def __init__(self, pdb_file):
self.receptor = oechem.OEGraphMol()
self.scorers = [oedocking.OEScore(oedocking.OEScoreType_Shapegauss),
oedocking.OEScore(oedocking.OEScoreType_Chemscore),
oedocking.OEScore(oedocking.OEScoreType_Chemgauss3),
oedocking.OEScore(oedocking.OEScoreType_Chemgauss4),
]
self.score = oedocking.OEScore(oedocking.OEScoreType_Chemgauss4)
oedocking.OEReadReceptorFile(self.receptor, pdb_file)
for score in self.scorers:
score.Initialize(self.receptor)
def __init__(self, receptor):
self.receptor = oechem.OEGraphMol()
self.scorers = {
'Shapegauss': oedocking.OEScore(oedocking.OEScoreType_Shapegauss),
'Chemscore': oedocking.OEScore(oedocking.OEScoreType_Chemscore),
'Chemgauss': oedocking.OEScore(oedocking.OEScoreType_Chemgauss),
'Chemgauss3': oedocking.OEScore(oedocking.OEScoreType_Chemgauss3),
'Chemgauss4': oedocking.OEScore(oedocking.OEScoreType_Chemgauss4),
}
for _, score in self.scorers.items():
score.Initialize(receptor)
def main(argv=[__name__]):
if len(argv) != 3:
oechem.OEThrow.Usage("%s <receptor> <poses>" % argv[0])
receptor = oechem.OEGraphMol()
oedocking.OEReadReceptorFile(receptor, argv[1])
oescore = oedocking.OEScore()
oescore.Initialize(receptor)
poses = oechem.OEGraphMol()
imstr = oechem.oemolistream(argv[2])
for poses in imstr.GetOEMols():
TagPoses(oescore, poses, oescore.GetName())
def __init__(self, pdb_file, xmax, ymax, zmax, xmin, ymin, zmin):
self.receptor = oechem.OEGraphMol()
self.scorers = {
'Shapegauss': oedocking.OEScore(oedocking.OEScoreType_Shapegauss),
'Chemscore': oedocking.OEScore(oedocking.OEScoreType_Chemscore),
'Chemgauss': oedocking.OEScore(oedocking.OEScoreType_Chemgauss),
'Chemgauss3': oedocking.OEScore(oedocking.OEScoreType_Chemgauss3),
'Chemgauss4': oedocking.OEScore(oedocking.OEScoreType_Chemgauss4),
}
proteinStructure = oechem.OEGraphMol()
ifs = oechem.oemolistream(pdb_file)
ifs.SetFormat(oechem.OEFormat_PDB)
oechem.OEReadMolecule(ifs, proteinStructure)
box = oedocking.OEBox(xmax, ymax, zmax, xmin, ymin, zmin)
receptor = oechem.OEGraphMol()
s = oedocking.OEMakeReceptor(receptor, proteinStructure, box)
for _, score in self.scorers.items():
assert (s != False)
score.Initialize(receptor)
def __init__(self, pdb_file, xmax, ymax, zmax, xmin, ymin, zmin):
self.receptor = oechem.OEGraphMol()
self.scorers = oedocking.OEScore(oedocking.OEScoreType_Chemgauss4)
proteinStructure = oechem.OEGraphMol()
ifs = oechem.oemolistream(pdb_file)
ifs.SetFormat(oechem.OEFormat_PDB)
oechem.OEReadMolecule(ifs, proteinStructure)
box = oedocking.OEBox(xmax, ymax, zmax, xmin, ymin, zmin)
receptor = oechem.OEGraphMol()
s = oedocking.OEMakeReceptor(receptor, proteinStructure, box)
self.scorers.Initialize(receptor)
def main(argv=[__name__]):
itf = oechem.OEInterface(InterfaceData)
# @ <SNIPPET-RESCORE-POSES-CONFIGURE>
oedocking.OEScoreTypeConfigure(itf, "-score")
# @ </SNIPPET-RESCORE-POSES-CONFIGURE>
if not oechem.OEParseCommandLine(itf, argv):
return 1
