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# Copyright (C) 2014 Sereina Riniker
#
# 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.
#
""" Torsion Fingerprints (Deviation) (TFD)
According to a paper from Schulz-Gasch et al., JCIM, 52, 1499-1512 (2012).
"""
from rdkit import rdBase
from rdkit import RDConfig
from rdkit import Geometry
from rdkit import Chem
from rdkit.Chem import rdchem
from rdkit.Chem import rdMolDescriptors
import math, os
def _doMatch(inv, atoms):
""" Helper function to check if all atoms in the list are the same
Arguments:
- inv: atom invariants (used to define equivalence of atoms)
- atoms: list of atoms to check
Return: boolean
"""
match = True
for i in range(len(atoms) - 1):
for j in range(i + 1, len(atoms)):
if (inv[atoms[i].GetIdx()] != inv[atoms[j].GetIdx()]):
match = False
return match
return match
def _doNotMatch(inv, atoms):
""" Helper function to check if all atoms in the list are NOT the same
Arguments:
- inv: atom invariants (used to define equivalence of atoms)
- atoms: list of atoms to check
Return: boolean
"""
match = True
for i in range(len(atoms) - 1):
for j in range(i + 1, len(atoms)):
if (inv[atoms[i].GetIdx()] == inv[atoms[j].GetIdx()]):
match = False
return match
return match
def _doMatchExcept1(inv, atoms):
""" Helper function to check if two atoms in the list are the same,
and one not
Note: Works only for three atoms
Arguments:
- inv: atom invariants (used to define equivalence of atoms)
- atoms: list of atoms to check
Return: atom that is different
"""
if len(atoms) != 3:
raise ValueError("Number of atoms must be three")
a1 = atoms[0].GetIdx()
a2 = atoms[1].GetIdx()
a3 = atoms[2].GetIdx()
if (inv[a1] == inv[a2] and inv[a1] != inv[a3] and inv[a2] != inv[a3]):
return atoms[2]
elif (inv[a1] != inv[a2] and inv[a1] == inv[a3] and inv[a2] != inv[a3]):
return atoms[1]
elif (inv[a1] != inv[a2] and inv[a1] != inv[a3] and inv[a2] == inv[a3]):
return atoms[0]
return None
def _getAtomInvariantsWithRadius(mol, radius):
""" Helper function to calculate the atom invariants for each atom
with a given radius
Arguments:
- mol: the molecule of interest
- radius: the radius for the Morgan fingerprint
Return: list of atom invariants
"""
inv = []
for i in range(mol.GetNumAtoms()):
info = {}
fp = rdMolDescriptors.GetMorganFingerprint(mol, radius, fromAtoms=[i], bitInfo=info)
for k in info.keys():
if info[k][0][1] == radius:
inv.append(k)
return inv
def _getHeavyAtomNeighbors(atom1, aid2=-1):
""" Helper function to calculate the number of heavy atom neighbors.
Arguments:
- atom1: the atom of interest
- aid2: atom index that should be excluded from neighbors (default: none)
Return: a list of heavy atom neighbors of the given atom
"""
if aid2 < 0:
return [n for n in atom1.GetNeighbors() if n.GetSymbol() != 'H']
else:
return [n for n in atom1.GetNeighbors() if (n.GetSymbol() != 'H' and n.GetIdx() != aid2)]
def _getIndexforTorsion(neighbors, inv):
""" Helper function to calculate the index of the reference atom for
a given atom
Arguments:
- neighbors: list of the neighbors of the atom
- inv: atom invariants
Return: list of atom indices as reference for torsion
"""
if len(neighbors) == 1: # atom has only one neighbor
return [neighbors[0]]
elif _doMatch(inv, neighbors): # atom has all symmetric neighbors
return neighbors
elif _doNotMatch(inv, neighbors): # atom has all different neighbors
# sort by atom inv and simply use the first neighbor
neighbors = sorted(neighbors, key=lambda x: inv[x.GetIdx()])
return [neighbors[0]]
at = _doMatchExcept1(inv, neighbors) # two neighbors the same, one different
if at is None:
raise ValueError("Atom neighbors are either all the same or all different")
return [at]
def _getBondsForTorsions(mol, ignoreColinearBonds):
""" Determine the bonds (or pair of atoms treated like a bond) for which
torsions should be calculated.
