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RDKit toolkit实战二:Generating Simi

RDKit toolkit实战二:Generating Simi

作者: AspirinCode | 来源:发表于2019-06-27 15:11 被阅读0次

\color{red} {相似性图是一种可视化分子与参考分子之间的相似性的原子贡献的方式。}

RDKit的rdkit.Chem.Draw.SimilarityMaps模块中提供了相关方法。

from rdkit import Chem
from rdkit.Chem import Draw
from rdkit.Chem.Draw import SimilarityMaps

mol = Chem.MolFromSmiles('COc1cccc2cc(C(=O)NCCCCN3CCN(c4cccc5nccnc54)CC3)oc21')
refmol = Chem.MolFromSmiles('CCCN(CCCCN1CCN(c2ccccc2OC)CC1)Cc1ccc2ccccc2c1')

fp = SimilarityMaps.GetAPFingerprint(mol, fpType='normal')
fp = SimilarityMaps.GetTTFingerprint(mol, fpType='normal')
fp = SimilarityMaps.GetMorganFingerprint(mol, fpType='bv')

fig, maxweight = SimilarityMaps.GetSimilarityMapForFingerprint(refmol, mol, SimilarityMaps.GetMorganFingerprint)

from rdkit import DataStructs
fig, maxweight = SimilarityMaps.GetSimilarityMapForFingerprint(refmol, mol, lambda m,idx: SimilarityMaps.GetMorganFingerprint(m, atomId=idx, radius=1, fpType='count'), metric=DataStructs.TanimotoSimilarity)

print(maxweight)
weights = SimilarityMaps.GetAtomicWeightsForFingerprint(refmol, mol, SimilarityMaps.GetMorganFingerprint)
print(["%.2f " % w for w in weights])
fig = SimilarityMaps.GetSimilarityMapFromWeights(mol, weights)

\color{blue} {Jupyter Notebooks效果}

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\color{green} {参考}

https://blog.csdn.net/u012325865/article/details/78396087

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