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import copy, time |
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import numpy as np |
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from collections import defaultdict |
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from rdkit import Chem, RDLogger |
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from rdkit.Chem import AllChem, rdMolTransforms |
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from rdkit import Geometry |
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import networkx as nx |
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from scipy.optimize import differential_evolution |
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RDLogger.DisableLog('rdApp.*') |
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""" |
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Conformer matching routines from Torsional Diffusion |
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""" |
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def GetDihedral(conf, atom_idx): |
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return rdMolTransforms.GetDihedralRad(conf, atom_idx[0], atom_idx[1], atom_idx[2], atom_idx[3]) |
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def SetDihedral(conf, atom_idx, new_vale): |
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rdMolTransforms.SetDihedralRad(conf, atom_idx[0], atom_idx[1], atom_idx[2], atom_idx[3], new_vale) |
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def apply_changes(mol, values, rotable_bonds, conf_id): |
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opt_mol = copy.copy(mol) |
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[SetDihedral(opt_mol.GetConformer(conf_id), rotable_bonds[r], values[r]) for r in range(len(rotable_bonds))] |
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return opt_mol |
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def optimize_rotatable_bonds(mol, true_mol, rotable_bonds, probe_id=-1, ref_id=-1, seed=0, popsize=15, maxiter=500, |
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mutation=(0.5, 1), recombination=0.8): |
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opt = OptimizeConformer(mol, true_mol, rotable_bonds, seed=seed, probe_id=probe_id, ref_id=ref_id) |
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max_bound = [np.pi] * len(opt.rotable_bonds) |
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min_bound = [-np.pi] * len(opt.rotable_bonds) |
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bounds = (min_bound, max_bound) |
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bounds = list(zip(bounds[0], bounds[1])) |
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result = differential_evolution(opt.score_conformation, bounds, |
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maxiter=maxiter, popsize=popsize, |
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mutation=mutation, recombination=recombination, disp=False, seed=seed) |
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opt_mol = apply_changes(opt.mol, result['x'], opt.rotable_bonds, conf_id=probe_id) |
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return opt_mol |
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class OptimizeConformer: |
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def __init__(self, mol, true_mol, rotable_bonds, probe_id=-1, ref_id=-1, seed=None): |
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super(OptimizeConformer, self).__init__() |
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if seed: |
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np.random.seed(seed) |
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self.rotable_bonds = rotable_bonds |
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self.mol = mol |
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self.true_mol = true_mol |
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self.probe_id = probe_id |
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self.ref_id = ref_id |
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def score_conformation(self, values): |
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for i, r in enumerate(self.rotable_bonds): |
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SetDihedral(self.mol.GetConformer(self.probe_id), r, values[i]) |
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return RMSD(self.mol, self.true_mol, self.probe_id, self.ref_id) |
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def get_torsion_angles(mol): |
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torsions_list = [] |
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G = nx.Graph() |
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for i, atom in enumerate(mol.GetAtoms()): |
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G.add_node(i) |
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nodes = set(G.nodes()) |
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for bond in mol.GetBonds(): |
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start, end = bond.GetBeginAtomIdx(), bond.GetEndAtomIdx() |
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G.add_edge(start, end) |
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for e in G.edges(): |
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G2 = copy.deepcopy(G) |
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G2.remove_edge(*e) |
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if nx.is_connected(G2): continue |
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l = list(sorted(nx.connected_components(G2), key=len)[0]) |
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if len(l) < 2: continue |
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n0 = list(G2.neighbors(e[0])) |
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n1 = list(G2.neighbors(e[1])) |
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torsions_list.append( |
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(n0[0], e[0], e[1], n1[0]) |
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) |
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return torsions_list |
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def get_torsions(mol_list): |
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print('USING GEOMOL GET TORSIONS FUNCTION') |
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atom_counter = 0 |
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torsionList = [] |
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for m in mol_list: |
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torsionSmarts = '[!$(*#*)&!D1]-&!@[!$(*#*)&!D1]' |
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torsionQuery = Chem.MolFromSmarts(torsionSmarts) |
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matches = m.GetSubstructMatches(torsionQuery) |
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for match in matches: |
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idx2 = match[0] |
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idx3 = match[1] |