receptor = oechem.OEGraphMol()
if not oedocking.OEReadReceptorFile(receptor, itf.GetString("-receptor")):
oechem.OEThrow.Fatal("Unable to read receptor")
imstr = oechem.oemolistream()
if not imstr.open(itf.GetString("-in")):
oechem.OEThrow.Fatal("Unable to open input file of ligands")
omstr = oechem.oemolostream()
if not omstr.open(itf.GetString("-out")):
oechem.OEThrow.Fatal("Unable to open out file for rescored ligands")
# @ <SNIPPET-RESCORE-POSES-GET-VALUE>
scoreType = oedocking.OEScoreTypeGetValue(itf, "-score")
# @ </SNIPPET-RESCORE-POSES-GET-VALUE>
# @ <SNIPPET-RESCORE-POSES-SETUP-SCORE>
score = oedocking.OEScore(scoreType)
# @ </SNIPPET-RESCORE-POSES-SETUP-SCORE>
# @ <SNIPPET-RESCORE-POSES-INITIALIZE>
score.Initialize(receptor)
# @ </SNIPPET-RESCORE-POSES-INITIALIZE>
for ligand in imstr.GetOEMols():
if itf.GetBool("-optimize"):
# @ <SNIPPET-RESCORE-POSES-OPTIMIZE>
score.SystematicSolidBodyOptimize(ligand)
# @ </SNIPPET-RESCORE-POSES-OPTIMIZE>
# @ <SNIPPET-RESCORE-POSES-ANNOTATE>
score.AnnotatePose(ligand)
# @ </SNIPPET-RESCORE-POSES-ANNOTATE>
sdtag = score.GetName()
# @ <SNIPPET-RESCORE-POSES-ASSIGN-SCORE>
oedocking.OESetSDScore(ligand, score, sdtag)
# @ </SNIPPET-RESCORE-POSES-ASSIGN-SCORE>
# @ <SNIPPET-RESCORE-POSES-SCORE-SORTING>
oechem.OESortConfsBySDTag(ligand, sdtag,
score.GetHighScoresAreBetter())
# @ </SNIPPET-RESCORE-POSES-SCORE-SORTING>
oechem.OEWriteMolecule(omstr, ligand)
return 0
def main(argv=[__name__]):
if len(argv) != 3:
oechem.OEThrow.Usage("%s <receptor> <ligand>" % argv[0])
receptor = oechem.OEGraphMol()
oedocking.OEReadReceptorFile(receptor, argv[1])
oescore = oedocking.OEScore()
oescore.Initialize(receptor)
imstr = oechem.oemolistream(argv[2])
mcmol = oechem.OEMol()
oechem.OEReadMolecule(imstr, mcmol)
for pose in mcmol.GetConfs():
PrintScore(oescore, pose)
for atom in pose.GetAtoms():
PrintAtomScore(oescore, pose, atom)
def main(argv=[__name__]):
if len(argv) != 3:
oechem.OEThrow.Usage("%s <receptor> <ligand>" % argv[0])
# @ <SNIPPET-SCORE-BOX-1>
protein = oechem.OEGraphMol()
imstr = oechem.oemolistream(argv[1])
oechem.OEReadMolecule(imstr, protein)
pose = oechem.OEGraphMol()
imstr.open(argv[2])
oechem.OEReadMolecule(imstr, pose)
addbox = 4.0
box = oedocking.OEBox()
oedocking.OESetupBox(box, pose, addbox)
oescore = oedocking.OEScore()
oescore.Initialize(protein, box)
def generate_restricted_conformers(receptor, refmol, mol, core_smarts=None):
"""
Generate and select a conformer of the specified molecule using the reference molecule
Parameters
----------
receptor : openeye.oechem.OEGraphMol
Receptor (already prepped for docking) for identifying optimal pose
refmol : openeye.oechem.OEGraphMol
Reference molecule which shares some part in common with the proposed molecule
mol : openeye.oechem.OEGraphMol
Molecule whose conformers are to be enumerated
core_smarts : str, optional, default=None
If core_smarts is specified, substructure will be extracted using SMARTS.