Arguments:
- refmol: the molecule of interest
- ignoreColinearBonds: if True (default), single bonds adjacent to
triple bonds are ignored
if False, alternative not-covalently bound
atoms are used to define the torsion
"""
# flag the atoms that cannot be part of the centre atoms of a torsion
# patterns: triple bonds and allenes
patts = [Chem.MolFromSmarts(x) for x in ['*#*', '[$([C](=*)=*)]']]
atomFlags = [0] * mol.GetNumAtoms()
for p in patts:
if mol.HasSubstructMatch(p):
matches = mol.GetSubstructMatches(p)
for match in matches:
for a in match:
atomFlags[a] = 1
bonds = []
doneBonds = [0] * mol.GetNumBonds()
for b in mol.GetBonds():
if b.IsInRing():
continue
a1 = b.GetBeginAtomIdx()
a2 = b.GetEndAtomIdx()
nb1 = _getHeavyAtomNeighbors(b.GetBeginAtom(), a2)
nb2 = _getHeavyAtomNeighbors(b.GetEndAtom(), a1)
if not doneBonds[b.GetIdx()] and (nb1 and nb2): # no terminal bonds
doneBonds[b.GetIdx()] = 1
# check if atoms cannot be middle atoms
if atomFlags[a1] or atomFlags[a2]:
if not ignoreColinearBonds: # search for alternative not-covalently bound atoms
while len(nb1) == 1 and atomFlags[a1]:
a1old = a1
a1 = nb1[0].GetIdx()
b = mol.GetBondBetweenAtoms(a1old, a1)
if b.GetEndAtom().GetIdx() == a1old:
nb1 = _getHeavyAtomNeighbors(b.GetBeginAtom(), a1old)
else:
nb1 = _getHeavyAtomNeighbors(b.GetEndAtom(), a1old)
doneBonds[b.GetIdx()] = 1
while len(nb2) == 1 and atomFlags[a2]:
doneBonds[b.GetIdx()] = 1
a2old = a2
a2 = nb2[0].GetIdx()
b = mol.GetBondBetweenAtoms(a2old, a2)
if b.GetBeginAtom().GetIdx() == a2old:
nb2 = _getHeavyAtomNeighbors(b.GetEndAtom(), a2old)
else:
nb2 = _getHeavyAtomNeighbors(b.GetBeginAtom(), a2old)
doneBonds[b.GetIdx()] = 1
if nb1 and nb2:
bonds.append((a1, a2, nb1, nb2))
else:
bonds.append((a1, a2, nb1, nb2))
return bonds
def CalculateTorsionLists(mol, maxDev='equal', symmRadius=2, ignoreColinearBonds=True):
""" Calculate a list of torsions for a given molecule. For each torsion
the four atom indices are determined and stored in a set.
