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基于结构的虚拟筛选方法在激酶导向药物发现中的应用

Structure-based Virtual Screening Approaches in Kinase-directed Drug Discovery.

作者信息

Bajusz David, Ferenczy Gyorgy G, Keseru Gyorgy M

机构信息

Medicinal Chemistry Research Group, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2, Budapest 1117, Hungary.

出版信息

Curr Top Med Chem. 2017;17(20):2235-2259. doi: 10.2174/1568026617666170224121313.

Abstract

Protein kinases are one of the most targeted protein families in current drug discovery pipelines. They are implicated in many oncological, inflammatory, CNS-related and other clinical indications. Virtual screening is a computational technique with a diverse set of available tools that has been shown many times to provide novel starting points for kinase-directed drug discovery. This review starts with a concise overview of the function, structural features and inhibitory mechanisms of protein kinases. In addition to briefly reviewing the practical aspects of structure-based virtual screenings, we discuss several case studies to illustrate the state of the art in the virtual screening for type I, type II, allosteric (type III-V) and covalent (type VI) kinase inhibitors. With this review, we strive to provide a summary of the latest advances in the structure-based discovery of novel kinase inhibitors, as well as a practical tool to anyone who wishes to embark on such an endeavor.

摘要

蛋白激酶是当前药物研发流程中最具靶向性的蛋白家族之一。它们与许多肿瘤、炎症、中枢神经系统相关及其他临床适应症有关。虚拟筛选是一种拥有多种可用工具的计算技术,已多次证明可为激酶导向的药物研发提供新的起点。本文综述首先简要概述了蛋白激酶的功能、结构特征和抑制机制。除了简要回顾基于结构的虚拟筛选的实际操作方面,我们还讨论了几个案例研究,以说明I型、II型、变构(III-V型)和共价(VI型)激酶抑制剂虚拟筛选的现状。通过本综述,我们力求总结基于结构发现新型激酶抑制剂的最新进展,并为任何希望开展此类研究的人提供实用工具。

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