# # Copyright (C) 2006-2017 greg Landrum and Rational Discovery LLC # # @@ All Rights Reserved @@ # This file is part of the RDKit. # The contents are covered by the terms of the BSD license # which is included in the file license.txt, found at the root # of the RDKit source tree. # """ Import all RDKit chemistry modules """ import sys import warnings from collections import namedtuple import numpy from rdkit import DataStructs from rdkit import ForceField from rdkit import RDConfig from rdkit import rdBase from rdkit.Chem import * from rdkit.Chem.ChemicalFeatures import * from rdkit.Chem.rdChemReactions import * from rdkit.Chem.rdDepictor import * from rdkit.Chem.rdDistGeom import * from rdkit.Chem.rdForceFieldHelpers import * from rdkit.Chem.rdMolAlign import * from rdkit.Chem.rdMolDescriptors import * from rdkit.Chem.rdMolTransforms import * from rdkit.Chem.rdPartialCharges import * from rdkit.Chem.rdReducedGraphs import * from rdkit.Chem.rdShapeHelpers import * from rdkit.Chem.rdqueries import * from rdkit.Chem.rdMolEnumerator import * from rdkit.Geometry import rdGeometry from rdkit.RDLogger import logger from rdkit.Chem.EnumerateStereoisomers import StereoEnumerationOptions, EnumerateStereoisomers try: from rdkit.Chem.rdSLNParse import * except ImportError: pass Mol.Compute2DCoords = Compute2DCoords Mol.ComputeGasteigerCharges = ComputeGasteigerCharges logger = logger() def TransformMol(mol, tform, confId=-1, keepConfs=False): """ Applies the transformation (usually a 4x4 double matrix) to a molecule if keepConfs is False then all but that conformer are removed """ refConf = mol.GetConformer(confId) TransformConformer(refConf, tform) if not keepConfs: if confId == -1: confId = 0 allConfIds = [c.GetId() for c in mol.GetConformers()] for cid in allConfIds: if not cid == confId: mol.RemoveConformer(cid) # reset the conf Id to zero since there is only one conformer left mol.GetConformer(confId).SetId(0) def ComputeMolShape(mol, confId=-1, boxDim=(20, 20, 20), spacing=0.5, **kwargs): """ returns a grid representation of the molecule's shape """ res = rdGeometry.UniformGrid3D(boxDim[0], boxDim[1], boxDim[2], spacing=spacing) EncodeShape(mol, res, confId, **kwargs) return res def ComputeMolVolume(mol, confId=-1, gridSpacing=0.2, boxMargin=2.0): """ Calculates the volume of a particular conformer of a molecule based on a grid-encoding of the molecular shape. A bit of demo as well as a test of github #1883: >>> from rdkit import Chem >>> from rdkit.Chem import AllChem >>> mol = Chem.AddHs(Chem.MolFromSmiles('C')) >>> AllChem.EmbedMolecule(mol) 0 >>> ComputeMolVolume(mol) 28... >>> mol = Chem.AddHs(Chem.MolFromSmiles('O')) >>> AllChem.EmbedMolecule(mol) 0 >>> ComputeMolVolume(mol) 20... """ mol = rdchem.Mol(mol) conf = mol.GetConformer(confId) CanonicalizeConformer(conf, ignoreHs=False) box = ComputeConfBox(conf) sideLen = (box[1].x - box[0].x + 2 * boxMargin, box[1].y - box[0].y + 2 * boxMargin, box[1].z - box[0].z + 2 * boxMargin) shape = rdGeometry.UniformGrid3D(sideLen[0], sideLen[1], sideLen[2], spacing=gridSpacing) EncodeShape(mol, shape, confId, ignoreHs=False, vdwScale=1.0) voxelVol = gridSpacing**3 occVect = shape.GetOccupancyVect() voxels = [1 for x in occVect if x == 3] vol = voxelVol * len(voxels) return vol def GetConformerRMS(mol, confId1, confId2, atomIds=None, prealigned=False): """ Returns the RMS between two conformations. By default, the conformers will be aligned to the first conformer before the RMS calculation and, as a side-effect, the second will be left in