Arguments:
- mol: the molecule of interest
- maxDev: maximal deviation used for normalization
'equal': all torsions are normalized using 180.0 (default)
'spec': each torsion is normalized using its specific
maximal deviation as given in the paper
- symmRadius: radius used for calculating the atom invariants
(default: 2)
- ignoreColinearBonds: if True (default), single bonds adjacent to
triple bonds are ignored
if False, alternative not-covalently bound
atoms are used to define the torsion
Return: two lists of torsions: non-ring and ring torsions
"""
if maxDev not in ['equal', 'spec']:
raise ValueError("maxDev must be either equal or spec")
# get non-terminal, non-cyclic bonds
bonds = _getBondsForTorsions(mol, ignoreColinearBonds)
# get atom invariants
if symmRadius > 0:
inv = _getAtomInvariantsWithRadius(mol, symmRadius)
else:
inv = rdMolDescriptors.GetConnectivityInvariants(mol)
# get the torsions
tors_list = [] # to store the atom indices of the torsions
for a1, a2, nb1, nb2 in bonds:
d1 = _getIndexforTorsion(nb1, inv)
d2 = _getIndexforTorsion(nb2, inv)
if len(d1) == 1 and len(d2) == 1: # case 1, 2, 4, 5, 7, 10, 16, 12, 17, 19
tors_list.append(([(d1[0].GetIdx(), a1, a2, d2[0].GetIdx())], 180.0))
elif len(d1) == 1: # case 3, 6, 8, 13, 20
if len(nb2) == 2: # two neighbors
tors_list.append(([(d1[0].GetIdx(), a1, a2, nb.GetIdx()) for nb in d2], 90.0))
else: # three neighbors
tors_list.append(([(d1[0].GetIdx(), a1, a2, nb.GetIdx()) for nb in d2], 60.0))
elif len(d2) == 1: # case 3, 6, 8, 13, 20
if len(nb1) == 2:
tors_list.append(([(nb.GetIdx(), a1, a2, d2[0].GetIdx()) for nb in d1], 90.0))
else: # three neighbors
tors_list.append(([(nb.GetIdx(), a1, a2, d2[0].GetIdx()) for nb in d1], 60.0))
else: # both symmetric
tmp = []
for n1 in d1:
for n2 in d2:
tmp.append((n1.GetIdx(), a1, a2, n2.GetIdx()))
if len(nb1) == 2 and len(nb2) == 2: # case 9
tors_list.append((tmp, 90.0))
elif len(nb1) == 3 and len(nb2) == 3: # case 21
tors_list.append((tmp, 60.0))
else: # case 15
tors_list.append((tmp, 30.0))
# maximal possible deviation for non-cyclic bonds
if maxDev == 'equal':
tors_list = [(t, 180.0) for t, d in tors_list]
# rings
rings = Chem.GetSymmSSSR(mol)
tors_list_rings = []
for r in rings:
# get the torsions
tmp = []
num = len(r)
maxdev = 180.0 * math.exp(-0.025 * (num - 14) * (num - 14))
for i in range(len(r)):
tmp.append((r[i], r[(i + 1) % num], r[(i + 2) % num], r[(i + 3) % num]))
tors_list_rings.append((tmp, maxdev))
return tors_list, tors_list_rings
def _getTorsionAtomPositions(atoms, conf):
""" Helper function to retrieve the coordinates of the four atoms
in a torsion
Arguments:
- atoms: list with the four atoms
- conf: conformation of the molecule
Return: Point3D objects of the four atoms
"""
if len(atoms) != 4:
raise ValueError("List must contain exactly four atoms")
p1 = conf.GetAtomPosition(atoms[0])
p2 = conf.GetAtomPosition(atoms[1])
p3 = conf.GetAtomPosition(atoms[2])
p4 = conf.GetAtomPosition(atoms[3])
return p1, p2, p3, p4
def CalculateTorsionAngles(mol, tors_list, tors_list_rings, confId=-1):
""" Calculate the torsion angles for a list of non-ring and
a list of ring torsions.
Arguments:
- mol: the molecule of interest
- tors_list: list of non-ring torsions
- tors_list_rings: list of ring torsions
- confId: index of the conformation (default: first conformer)
Return: list of torsion angles
"""
torsions = []
conf = mol.GetConformer(confId)
for quartets, maxdev in tors_list:
tors = []
# loop over torsions and calculate angle
for atoms in quartets:
p1, p2, p3, p4 = _getTorsionAtomPositions(atoms, conf)
tmpTors = (Geometry.ComputeSignedDihedralAngle(p1, p2, p3, p4) / math.pi) * 180.0
if tmpTors < 0:
tmpTors += 360.0 # angle between 0 and 360
tors.append(tmpTors)
torsions.append((tors, maxdev))
# rings
for quartets, maxdev in tors_list_rings:
num = len(quartets)
# loop over torsions and sum them up
tors = 0
for atoms in quartets:
p1, p2, p3, p4 = _getTorsionAtomPositions(atoms, conf)
tmpTors = abs((Geometry.ComputeSignedDihedralAngle(p1, p2, p3, p4) / math.pi) * 180.0)
tors += tmpTors
tors /= num
torsions.append(([tors], maxdev))
return torsions
def _findCentralBond(mol, distmat):
""" Helper function to identify the atoms of the most central bond.
