RDKit toolkit实战二：Generating Similarity Maps Using Fingerprints

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Linux（CentOS 7_x64位）系统下安装RDkit(修正)点击打开链接

RDKit toolkit实战演练学习一下，参考网站点击打开链接

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。

#！Python2.7from rdkit import Chemfrom rdkit.Chem import Drawfrom rdkit.Chem.Draw import SimilarityMapsmol = 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 DataStructsfig, 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)

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