(GetDihedral(conf, (k, i, j, k_0)) + GetDihedral(conf, (l_0, i, j, l))) v = v + np.matmul(a_mat, s_star) v = v / np.linalg.norm(v) v = v.reshape(-1) return np.arctan2(v[1], v[0]) def get_von_mises_rms(mol, mol_rdkit, rotable_bonds, conf_id): new_dihedrals = np.zeros(len(rotable_bonds)) for idx, r in enumerate(rotable_bonds): new_dihedrals[idx] = get_dihedral_vonMises(mol_rdkit, mol_rdkit.GetConformer(conf_id), r, mol.GetConformer().GetPositions()) mol_rdkit = apply_changes(mol_rdkit, new_dihedrals, rotable_bonds, conf_id) return RMSD(mol_rdkit, mol, conf_id) def mmff_func(mol): mol_mmff = copy.deepcopy(mol) AllChem.MMFFOptimizeMoleculeConfs(mol_mmff, mmffVariant='MMFF94s') for i in range(mol.GetNumConformers()): coords = mol_mmff.GetConformers()[i].GetPositions() for j in range(coords.shape[0]): mol.GetConformer(i).SetAtomPosition(j, Geometry.Point3D(*coords[j])) RMSD = AllChem.AlignMol