Arguments:
- mol: the molecule of interest
- distmat: distance matrix of the molecule
Return: atom indices of the two most central atoms (in order)
"""
from numpy import std
# get the most central atom = atom with the least STD of shortest distances
stds = []
for i in range(mol.GetNumAtoms()):
# only consider non-terminal atoms
if len(_getHeavyAtomNeighbors(mol.GetAtomWithIdx(i))) < 2:
continue
tmp = [d for d in distmat[i]]
tmp.pop(i)
stds.append((std(tmp), i))
stds.sort()
aid1 = stds[0][1]
# find the second most central bond that is bonded to aid1
i = 1
while 1:
if mol.GetBondBetweenAtoms(aid1, stds[i][1]) is None:
i += 1
else:
aid2 = stds[i][1]
break
return aid1, aid2 # most central atom comes first
def _calculateBeta(mol, distmat, aid1):
""" Helper function to calculate the beta for torsion weights
according to the formula in the paper.
w(dmax/2) = 0.1
Arguments:
- mol: the molecule of interest
- distmat: distance matrix of the molecule
- aid1: atom index of the most central atom
Return: value of beta (float)
"""
# get all non-terminal bonds
bonds = []
for b in mol.GetBonds():
nb1 = _getHeavyAtomNeighbors(b.GetBeginAtom())
nb2 = _getHeavyAtomNeighbors(b.GetEndAtom())
if len(nb2) > 1 and len(nb2) > 1:
bonds.append(b)
# get shortest distance
dmax = 0
for b in bonds:
bid1 = b.GetBeginAtom().GetIdx()
bid2 = b.GetEndAtom().GetIdx()
d = max([distmat[aid1][bid1], distmat[aid1][bid2]])
if (d > dmax):
dmax = d
dmax2 = dmax / 2.0
beta = -math.log(0.1) / (dmax2 * dmax2)
return beta
def CalculateTorsionWeights(mol, aid1=-1, aid2=-1, ignoreColinearBonds=True):
""" Calculate the weights for the torsions in a molecule.
By default, the highest weight is given to the bond
connecting the two most central atoms.
If desired, two alternate atoms can be specified (must
be connected by a bond).
Arguments:
- mol: the molecule of interest
- aid1: index of the first atom (default: most central)
- aid2: index of the second atom (default: second most central)
- ignoreColinearBonds: if True (default), single bonds adjacent to
triple bonds are ignored
if False, alternative not-covalently bound
atoms are used to define the torsion
Return: list of torsion weights (both non-ring and ring)
"""
# get distance matrix
distmat = Chem.GetDistanceMatrix(mol)
if aid1 < 0 and aid2 < 0:
aid1, aid2 = _findCentralBond(mol, distmat)
else:
b = mol.GetBondBetweenAtoms(aid1, aid2)
if b is None:
raise ValueError("Specified atoms must be connected by a bond.")
# calculate beta according to the formula in the paper
beta = _calculateBeta(mol, distmat, aid1)
# get non-terminal, non-cyclic bonds
bonds = _getBondsForTorsions(mol, ignoreColinearBonds)
# get shortest paths and calculate weights
weights = []
for bid1, bid2, nb1, nb2 in bonds:
if ((bid1, bid2) == (aid1, aid2) or
(bid2, bid1) == (aid1, aid2)): # if it's the most central bond itself
d = 0
else:
# get shortest distance between the 4 atoms and add 1 to get bond distance
d = min(distmat[aid1][bid1], distmat[aid1][bid2], distmat[aid2][bid1],
distmat[aid2][bid2]) + 1
w = math.exp(-beta * (d * d))
weights.append(w)
## RINGS
rings = mol.GetRingInfo()
for r in rings.BondRings():
# get shortest distances
tmp = []
num = len(r)
for bidx in r:
b = mol.GetBondWithIdx(bidx)
bid1 = b.GetBeginAtomIdx()
bid2 = b.GetEndAtomIdx()
# get shortest distance between the 4 atoms and add 1 to get bond distance
d = min(distmat[aid1][bid1], distmat[aid1][bid2], distmat[aid2][bid1],
distmat[aid2][bid2]) + 1
tmp.append(d)
# calculate weights and append to list
# Note: the description in the paper is not very clear, the following
# formula was found to give the same weights as shown in Fig. 1
# For a ring of size N: w = N/2 * exp(-beta*(sum(w of each bond in ring)/N)^2)
w = sum(tmp) / float(num)
w = math.exp(-beta * (w * w))
weights.append(w * (num / 2.0))
return weights
def CalculateTFD(torsions1, torsions2, weights=None):
""" Calculate the torsion deviation fingerprint (TFD) given two lists of
torsion angles.
