MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs

相似性(几何) 悬崖 基础(线性代数) 合并(版本控制) 结构相似性 计算机科学 下部结构 人工智能 化学 计算生物学 情报检索 数学 地质学 生物 图像(数学) 工程类 古生物学 几何学 结构工程
作者
Xiaoying Hu,Ye Hu,Martin Vogt,Dagmar Stumpfe,Jürgen Bajorath
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:52 (5): 1138-1145 被引量:205
标识
DOI:10.1021/ci3001138
摘要

Activity cliffs are generally defined as pairs of structurally similar compounds having large differences in potency. The analysis of activity cliffs is of general interest because structure-activity relationship (SAR) determinants can often be deduced from them. Critical questions for the study of activity cliffs include how similar compounds should be to qualify as cliff partners, how similarity should be assessed, and how large potency differences between participating compounds should be. Thus far, activity cliffs have mostly been defined on the basis of calculated Tanimoto similarity values using structural descriptors, especially 2D fingerprints. As any theoretical assessment of molecular similarity, this approach has its limitations. For example, calculated Tanimoto similarities might often be difficult to reconcile and interpret from a chemical perspective, a point of critique frequently raised in medicinal chemistry. Herein, we have explored activity cliffs by considering well-defined substructure replacements instead of calculated similarity values. For this purpose, the matched molecular pair (MMP) formalism has been applied. MMPs were systematically derived from public domain compounds, and activity cliffs were extracted from them, termed MMP-cliffs. The frequency of cliff formation was determined for compounds active against different targets, MMP-cliffs were analyzed in detail, and re-evaluated on the basis of Tanimoto similarity. In many instances, chemically intuitive activity cliffs were only detected on the basis of MMPs, but not Tanimoto similarity.
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