the aligned state. Arguments: - mol: the molecule - confId1: the id of the first conformer - confId2: the id of the second conformer - atomIds: (optional) list of atom ids to use a points for alingment - defaults to all atoms - prealigned: (optional) by default the conformers are assumed be unaligned and the second conformer be aligned to the first """ # align the conformers if necessary # Note: the reference conformer is always the first one if not prealigned: if atomIds: AlignMolConformers(mol, confIds=[confId1, confId2], atomIds=atomIds) else: AlignMolConformers(mol, confIds=[confId1, confId2]) # calculate the RMS between the two conformations conf1 = mol.GetConformer(id=confId1) conf2 = mol.GetConformer(id=confId2) ssr = 0 for i in range(mol.GetNumAtoms()): d = conf1.GetAtomPosition(i).Distance(conf2.GetAtomPosition(i)) ssr += d * d ssr /= mol.GetNumAtoms() return numpy.sqrt(ssr) def GetConformerRMSMatrix(mol, atomIds=None, prealigned=False): """ Returns the RMS matrix of the conformers of a molecule. As a side-effect, the conformers will be aligned to the first conformer (i.e. the reference) and will left in the aligned state. Arguments: - mol: the molecule - atomIds: (optional) list of atom ids to use a points for alingment - defaults to all atoms - prealigned: (optional) by default the conformers are assumed be unaligned and will therefore be aligned to the first conformer Note that the returned RMS matrix is symmetrical, i.e. it is the lower half of the matrix, e.g. for 5 conformers:: rmsmatrix = [ a, b, c, d, e, f, g, h, i, j] where a is the RMS between conformers 0 and 1, b is the RMS between conformers 0 and 2, etc. This way it can be directly used as distance matrix in e.g. Butina clustering. """ # if necessary, align the conformers # Note: the reference conformer is always the first one rmsvals = [] confIds = [conf.GetId() for conf in mol.GetConformers()] if not prealigned: if atomIds: AlignMolConformers(mol, atomIds=atomIds, RMSlist=rmsvals) else: AlignMolConformers(mol, RMSlist=rmsvals) else: # already prealigned for i in range(1, len(confIds)): rmsvals.append( GetConformerRMS(mol, confIds[0], confIds[i], atomIds=atomIds, prealigned=prealigned)) # loop over the conformations (except the reference one) cmat = [] for i in range(1, len(confIds)): cmat.append(rmsvals[i - 1]) for j in range(1, i): cmat.append(GetConformerRMS(mol, confIds[i], confIds[j], atomIds=atomIds, prealigned=True)) return cmat def EnumerateLibraryFromReaction(reaction, sidechainSets, returnReactants=False): """ Returns a generator for the virtual library defined by a reaction and a sequence of sidechain sets >>> from rdkit import Chem >>> from rdkit.Chem import AllChem >>> s1=[Chem.MolFromSmiles(x) for x in ('NC','NCC')] >>> s2=[Chem.MolFromSmiles(x) for x in ('OC=O','OC(=O)C')] >>> rxn = AllChem.ReactionFromSmarts('[O:2]=[C:1][OH].[N:3]>>[O:2]=[C:1][N:3]') >>> r = AllChem.EnumerateLibraryFromReaction(rxn,[s2,s1]) >>> [Chem.MolToSmiles(x[0]) for x in list(r)] ['CNC=O', 'CCNC=O', 'CNC(C)=O', 'CCNC(C)=O'] Note that this is all done in a lazy manner, so "infinitely" large libraries can be done without worrying about running out of memory. Your patience will run out first: Define a set of 10000 amines: >>> amines = (Chem.MolFromSmiles('N'+'C'*x) for x in range(10000)) ... a set of 10000 acids >>> acids = (Chem.MolFromSmiles('OC(=O)'+'C'*x) for x in range(10000)) ... now the virtual library (1e8 compounds in principle): >>> r = AllChem.EnumerateLibraryFromReaction(rxn,[acids,amines]) ... look at the