Arguments:
- torsions1: torsion angles of conformation 1
- torsions2: torsion angles of conformation 2
- weights: list of torsion weights (default: None)
Return: TFD value (float)
"""
if len(torsions1) != len(torsions2):
raise ValueError("List of torsions angles must have the same size.")
# calculate deviations and normalize (divide by max. possible deviation)
deviations = []
for tors1, tors2 in zip(torsions1, torsions2):
mindiff = 180.0
for t1 in tors1[0]:
for t2 in tors2[0]:
diff = abs(t1 - t2)
if (360.0 - diff) < diff: # we do not care about direction
diff = 360.0 - diff
#print t1, t2, diff
if diff < mindiff:
mindiff = diff
deviations.append(mindiff / tors1[1])
# do we use weights?
if weights is not None:
if len(weights) != len(torsions1):
raise ValueError("List of torsions angles and weights must have the same size.")
deviations = [d * w for d, w in zip(deviations, weights)]
sum_weights = sum(weights)
else:
sum_weights = len(deviations)
tfd = sum(deviations)
if sum_weights != 0: # avoid division by zero
tfd /= sum_weights
return tfd
def _getSameAtomOrder(mol1, mol2):
""" Generate a new molecule with the atom order of mol1 and coordinates
from mol2.
Arguments:
- mol1: first instance of the molecule of interest
- mol2: second instance the molecule of interest
Return: RDKit molecule
"""
match = mol2.GetSubstructMatch(mol1)
atomNums = tuple(range(mol1.GetNumAtoms()))
if match != atomNums: # atom orders are not the same!
#print "Atoms of second molecule reordered."
mol3 = Chem.Mol(mol1)
mol3.RemoveAllConformers()
for conf2 in mol2.GetConformers():
confId = conf2.GetId()
conf = rdchem.Conformer(mol1.GetNumAtoms())
conf.SetId(confId)
for i in range(mol1.GetNumAtoms()):
conf.SetAtomPosition(i, mol2.GetConformer(confId).GetAtomPosition(match[i]))
cid = mol3.AddConformer(conf)
return mol3
else:
return Chem.Mol(mol2)
# some wrapper functions
def GetTFDBetweenConformers(mol, confIds1, confIds2, useWeights=True, maxDev='equal', symmRadius=2,
ignoreColinearBonds=True):
""" Wrapper to calculate the TFD between two list of conformers
of a molecule
Arguments:
- mol: the molecule of interest
- confIds1: first list of conformer indices
- confIds2: second list of conformer indices
- useWeights: flag for using torsion weights in the TFD calculation
- maxDev: maximal deviation used for normalization
'equal': all torsions are normalized using 180.0 (default)
'spec': each torsion is normalized using its specific
maximal deviation as given in the paper
- symmRadius: radius used for calculating the atom invariants
(default: 2)
- ignoreColinearBonds: if True (default), single bonds adjacent to
triple bonds are ignored
if False, alternative not-covalently bound
atoms are used to define the torsion
Return: list of TFD values
"""
tl, tlr = CalculateTorsionLists(mol, maxDev=maxDev, symmRadius=symmRadius,
ignoreColinearBonds=ignoreColinearBonds)
torsions1 = [CalculateTorsionAngles(mol, tl, tlr, confId=cid) for cid in confIds1]
torsions2 = [CalculateTorsionAngles(mol, tl, tlr, confId=cid) for cid in confIds2]
tfd = []
if useWeights:
weights = CalculateTorsionWeights(mol, ignoreColinearBonds=ignoreColinearBonds)
for t1 in torsions1:
for t2 in torsions2:
tfd.append(CalculateTFD(t1, t2, weights=weights))
else:
for t1 in torsions1:
for t2 in torsions2:
tfd.append(CalculateTFD(t1, t2))
return tfd
def GetTFDBetweenMolecules(mol1, mol2, confId1=-1, confId2=-1, useWeights=True, maxDev='equal',
symmRadius=2, ignoreColinearBonds=True):
""" Wrapper to calculate the TFD between two molecules.
