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一种基于受体的药物设计中提高配体选择性的新策略。

A novel strategy for improving ligand selectivity in receptor-based drug design.

作者信息

Pastor M, Cruciani G

机构信息

Department of Chemistry, University of Perugia, Italy.

出版信息

J Med Chem. 1995 Nov 10;38(23):4637-47. doi: 10.1021/jm00023a003.

Abstract

A major desirable characteristic of many drugs is their ability to interact specifically with only one variety of the target receptor among many others. It is remarkable that, even when accurate three dimensional structures for the target biomolecules are available, there is no well-established methodology to describe their differences and use them for the design of selectively-interacting compounds. This work presents a novel method that uses multivariate GRID descriptors and principal component analysis (PCA) with the aim of revealing the most relevant structural and physicochemical differences between biomacromolecules related to receptor selectivity. The methodology is described through an example involving the study of bacterial (Escherichia coli) and recombinant human varieties of the dihydrofolate reductase (EC 1.5.1.3, DHFR) enzyme. This analysis easily unveils the most important regions on these biomolecules which should be taken into consideration for the design of selectively interacting compounds.

摘要

许多药物的一个主要理想特性是它们能够仅与众多其他受体中的一种特定类型的靶标受体发生特异性相互作用。值得注意的是,即使有靶标生物分子的精确三维结构,也没有完善的方法来描述它们的差异并将其用于设计选择性相互作用的化合物。这项工作提出了一种新方法,该方法使用多元GRID描述符和主成分分析(PCA),旨在揭示与受体选择性相关的生物大分子之间最相关的结构和物理化学差异。通过一个涉及细菌(大肠杆菌)和重组人二氢叶酸还原酶(EC 1.5.1.3,DHFR)酶变体研究的例子来描述该方法。该分析很容易揭示这些生物分子上对于设计选择性相互作用化合物应予以考虑的最重要区域。

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