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自由威尔逊选择性分析在组合文库设计中的应用。

Application of Free-Wilson selectivity analysis for combinatorial library design.

作者信息

Sciabola Simone, Stanton Robert V, Johnson Theresa L, Xi Hualin

机构信息

Pfizer Research Technology Center, Cambridge, MA, USA.

出版信息

Methods Mol Biol. 2011;685:91-109. doi: 10.1007/978-1-60761-931-4_5.

Abstract

In this chapter we present an application of in silico quantitative structure-activity relationship (QSAR) models to establish a new ligand-based computational approach for generating virtual libraries. The Free-Wilson methodology was applied to extract rules from two data sets containing compounds which were screened against either kinase or PDE gene family panels. The rules were used to make predictions for all compounds enumerated from their respective virtual libraries. We also demonstrate the construction of R-group selectivity profiles by deriving activity contributions against each protein target using the QSAR models. Such selectivity profiles were used together with protein structural information from X-ray data to provide a better understanding of the subtle selectivity relationships between kinase and PDE family members.

摘要

在本章中,我们展示了计算机辅助定量构效关系(QSAR)模型的一种应用,以建立一种基于配体的新计算方法来生成虚拟库。应用Free-Wilson方法从两个数据集提取规则,这两个数据集包含针对激酶或磷酸二酯酶(PDE)基因家族筛选的化合物。这些规则用于对从各自虚拟库中列举出的所有化合物进行预测。我们还通过使用QSAR模型推导针对每个蛋白质靶点的活性贡献,展示了R基团选择性图谱的构建。这些选择性图谱与来自X射线数据的蛋白质结构信息一起使用,以更好地理解激酶和PDE家族成员之间微妙的选择性关系。

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