"""
from openeye import oechem, oeomega
# DEBUG: For benzotriazoles, truncate refmol
core_smarts = 'c1ccc(NC(=O)[C,N]n2nnc3ccccc32)cc1' # prospective
core_smarts = 'NC(=O)[C,N]n2nnc3ccccc32' # retrospective
# Get core fragment
if core_smarts:
# Truncate refmol to SMARTS if specified
#print(f'Trunctating using SMARTS {refmol_smarts}')
ss = oechem.OESubSearch(core_smarts)
oechem.OEPrepareSearch(refmol, ss)
for match in ss.Match(refmol):
core_fragment = oechem.OEGraphMol()
oechem.OESubsetMol(core_fragment, match)
break
#print(f'refmol has {refmol.NumAtoms()} atoms')
else:
core_fragment = GetCoreFragment(refmol, [mol])
oechem.OESuppressHydrogens(core_fragment)
#print(f' Core fragment has {core_fragment.NumAtoms()} heavy atoms')
MIN_CORE_ATOMS = 6
if core_fragment.NumAtoms() < MIN_CORE_ATOMS:
return None
# Create an Omega instance
#omegaOpts = oeomega.OEOmegaOptions()
omegaOpts = oeomega.OEOmegaOptions(oeomega.OEOmegaSampling_Dense)
# Set the fixed reference molecule
omegaFixOpts = oeomega.OEConfFixOptions()
omegaFixOpts.SetFixMaxMatch(10) # allow multiple MCSS matches
omegaFixOpts.SetFixDeleteH(True) # only use heavy atoms
omegaFixOpts.SetFixMol(core_fragment)
#omegaFixOpts.SetFixSmarts(smarts)
omegaFixOpts.SetFixRMS(0.5)
atomexpr = oechem.OEExprOpts_Aromaticity | oechem.OEExprOpts_Hybridization
bondexpr = oechem.OEExprOpts_BondOrder | oechem.OEExprOpts_Aromaticity
omegaFixOpts.SetAtomExpr(atomexpr)
omegaFixOpts.SetBondExpr(bondexpr)
omegaOpts.SetConfFixOptions(omegaFixOpts)
molBuilderOpts = oeomega.OEMolBuilderOptions()
molBuilderOpts.SetStrictAtomTypes(False) # don't give up if MMFF types are not found
omegaOpts.SetMolBuilderOptions(molBuilderOpts)
omegaOpts.SetWarts(False) # expand molecule title
omegaOpts.SetStrictStereo(False) # set strict stereochemistry
omegaOpts.SetIncludeInput(False) # don't include input
omegaOpts.SetMaxConfs(1000) # generate lots of conformers
#omegaOpts.SetEnergyWindow(10.0) # allow high energies
omega = oeomega.OEOmega(omegaOpts)
from openeye import oequacpac
if not oequacpac.OEGetReasonableProtomer(mol):
print('No reasonable protomer found')
return None
mol = oechem.OEMol(mol) # multi-conformer molecule
ret_code = omega.Build(mol)
if (mol.GetDimension() != 3) or (ret_code != oeomega.OEOmegaReturnCode_Success):
print(f'Omega failure: {mol.GetDimension()} and {oeomega.OEGetOmegaError(ret_code)}')
return None
# Extract poses
class Pose(object):
def __init__(self, conformer):
self.conformer = conformer
self.clash_score = None
self.docking_score = None
self.overlap_score = None
poses = [ Pose(conf) for conf in mol.GetConfs() ]
# Score clashes
bump_check = BumpCheck(receptor)
for pose in poses:
pose.clash_score = bump_check.count(pose.conformer)
# Score docking poses
from openeye import oedocking
score = oedocking.OEScore(oedocking.OEScoreType_Chemgauss4)
score.Initialize(receptor)
for pose in poses:
pose.docking_score = score.ScoreLigand(pose.conformer)
# Compute overlap scores
from openeye import oeshape
overlap_prep = oeshape.OEOverlapPrep()
overlap_prep.Prep(refmol)
shapeFunc = oeshape.OEExactShapeFunc()
shapeFunc.SetupRef(refmol)
oeshape_result = oeshape.OEOverlapResults()
for pose in poses:
tmpmol = oechem.OEGraphMol(pose.conformer)
overlap_prep.Prep(tmpmol)
