Parameterization and Conformational Sampling Effects in Pharmacophore Multiplet Searching
Parameterization and Conformational Sampling Effects in Pharmacophore Multiplet Searching
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DOI：
10.1021/ci800234q
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发表时间：
2008-12-01
影响因子：
5.6
通讯作者：
Clark, Robert D.
中科院分区：
文献类型：
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作者：
Fox, Peter C.;Wolohan, Philippa R. N.;Clark, Robert D.
配体中的药效团模式可以根据其组成药效团多重峰来有效地表征。编码在给定配体中发现的特定多重峰的位集（指纹）已经并继续被用作分子建模应用范围中的分子描述符，从配体比对和多样性分析到基于药效团的灵活搜索。能够以压缩形式（如位图）创建、存储和操作多元组使得将它们集成到高吞吐量技术中成为可能。许多关键参数影响多重峰的表现，包括边长分箱的粒度;在从多个配体创建假设时如何对不同的多重峰进行加权;以及药效团假设中应包含的位数。用于位图比较的相似性度量也影响搜索性能，用于表征柔性分子的构象采样制度也是如此。在这份报告中，我们探讨了参数变化对7个不同药理学类别的类内和类间相似性的影响，并介绍了一种新的分子相似性度量-不对称随机余弦-唯一适合于搜索数据库以匹配从多个配体推导出的查询假设。令人惊讶的是，事实证明，最有区别的位图是使用相对较少的构象。然而，对于单一构象所看到的极端辨别力似乎反映了所获得的3D结构的2D连接性油的一致影响。通过系统搜索进行的构象采样强化了这种间接歧视，应避免。潜在的系统性偏差变得清晰时，其他类似的构象合奏的本地能量最小化或随机采样的行为被认为是。整合来自多种已知活性物质的信息或先验地建立单一“生物活性”构象是提高药效学多重峰搜索中的辨别力的更安全的方法。
Pharmacophore patterns in ligands can be effectively characterized in terms of their constituent pharmacophore multiplets. Bitsets (fingerprints) encoding which particular multiplets are found in a given ligand have been and continue to be used as molecular descriptors in a range Of Molecular modeling applications, from ligand alignment and diversity analysis to pharmacophore-based flexible searching. Being able to create, store, and manipulate multiplets in compressed form - as bitmaps - has made it possible to integrate them into high-throughput technologies. A number of key parameters affect how well multiplets perform, including the granularity of edge length binning; how different multiplets are weighted in creating hypotheses from multiple ligands; and the number of bits that should be included in a pharmacophore hypothesis. The similarity metric employed for bitmap comparison,, also affects search performance, as does the conformational sampling regime used for characterizing flexible molecules. In this report we explore the effect of parameter variation on within- and between-class similarity across seven different pharmacological classes and introduce a new measure of molecular similarity - the asymmetric stochastic cosine - uniquely suited to searching a database for matches to query hypotheses deduced from multiple ligands. Surprisingly, it turns out that the most discriminating bitmaps are obtained Using relatively few conformers. The extreme discrimination power seen for single conformers, however, seems to reflect consistent effects of 2D connectivity oil the 3D structure obtained. Conformational sampling by systematic search reinforces such circumstantial discrimination and should be avoided. The potential for systematic bias becomes clear when the behavior of otherwise similar conformational ensembles created by local energy minimization or by random sampling is considered. Consolidating information from multiple known actives or establishing single "bioactive" conformations a priori are safer ways to improve discrimination in pharmacophoric multiplet searching.