Integrating computational and mixture-based screening of combinatorial libraries.
Integrating computational and mixture-based screening of combinatorial libraries.
复制标题
集成组合文库的计算和基于混合物的筛选。
DOI：
10.1007/s00894-010-0850-1
复制
发表时间：
2011
影响因子：
2.2
通讯作者：
Martínez-Mayorga,Karina
中科院分区：
文献类型：
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作者：
Yongye,AustinB;Pinilla,Clemencia;Medina-Franco,JoseL;Giulianotti,MarcA;Dooley,ColetteT;Appel,JonR;Nefzi,Adel;Scior,Thomas;Houghten,RichardA;Martínez-Mayorga,Karina
基于混合物的合成组合文库（MB-SCL）筛选是一种成熟的快速检索构效关系（SAR）和识别命中的实验方法。虚拟筛选也是一种强大的方法，越来越多地用于药物发现计划，并有越来越多的成功应用。然而，在整合这两种技术方面所做的努力有限。为此，我们结合了来自针对κ-阿片受体筛选的双环胍的MB-SCL的实验数据和分子相似性方法。将活动数据和相似性分析集成在生物特征分析相似性图中。这种图谱允许将分子分类为活性物质、活性悬崖、与参比化合物的低相似性或错过的命中。在“遗漏命中”区域中发现了IC 50 = 309 nM的化合物，表明活性化合物可以通过计算方法从MS-SCL中检索。在这项工作中提出的策略是一般性的，并设想作为一个通用的方法，可以应用到其他MB-SCLs.Mixture-based筛选活性数据和分子相似性比较已知的活性化合物集成通过生物统计分析相似性地图，以确定在何种程度上分子相似性方法可以挽救错过的命中从混合物为基础的筛选合成组合库。
Mixture-based synthetic combinatorial library (MB-SCL) screening is a well-established experimental approach for rapidly retrieving structure–activity relationships (SAR) and identifying hits. Virtual screening is also a powerful approach that is increasingly being used in drug discovery programs and has a growing number of successful applications. However, limited efforts have been made to integrate both techniques. To this end, we combined experimental data from a MB-SCL of bicyclic guanidines screened against the κ-opioid receptor and molecular similarity methods. The activity data and similarity analyses were integrated in a biometric analysis–similarity map. Such a map allows the molecules to be categorized as actives, activity cliffs, low similarity to the reference compounds, or missed hits. A compound with IC50= 309 nM was found in the “missed hits” region, showing that active compounds can be retrieved from a MS-SCL via computational approaches. The strategy presented in this work is general and is envisioned as a general-purpose approach that can be applied to other MB-SCLs.Mixture-based screening activity data and molecular similarity comparisons to known active compounds are integrated via abiometrical analysis-similarity map, to determine the extent to which molecular similarity methods can rescue missed hits from a mixture-based screening synthetic combinatorial library.