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