Important: The two molecules must be instances of the same molecule
Arguments:
- mol1: first instance of the molecule of interest
- mol2: second instance the molecule of interest
- confId1: conformer index for mol1 (default: first conformer)
- confId2: conformer index for mol2 (default: first conformer)
- useWeights: flag for using torsion weights in the TFD calculation
- maxDev: maximal deviation used for normalization
'equal': all torsions are normalized using 180.0 (default)
'spec': each torsion is normalized using its specific
maximal deviation as given in the paper
- symmRadius: radius used for calculating the atom invariants
(default: 2)
- ignoreColinearBonds: if True (default), single bonds adjacent to
triple bonds are ignored
if False, alternative not-covalently bound
atoms are used to define the torsion
Return: TFD value
"""
if (Chem.MolToSmiles(mol1) != Chem.MolToSmiles(mol2)):
raise ValueError("The two molecules must be instances of the same molecule!")
mol2 = _getSameAtomOrder(mol1, mol2)
tl, tlr = CalculateTorsionLists(mol1, maxDev=maxDev, symmRadius=symmRadius,
ignoreColinearBonds=ignoreColinearBonds)
# first molecule
torsion1 = CalculateTorsionAngles(mol1, tl, tlr, confId=confId1)
# second molecule
torsion2 = CalculateTorsionAngles(mol2, tl, tlr, confId=confId2)
if useWeights:
weights = CalculateTorsionWeights(mol1, ignoreColinearBonds=ignoreColinearBonds)
tfd = CalculateTFD(torsion1, torsion2, weights=weights)
else:
tfd = CalculateTFD(torsion1, torsion2)
return tfd
def GetTFDMatrix(mol, useWeights=True, maxDev='equal', symmRadius=2, ignoreColinearBonds=True):
""" Wrapper to calculate the matrix of TFD values for the
conformers of a molecule.
Arguments:
- mol: the molecule of interest
- useWeights: flag for using torsion weights in the TFD calculation
- maxDev: maximal deviation used for normalization
'equal': all torsions are normalized using 180.0 (default)
'spec': each torsion is normalized using its specific
maximal deviation as given in the paper
- symmRadius: radius used for calculating the atom invariants
(default: 2)
- ignoreColinearBonds: if True (default), single bonds adjacent to
triple bonds are ignored
if False, alternative not-covalently bound
atoms are used to define the torsion
Return: matrix of TFD values
Note that the returned matrix is symmetrical, i.e. it is the
lower half of the matrix, e.g. for 5 conformers:
matrix = [ a,
b, c,
d, e, f,
g, h, i, j]
"""
tl, tlr = CalculateTorsionLists(mol, maxDev=maxDev, symmRadius=symmRadius,
ignoreColinearBonds=ignoreColinearBonds)
numconf = mol.GetNumConformers()
torsions = [CalculateTorsionAngles(mol, tl, tlr, confId=conf.GetId())
for conf in mol.GetConformers()]
tfdmat = []
if useWeights:
weights = CalculateTorsionWeights(mol, ignoreColinearBonds=ignoreColinearBonds)
for i in range(0, numconf):
for j in range(0, i):
tfdmat.append(CalculateTFD(torsions[i], torsions[j], weights=weights))
else:
for i in range(0, numconf):
for j in range(0, i):
tfdmat.append(CalculateTFD(torsions[i], torsions[j]))
return tfdmat
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