def get_atom_pair_similarity(correct_ligand,
mol_to_fix,
type_fp='normal',
use_features=False):
type_fp = type_fp
correct_ligand_fingerprint = SimilarityMaps.GetAPFingerprint(
correct_ligand,
nBits=4096,
fpType=type_fp,
)
mol_to_fix_fingerprint = SimilarityMaps.GetAPFingerprint(
mol_to_fix,
nBits=4096,
fpType=type_fp,
)
test = 1
sim_func = DataStructs.FingerprintSimilarity
temp_autoinducer_TanimotoSimilarty = sim_func(
correct_ligand_fingerprint,
mol_to_fix_fingerprint,
metric=DataStructs.TanimotoSimilarity)
test = 1
curr_metric = DataStructs.TanimotoSimilarity
fig, maxweight = SimilarityMaps.GetSimilarityMapForFingerprint(
correct_ligand,
mol_to_fix,
lambda m, idx: SimilarityMaps.GetAPFingerprint(
m, atomId=idx, fpType='normal'),
metric=curr_metric)
# print(maxweight)
# fig.suptitle('test title', fontsize=20)
ax = fig.gca()
# ax.title
plt.title('test', fontsize=30)
fig.set_size_inches(7, 7)
fig.set_dpi(600)
fig.savefig('test_ap.png', bbox_inches='tight')
test = 1
def testSimilarityMap(self):
# Morgan2 BV
refWeights = [0.5, 0.5, 0.5, -0.5, 0.5, 0.5]
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetMorganFingerprint(m, i, radius=2, fpType='bv'))
for w,r in zip(weights, refWeights): self.assertEqual(w, r)
fig, maxWeight = sm.GetSimilarityMapForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetMorganFingerprint(m, i, radius=2, fpType='bv'))
self.assertEqual(maxWeight, 0.5)
weights, maxWeight = sm.GetStandardizedWeights(weights)
self.assertEqual(maxWeight, 0.5)
refWeights = [1.0, 1.0, 1.0, -1.0, 1.0, 1.0]
for w,r in zip(weights, refWeights): self.assertEqual(w, r)
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetMorganFingerprint(m, i, fpType='count'))
self.assertTrue(weights[3] < 0)
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetMorganFingerprint(m, i, fpType='bv', useFeatures=True))
self.assertTrue(weights[3] < 0)
# hashed AP BV
refWeights = [0.09523, 0.17366, 0.17366, -0.23809, 0.17366, 0.17366]
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetAPFingerprint(m, i, fpType='bv', nBits=1024))
for w,r in zip(weights, refWeights): self.assertAlmostEqual(w, r, 4)
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetAPFingerprint(m, i, fpType='normal'))
self.assertTrue(weights[3] < 0)
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetAPFingerprint(m, i, fpType='hashed'))
self.assertTrue(weights[3] < 0)
# hashed TT BV
refWeights = [0.5, 0.5, -0.16666, -0.5, -0.16666, 0.5]
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetTTFingerprint(m, i, fpType='bv', nBits=1024, nBitsPerEntry=1))
for w,r in zip(weights, refWeights): self.assertAlmostEqual(w, r, 4)
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetTTFingerprint(m, i, fpType='normal'))
self.assertTrue(weights[3] < 0)
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetTTFingerprint(m, i, fpType='hashed'))
self.assertTrue(weights[3] < 0)
# RDK fingerprint BV
refWeights = [0.42105, 0.42105, 0.42105, -0.32895, 0.42105, 0.42105]
weights = sm.GetAtomicWeightsForFingerprint(self.mol1, self.mol2, lambda m, i: sm.GetRDKFingerprint(m, i, nBits=1024, nBitsPerHash=1))
for w,r in zip(weights, refWeights): self.assertAlmostEqual(w, r, 4)
def testSimilarityMapKWArgs(self):
# Morgan2 BV
m1 = Chem.MolFromSmiles('CC[C@](F)(Cl)c1ccccc1')
m2 = Chem.MolFromSmiles('CC[C@@](F)(Cl)c1ccccc1')
weights = sm.GetAtomicWeightsForFingerprint(
m1, m2, lambda m, i: sm.GetAPFingerprint(
m, atomId=i, includeChirality=False))
for w in weights:
self.assertAlmostEqual(w, 0.100, 4)
weights = sm.GetAtomicWeightsForFingerprint(
m1, m2, lambda m, i: sm.GetAPFingerprint(
m, atomId=i, includeChirality=True))
for i, w in enumerate(weights):
if i != 2:
self.assertAlmostEqual(w, 0.098, 3)
else:
self.assertAlmostEqual(w, -0.082, 3)
weights = sm.GetAtomicWeightsForFingerprint(
m1, m2, lambda m, i: sm.GetTTFingerprint(
m, atomId=i, includeChirality=False))
for w in weights:
self.assertTrue(w > 0.0)
weights = sm.GetAtomicWeightsForFingerprint(
m1, m2, lambda m, i: sm.GetTTFingerprint(
m, atomId=i, includeChirality=True))
for i, w in enumerate(weights):
if i > 4:
self.assertTrue(w > 0.0)
else:
self.assertTrue(w < 0.0)
weights = sm.GetAtomicWeightsForFingerprint(
m1, m2, lambda m, i: sm.GetMorganFingerprint(
m, radius=1, atomId=i, useChirality=False))
weights2 = sm.GetAtomicWeightsForFingerprint(
m1, m2, lambda m, i: sm.GetMorganFingerprint(
m, radius=1, atomId=i, useChirality=True))
# testing explicit values here seems silly, just check that the contribution of the
# chiral center drops:
self.assertTrue(weights[2] > weights2[2])
def draw_finger_print(smile_file):
with open(smile_file, 'r') as f:
for mol in f:
refmol = Chem.MolFromSmiles(
'CCCN(CCCCN1CCN(c2ccccc2OC)CC1)Cc1ccc2ccccc2c1'
) # this is the template here
ms = Chem.MolFromSmiles(mol)
fp = SimilarityMaps.GetAPFingerprint(ms, fpType='normal')
fp = SimilarityMaps.GetTTFingerprint(ms, fpType='normal')
fp = SimilarityMaps.GetMorganFingerprint(ms, fpType='bv')
fig, maxweight = SimilarityMaps.GetSimilarityMapForFingerprint(
refmol, ms, SimilarityMaps.GetMorganFingerprint)
fig.save('/home/nad/Desktop/navid22.png')
def fp_maps(results, query, fingerprint, fpradius, nbits, features, metric,
out_file, multfile):
if fingerprint == "ecfp" or fingerprint == "fcfp":
fp_func = lambda m, idx: SimilarityMaps.GetMorganFingerprint(
m,
atomId=idx,
radius=fpradius,
fpType='bv',
nBits=nbits,
useFeatures=features)
elif fingerprint == "rdkit":
fp_func = lambda m, idx: SimilarityMaps.GetRDKFingerprint(
m, atomId=idx, fpType="bv", nBits=nbits)
elif fingerprint == "ap":
fp_func = lambda m, idx: SimilarityMaps.GetAPFingerprint(
m, atomId=idx, fpType="bv", nBits=nbits)
else:
fp_func = lambda m, idx: SimilarityMaps.GetTTFingerprint(
m, atomId=idx, fpType="bv", nBits=nbits)
if multfile:
sim_map_mf(results, query, fp_func, metric, out_file)
else:
sim_map(results, query, fp_func, metric, out_file)
def getAtomPair(mol, nBits=1024):
return SimilarityMaps.GetAPFingerprint(mol, fpType='bv', nBits=nBits)