def testTorsionFingerprintsColinearBonds(self):
# test that single bonds adjacent to triple bonds are ignored
mol = Chem.MolFromSmiles('CCC#CCC')
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(mol,
ignoreColinearBonds=True)
self.assertEqual(len(tors_list), 0)
weights = TorsionFingerprints.CalculateTorsionWeights(mol, ignoreColinearBonds=True)
self.assertEqual(len(weights), 0)
# test that they are not ignored, but alternative atoms searched for
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(
mol, ignoreColinearBonds=False)
self.assertEqual(len(tors_list), 1)
self.assertEqual(tors_list[0][0][0], (0, 1, 4, 5))
weights = TorsionFingerprints.CalculateTorsionWeights(mol, ignoreColinearBonds=False)
self.assertEqual(len(weights), 1)
# test that single bonds adjacent to terminal triple bonds are always ignored
mol = Chem.MolFromSmiles('C#CCC')
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(mol,
ignoreColinearBonds=True)
self.assertEqual(len(tors_list), 0)
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(
mol, ignoreColinearBonds=False)
self.assertEqual(len(tors_list), 0)
def testTorsionFingerprints(self):
# we use the xray structure from the paper (JCIM, 52, 1499, 2012): 1DWD
refFile = os.path.join(RDConfig.RDCodeDir, 'Chem', 'test_data', '1DWD_ligand.pdb')
ref = Chem.MolFromSmiles(
'NC(=[NH2+])c1ccc(C[C@@H](NC(=O)CNS(=O)(=O)c2ccc3ccccc3c2)C(=O)N2CCCCC2)cc1')
mol = Chem.MolFromPDBFile(refFile)
mol = AllChem.AssignBondOrdersFromTemplate(ref, mol)
# the torsion lists
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(mol)
self.assertEqual(len(tors_list), 11)
self.assertEqual(len(tors_list_rings), 4)
self.assertAlmostEqual(tors_list[-1][1], 180.0, 4)
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(mol, maxDev='spec')
self.assertAlmostEqual(tors_list[-1][1], 90.0, 4)
self.assertRaises(ValueError, TorsionFingerprints.CalculateTorsionLists, mol, maxDev='test')
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(mol, symmRadius=0)
self.assertEqual(len(tors_list[0][0]), 2)
# the weights
weights = TorsionFingerprints.CalculateTorsionWeights(mol)
self.assertAlmostEqual(weights[4], 1.0)
self.assertEqual(len(weights), len(tors_list + tors_list_rings))
weights = TorsionFingerprints.CalculateTorsionWeights(mol, 15, 14)
self.assertAlmostEqual(weights[3], 1.0)
self.assertRaises(ValueError, TorsionFingerprints.CalculateTorsionWeights, mol, 15, 3)
# the torsion angles
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(mol)
torsions = TorsionFingerprints.CalculateTorsionAngles(mol, tors_list, tors_list_rings)
self.assertEqual(len(weights), len(torsions))
self.assertAlmostEqual(torsions[2][0][0], 232.5346, 4)
# the torsion fingerprint deviation
tfd = TorsionFingerprints.CalculateTFD(torsions, torsions)
self.assertAlmostEqual(tfd, 0.0)
refFile = os.path.join(RDConfig.RDCodeDir, 'Chem', 'test_data', '1PPC_ligand.pdb')
mol2 = Chem.MolFromPDBFile(refFile)
mol2 = AllChem.AssignBondOrdersFromTemplate(ref, mol2)
torsions2 = TorsionFingerprints.CalculateTorsionAngles(mol2, tors_list, tors_list_rings)
weights = TorsionFingerprints.CalculateTorsionWeights(mol)
tfd = TorsionFingerprints.CalculateTFD(torsions, torsions2, weights=weights)
self.assertAlmostEqual(tfd, 0.0691, 4)
tfd = TorsionFingerprints.CalculateTFD(torsions, torsions2)
self.assertAlmostEqual(tfd, 0.1115, 4)
# the wrapper functions
tfd = TorsionFingerprints.GetTFDBetweenMolecules(mol, mol2)
self.assertAlmostEqual(tfd, 0.0691, 4)
mol.AddConformer(mol2.GetConformer(), assignId=True)
mol.AddConformer(mol2.GetConformer(), assignId=True)
tfd = TorsionFingerprints.GetTFDBetweenConformers(mol, confIds1=[0], confIds2=[1, 2])
self.assertEqual(len(tfd), 2)
self.assertAlmostEqual(tfd[0], 0.0691, 4)
tfdmat = TorsionFingerprints.GetTFDMatrix(mol)
self.assertEqual(len(tfdmat), 3)
def __init__(self, mol_config: MolConfig, max_steps=200):
super(ConformerEnv, self).__init__()
logging.info('initializing conformer environment')
self.config = copy.deepcopy(mol_config)
self.max_steps = max_steps
self.total_reward = 0
self.current_step = 0
self.step_info = {}
self.episode_info = {}
self.mol = self.config.mol
# set mol to have exactly one conformer
if self.mol.GetNumConformers() != 1:
logging.warn(
"Input molecule to environment should have exactly one conformer, none or more than one detected."
)
self.mol.RemoveAllConformers()
if Chem.EmbedMolecule(self.mol,
randomSeed=self.config.seed,
useRandomCoords=True) == -1:
raise Exception(
'Unable to embed molecule with conformer using rdkit')
self.conf = self.mol.GetConformer()
nonring, ring = TorsionFingerprints.CalculateTorsionLists(self.mol)
self.nonring = [list(atoms[0]) for atoms, ang in nonring]
self.reset()
def testGithub4720(self):
# exceptions with highly-coordinated atoms
mol = Chem.MolFromSmiles('S(F)(F)(F)(F)(Cl)c1ccccc1')
tors_list, tors_list_rings = TorsionFingerprints.CalculateTorsionLists(
mol)
self.assertEqual(len(tors_list), 1)
def calculate(self, mol):
yield tuple(
Torsion(*mol.get_atoms(atoms[0])) for atoms, _ in
(TorsionFingerprints.CalculateTorsionLists(mol.to_rdkit_mol())[0]))