first 4 compounds: >>> [Chem.MolToSmiles(next(r)[0]) for x in range(4)] ['NC=O', 'CNC=O', 'CCNC=O', 'CCCNC=O'] """ if len(sidechainSets) != reaction.GetNumReactantTemplates(): raise ValueError('%d sidechains provided, %d required' % (len(sidechainSets), reaction.GetNumReactantTemplates())) def _combiEnumerator(items, depth=0): for item in items[depth]: if depth + 1 < len(items): v = _combiEnumerator(items, depth + 1) for entry in v: l = [item] l.extend(entry) yield l else: yield [item] ProductReactants = namedtuple('ProductReactants', 'products,reactants') for chains in _combiEnumerator(sidechainSets): prodSets = reaction.RunReactants(chains) for prods in prodSets: if returnReactants: yield ProductReactants(prods, chains) else: yield prods def ConstrainedEmbed(mol, core, useTethers=True, coreConfId=-1, randomseed=2342, getForceField=UFFGetMoleculeForceField, **kwargs): """ generates an embedding of a molecule where part of the molecule is constrained to have particular coordinates Arguments - mol: the molecule to embed - core: the molecule to use as a source of constraints - useTethers: (optional) if True, the final conformation will be optimized subject to a series of extra forces that pull the matching atoms to the positions of the core atoms. Otherwise simple distance constraints based on the core atoms will be used in the optimization. - coreConfId: (optional) id of the core conformation to use - randomSeed: (optional) seed for the random number generator An example, start by generating a template with a 3D structure: >>> from rdkit.Chem import AllChem >>> template = AllChem.MolFromSmiles("c1nn(Cc2ccccc2)cc1") >>> AllChem.EmbedMolecule(template) 0 >>> AllChem.UFFOptimizeMolecule(template) 0 Here's a molecule: >>> mol = AllChem.MolFromSmiles("c1nn(Cc2ccccc2)cc1-c3ccccc3") Now do the constrained embedding >>> mol = AllChem.ConstrainedEmbed(mol, template) Demonstrate that the positions are nearly the same with template: >>> import math >>> molp = mol.GetConformer().GetAtomPosition(0) >>> templatep = template.GetConformer().GetAtomPosition(0) >>> all(math.isclose(v, 0.0, abs_tol=0.01) for v in molp-templatep) True >>> molp = mol.GetConformer().GetAtomPosition(1) >>> templatep = template.GetConformer().GetAtomPosition(1) >>> all(math.isclose(v, 0.0, abs_tol=0.01) for v in molp-templatep) True """ match = mol.GetSubstructMatch(core) if not match: raise ValueError("molecule doesn't match the core") coordMap = {} coreConf = core.GetConformer(coreConfId) for i, idxI in enumerate(match): corePtI = coreConf.GetAtomPosition(i) coordMap[idxI] = corePtI ci = EmbedMolecule(mol, coordMap=coordMap, randomSeed=randomseed, **kwargs) if ci < 0: raise ValueError('Could not embed molecule.') algMap = [(j, i) for i, j in enumerate(match)] if not useTethers: # clean up the conformation ff = getForceField(mol, confId=0) for i, idxI in enumerate(match): for j in range(i + 1, len(match)): idxJ = match[j] d = coordMap[idxI].Distance(coordMap[idxJ]) ff.AddDistanceConstraint(idxI, idxJ, d, d, 100.) ff.Initialize() n = 4 more = ff.Minimize() while more and n: more = ff.Minimize() n -= 1 # rotate the embedded conformation onto the core: rms = AlignMol(mol, core, atomMap=algMap) else: # rotate the embedded conformation onto the core: rms = AlignMol(mol, core, atomMap=algMap) ff = getForceField(mol, confId=0) conf = core.GetConformer() for i in range(core.GetNumAtoms()): p = conf.GetAtomPosition(i) pIdx = ff.AddExtraPoint(p.x, p.y, p.z, fixed=True) - 1 ff.AddDistanceConstraint(pIdx, match[i], 0, 0, 100.) ff.Initialize() n = 4 more = ff.Minimize(energyTol=1e-4, forceTol=1e-3) while more and n: more = ff.Minimize(energyTol=1e-4, forceTol=1e-3) n -= 1 # realign rms = AlignMol(mol, core, atomMap=algMap) mol.SetProp('EmbedRMS', str(rms)) return mol def AssignBondOrdersFromTemplate(refmol, mol): """ assigns bond orders to a molecule based on the bond orders in a template molecule Arguments - refmol: the template molecule - mol: the molecule to assign bond orders to An example, start by generating a template from a SMILES and read in the PDB structure of the molecule >>> import os >>> from rdkit.Chem import AllChem >>> template = AllChem.MolFromSmiles("CN1C(=NC(C1=O)(c2ccccc2)c3ccccc3)N") >>> mol = AllChem.MolFromPDBFile(os.path.join(RDConfig.RDCodeDir, 'Chem', 'test_data', '4DJU_lig.pdb')) >>> len([1 for b in template.GetBonds() if b.GetBondTypeAsDouble() == 1.0]) 8 >>> len([1 for b in mol.GetBonds() if b.GetBondTypeAsDouble() == 1.0]) 22 Now assign the bond orders based on the template molecule >>> newMol = AllChem.AssignBondOrdersFromTemplate(template, mol) >>> len([1 for b in newMol.GetBonds() if b.GetBondTypeAsDouble() == 1.0]) 8 Note that the template molecule should have no explicit hydrogens else the algorithm will fail. It also works if there are different formal charges (this was github issue 235): >>> template=AllChem.MolFromSmiles('CN(C)C(=O)Cc1ccc2c(c1)NC(=O)c3ccc(cc3N2)c4ccc(c(c4)OC)[N+](=O)[O-]') >>> mol = AllChem.MolFromMolFile(os.path.join(RDConfig.RDCodeDir, 'Chem', 'test_data', '4FTR_lig.mol')) >>> AllChem.MolToSmiles(mol) 'COC1CC(C2CCC3C(O)NC4CC(CC(O)N(C)C)CCC4NC3C2)CCC1N(O)O' >>> newMol = AllChem.AssignBondOrdersFromTemplate(template, mol) >>> AllChem.MolToSmiles(newMol) 'COc1cc(-c2ccc3c(c2)Nc2ccc(CC(=O)N(C)C)cc2NC3=O)ccc1[N+](=O)[O-]' """ refmol2 = rdchem.Mol(refmol) mol2 = rdchem.Mol(mol) # do the molecules match already? matching = mol2.GetSubstructMatch(refmol2) if not matching: # no, they don't match # check if bonds of mol are SINGLE for b in mol2.GetBonds(): if b.GetBondType() != BondType.SINGLE: b.SetBondType(BondType.SINGLE) b.SetIsAromatic(False) # set the bonds of mol to SINGLE for b in refmol2.GetBonds(): b.SetBondType(BondType.SINGLE) b.SetIsAromatic(False) # set atom charges to zero; for a in refmol2.GetAtoms(): a.SetFormalCharge(0) for a in mol2.GetAtoms(): a.SetFormalCharge(0) matching = mol2.GetSubstructMatches(refmol2, uniquify=False) # do the molecules match now? if matching: if len(matching) > 1: logger.warning("More than one matching pattern found - picking one") matching = matching[0] # apply matching: set bond properties for b in refmol.GetBonds(): atom1 = matching[b.GetBeginAtomIdx()] atom2 = matching[b.GetEndAtomIdx()] b2 = mol2.GetBondBetweenAtoms(atom1, atom2) b2.SetBondType(b.GetBondType()) b2.SetIsAromatic(b.GetIsAromatic()) # apply matching: set atom properties for a in refmol.GetAtoms(): a2 = mol2.GetAtomWithIdx(matching[a.GetIdx()]) a2.SetHybridization(a.GetHybridization()) a2.SetIsAromatic(a.GetIsAromatic()) a2.SetNumExplicitHs(a.GetNumExplicitHs()) a2.SetFormalCharge(a.GetFormalCharge()) SanitizeMol(mol2) if hasattr(mol2, '__sssAtoms'): mol2.__sssAtoms = None # we don't want all bonds highlighted else: raise ValueError("No matching found") return mol2 # ------------------------------------ # # doctest boilerplate # def _runDoctests(verbose=None): # pragma: nocover import sys import doctest failed, _ = doctest.testmod(optionflags=doctest.ELLIPSIS, verbose=verbose) sys.exit(failed) if __name__ == '__main__': # pragma: nocover _runDoctests()