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bond = m.GetBondBetweenAtoms(idx2, idx3) |
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jAtom = m.GetAtomWithIdx(idx2) |
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kAtom = m.GetAtomWithIdx(idx3) |
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for b1 in jAtom.GetBonds(): |
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if (b1.GetIdx() == bond.GetIdx()): |
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continue |
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idx1 = b1.GetOtherAtomIdx(idx2) |
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for b2 in kAtom.GetBonds(): |
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if ((b2.GetIdx() == bond.GetIdx()) |
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or (b2.GetIdx() == b1.GetIdx())): |
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continue |
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idx4 = b2.GetOtherAtomIdx(idx3) |
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if (idx4 == idx1): |
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continue |
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if m.GetAtomWithIdx(idx4).IsInRing(): |
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torsionList.append( |
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(idx4 + atom_counter, idx3 + atom_counter, idx2 + atom_counter, idx1 + atom_counter)) |
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break |
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else: |
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torsionList.append( |
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(idx1 + atom_counter, idx2 + atom_counter, idx3 + atom_counter, idx4 + atom_counter)) |
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break |
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break |
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atom_counter += m.GetNumAtoms() |
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return torsionList |
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def A_transpose_matrix(alpha): |
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return np.array([[np.cos(alpha), np.sin(alpha)], [-np.sin(alpha), np.cos(alpha)]], dtype=np.double) |
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def S_vec(alpha): |
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return np.array([[np.cos(alpha)], [np.sin(alpha)]], dtype=np.double) |
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def GetDihedralFromPointCloud(Z, atom_idx): |
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p = Z[list(atom_idx)] |
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b = p[:-1] - p[1:] |
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b[0] *= -1 |
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v = np.array([v - (v.dot(b[1]) / b[1].dot(b[1])) * b[1] for v in [b[0], b[2]]]) |
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v /= np.sqrt(np.einsum('...i,...i', v, v)).reshape(-1, 1) |
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b1 = b[1] / np.linalg.norm(b[1]) |
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x = np.dot(v[0], v[1]) |
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m = np.cross(v[0], b1) |
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y = np.dot(m, v[1]) |
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return np.arctan2(y, x) |
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def get_dihedral_vonMises(mol, conf, atom_idx, Z): |
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Z = np.array(Z) |
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v = np.zeros((2, 1)) |
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iAtom = mol.GetAtomWithIdx(atom_idx[1]) |
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jAtom = mol.GetAtomWithIdx(atom_idx[2]) |
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k_0 = atom_idx[0] |
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i = atom_idx[1] |
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j = atom_idx[2] |
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l_0 = atom_idx[3] |
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for b1 in iAtom.GetBonds(): |
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k = b1.GetOtherAtomIdx(i) |
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if k == j: |
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continue |
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for b2 in jAtom.GetBonds(): |
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l = b2.GetOtherAtomIdx(j) |
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if l == i: |
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continue |
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assert k != l |
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s_star = S_vec(GetDihedralFromPointCloud(Z, (k, i, j, l))) |
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a_mat = A_transpose_matrix(GetDihedral(conf, (k, i, j, k_0)) + GetDihedral(conf, (l_0, i, j, l))) |
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v = v + np.matmul(a_mat, s_star) |
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v = v / np.linalg.norm(v) |
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v = v.reshape(-1) |
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return np.arctan2(v[1], v[0]) |
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def get_von_mises_rms(mol, mol_rdkit, rotable_bonds, conf_id): |
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new_dihedrals = np.zeros(len(rotable_bonds)) |
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for idx, r in enumerate(rotable_bonds): |
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new_dihedrals[idx] = get_dihedral_vonMises(mol_rdkit, |
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mol_rdkit.GetConformer(conf_id), r, |
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mol.GetConformer().GetPositions()) |
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mol_rdkit = apply_changes(mol_rdkit, new_dihedrals, rotable_bonds, conf_id) |
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return RMSD(mol_rdkit, mol, conf_id) |
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def mmff_func(mol): |
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mol_mmff = copy.deepcopy(mol) |
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AllChem.MMFFOptimizeMoleculeConfs(mol_mmff, mmffVariant='MMFF94s') |
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for i in range(mol.GetNumConformers()): |
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coords = mol_mmff.GetConformers()[i].GetPositions() |
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for j in range(coords.shape[0]): |
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mol.GetConformer(i).SetAtomPosition(j, |
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Geometry.Point3D(*coords[j])) |
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RMSD = AllChem.AlignMol |
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