shapeFunc.Overlap(tmpmol, oeshape_result)
pose.overlap_score = oeshape_result.GetRefTversky()
# Filter poses based on top 10% of overlap
poses = sorted(poses, key= lambda pose : pose.overlap_score)
poses = poses[int(0.9*len(poses)):]
# Select the best docking score
import numpy as np
poses = sorted(poses, key=lambda pose : pose.docking_score)
pose = poses[0]
mol.SetActive(pose.conformer)
oechem.OESetSDData(mol, 'clash_score', str(pose.clash_score))
oechem.OESetSDData(mol, 'docking_score', str(pose.docking_score))
oechem.OESetSDData(mol, 'overlap_score', str(pose.overlap_score))
# Convert to single-conformer molecule
mol = oechem.OEGraphMol(mol)
return mol
def generate_restricted_conformers(receptor, refmol, mol, core_smarts=None):
"""
Generate and select a conformer of the specified molecule using the reference molecule
Parameters
----------
receptor : openeye.oechem.OEGraphMol
Receptor (already prepped for docking) for identifying optimal pose
refmol : openeye.oechem.OEGraphMol
Reference molecule which shares some part in common with the proposed molecule
mol : openeye.oechem.OEGraphMol
Molecule whose conformers are to be enumerated
core_smarts : str, optional, default=None
If core_smarts is specified, substructure will be extracted using SMARTS.
"""
from openeye import oechem, oeomega
logging.debug(
f'mol: {oechem.OEMolToSmiles(mol)} | core_smarts: {core_smarts}')
# Be quiet
from openeye import oechem
oechem.OEThrow.SetLevel(oechem.OEErrorLevel_Quiet)
#oechem.OEThrow.SetLevel(oechem.OEErrorLevel_Error)
# Get core fragment
if core_smarts:
# Truncate refmol to SMARTS if specified
#print(f'Trunctating using SMARTS {refmol_smarts}')
ss = oechem.OESubSearch(core_smarts)
oechem.OEPrepareSearch(refmol, ss)
for match in ss.Match(refmol):
core_fragment = oechem.OEGraphMol()
oechem.OESubsetMol(core_fragment, match)
logging.debug(
f'Truncated refmol to generate core_fragment: {oechem.OEMolToSmiles(core_fragment)}'
)
break
#print(f'refmol has {refmol.NumAtoms()} atoms')
else:
core_fragment = GetCoreFragment(refmol, [mol])
oechem.OESuppressHydrogens(core_fragment)
#print(f' Core fragment has {core_fragment.NumAtoms()} heavy atoms')
MIN_CORE_ATOMS = 6
if core_fragment.NumAtoms() < MIN_CORE_ATOMS:
return None
# Create an Omega instance
#omegaOpts = oeomega.OEOmegaOptions()
omegaOpts = oeomega.OEOmegaOptions(oeomega.OEOmegaSampling_Dense)
# Set the fixed reference molecule
omegaFixOpts = oeomega.OEConfFixOptions()
omegaFixOpts.SetFixMaxMatch(10) # allow multiple MCSS matches
omegaFixOpts.SetFixDeleteH(True) # only use heavy atoms
omegaFixOpts.SetFixMol(core_fragment)
#omegaFixOpts.SetFixSmarts(core_smarts) # DEBUG
omegaFixOpts.SetFixRMS(0.5)
# This causes a warning:
#Warning: OESubSearch::Match() is unable to match unset hybridization in the target (EN300-221518_3_1) for patterns with set hybridization, call OEPrepareSearch on the target first
#atomexpr = oechem.OEExprOpts_Aromaticity | oechem.OEExprOpts_Hybridization
atomexpr = oechem.OEExprOpts_Aromaticity | oechem.OEExprOpts_AtomicNumber
bondexpr = oechem.OEExprOpts_BondOrder | oechem.OEExprOpts_Aromaticity
omegaFixOpts.SetAtomExpr(atomexpr)
omegaFixOpts.SetBondExpr(bondexpr)
omegaOpts.SetConfFixOptions(omegaFixOpts)
molBuilderOpts = oeomega.OEMolBuilderOptions()
