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共价对接在药物发现中的应用:范围与局限性。

Covalent Docking in Drug Discovery: Scope and Limitations.

机构信息

Medicinal Chemistry Research Group, Research Centre for Natural Sciences, Magyar Tudósok Korutja 2, Budapest 1117, Hungary.

出版信息

Curr Pharm Des. 2020;26(44):5684-5699. doi: 10.2174/1381612824999201105164942.

Abstract

Drug discovery efforts for new covalent inhibitors have drastically increased in the last few years. The binding mechanism of covalent compounds entails the formation of a chemical bond between their electrophilic warhead group and the protein of interest. The use of moderately reactive warheads targeting nonconserved nucleophilic residues can improve the affinity and selectivity profiles of covalent binders as compared to their non-covalent analogs. Recent advances have also enabled their use as chemical probes to disclose novel and also less tractable targets. Increasing interest in covalent drug discovery prompted the development of new computational tools, including covalent docking methods, that are available to predict the binding mode and affinity of covalent ligands. These tools integrate conventional non-covalent docking and scoring schemes by modeling the newly formed covalent bond and the interactions occurring at the reaction site. In this review, we provide a thorough analysis of state-of-the-art covalent docking programs by highlighting their main features and current limitations. Focusing on the implemented algorithms, we show the differences in handling the formation of the new covalent bond and their relative impact on the prediction. This analysis provides a comprehensive overview of the current technology and suggests future improvements in computer-aided covalent drug design. Finally, discussing successful retrospective and prospective covalent docking-based virtual screening applications, we intend to identify best practices for the drug discovery community.

摘要

在过去的几年中,针对新型共价抑制剂的药物发现工作有了显著的增加。共价化合物的结合机制涉及到它们的亲电弹头基团与靶蛋白之间形成化学键。与非共价类似物相比,使用靶向非保守亲核残基的中等反应性弹头可以提高共价结合物的亲和力和选择性。最近的进展还使它们能够用作化学探针来揭示新的、也更难处理的靶标。人们对共价药物发现的兴趣日益浓厚,促使开发了新的计算工具,包括共价对接方法,这些方法可用于预测共价配体的结合模式和亲和力。这些工具通过模拟新形成的共价键和反应部位的相互作用,整合了传统的非共价对接和评分方案。在这篇综述中,我们通过突出显示其主要特点和当前限制,对最先进的共价对接程序进行了全面分析。我们专注于实施的算法,展示了处理新共价键形成的差异及其对预测的相对影响。这种分析提供了当前技术的全面概述,并为计算机辅助共价药物设计提出了未来的改进建议。最后,通过讨论成功的基于共价对接的回溯和前瞻性虚拟筛选应用,我们旨在为药物发现界确定最佳实践。

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