molBuilderOpts.SetStrictAtomTypes(
False) # don't give up if MMFF types are not found
omegaOpts.SetMolBuilderOptions(molBuilderOpts)
omegaOpts.SetWarts(False) # expand molecule title
omegaOpts.SetStrictStereo(True) # set strict stereochemistry
omegaOpts.SetIncludeInput(False) # don't include input
omegaOpts.SetMaxConfs(1000) # generate lots of conformers
omegaOpts.SetEnergyWindow(20.0) # allow high energies
omega = oeomega.OEOmega(omegaOpts)
# TODO: Expand protonation states and tautomers
from openeye import oequacpac
if not oequacpac.OEGetReasonableProtomer(mol):
logging.warning('No reasonable protomer found')
return None
mol = oechem.OEMol(mol) # multi-conformer molecule
ret_code = omega.Build(mol)
if (mol.GetDimension() != 3) or (ret_code !=
oeomega.OEOmegaReturnCode_Success):
msg = f'\nOmega failure for {mol.GetTitle()} : SMILES {oechem.OEMolToSmiles(mol)} : core_smarts {core_smarts} : {oeomega.OEGetOmegaError(ret_code)}\n'
logging.warning(msg)
return None
# Return the molecule with an error code
#oechem.OESetSDData(mol, 'error', '{oeomega.OEGetOmegaError(ret_code)}')
#return mol
# Extract poses
class Pose(object):
def __init__(self, conformer):
self.conformer = conformer
self.clash_score = None
self.docking_score = None
self.overlap_score = None
poses = [Pose(conf) for conf in mol.GetConfs()]
# Score clashes
bump_check = BumpCheck(receptor)
for pose in poses:
pose.clash_score = bump_check.count(pose.conformer)
# Score docking poses
from openeye import oedocking
score = oedocking.OEScore(oedocking.OEScoreType_Chemgauss4)
score.Initialize(receptor)
for pose in poses:
pose.docking_score = score.ScoreLigand(pose.conformer)
# Compute overlap scores
from openeye import oeshape
overlap_prep = oeshape.OEOverlapPrep()
overlap_prep.Prep(refmol)
shapeFunc = oeshape.OEExactShapeFunc()
shapeFunc.SetupRef(refmol)
oeshape_result = oeshape.OEOverlapResults()
for pose in poses:
tmpmol = oechem.OEGraphMol(pose.conformer)
overlap_prep.Prep(tmpmol)
shapeFunc.Overlap(tmpmol, oeshape_result)
pose.overlap_score = oeshape_result.GetRefTversky()
# Filter poses based on top 10% of overlap
poses = sorted(poses, key=lambda pose: pose.overlap_score)
poses = poses[int(0.9 * len(poses)):]
# Select the best docking score
import numpy as np
poses = sorted(poses, key=lambda pose: pose.docking_score)
pose = poses[0]
mol.SetActive(pose.conformer)
oechem.OESetSDData(mol, 'clash_score', str(pose.clash_score))
oechem.OESetSDData(mol, 'docking_score', str(pose.docking_score))
oechem.OESetSDData(mol, 'overlap_score', str(pose.overlap_score))
# Convert to single-conformer molecule
mol = oechem.OEGraphMol(mol)
# Compute MMFF energy
energy = mmff_energy(mol)
oechem.OESetSDData(mol, 'MMFF_internal_energy', str(energy))
# Store SMILES
docked_smiles = oechem.OEMolToSmiles(mol)
oechem.OESetSDData(mol, 'docked_smiles', docked_smiles)
return mol
def __init__(self, pdb_file):
self.receptor = oechem.OEGraphMol()
self.score = oedocking.OEScore(oedocking.OEScoreType_Chemgauss4)
oedocking.OEReadReceptorFile(self.receptor, pdb_file)
self.score.Initialize(self.receptor)
def __init__(self, receptor):
self.receptor = oechem.OEGraphMol()
self.scorers = oedocking.OEScore(oedocking.OEScoreType_Chemgauss4)
self.scorers.Initialize(receptor)
