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用于蛋白质-配体结合预测的自由能计算

Free Energy Calculations for Protein-Ligand Binding Prediction.

作者信息

Jespers Willem, Åqvist Johan, Gutiérrez-de-Terán Hugo

机构信息

Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Uppsala, Sweden.

出版信息

Methods Mol Biol. 2021;2266:203-226. doi: 10.1007/978-1-0716-1209-5_12.

Abstract

Computational prediction of protein-ligand binding involves initial determination of the binding mode and subsequent evaluation of the strength of the protein-ligand interactions, which directly correlates with ligand binding affinities. As a consequence of increasing computer power, rigorous approaches to calculate protein-ligand binding affinities, such as free energy perturbation (FEP) methods, are becoming an essential part of the toolbox of computer-aided drug design. In this chapter, we provide a general overview of these methods and introduce the QFEP modules, which are open-source API workflows based on our molecular dynamics (MD) package Q. The module QligFEP allows estimation of relative binding affinities along ligand series, while QresFEP is a module to estimate binding affinity shifts caused by single-point mutations of the protein. We herein provide guidelines for the use of each of these modules based on data extracted from ligand-design projects. While these modules are stand-alone, the combined use of the two workflows in a drug-design project yields complementary perspectives of the ligand binding problem, providing two sides of the same coin. The selected case studies illustrate how to use QFEP to approach the two key questions associated with ligand binding prediction: identifying the most favorable binding mode from different alternatives and establishing structure-affinity relationships that allow the rational optimization of hit compounds.

摘要

蛋白质-配体结合的计算预测涉及结合模式的初步确定以及随后对蛋白质-配体相互作用强度的评估,而这种相互作用强度与配体结合亲和力直接相关。随着计算机性能的提升,诸如自由能微扰(FEP)方法等用于计算蛋白质-配体结合亲和力的严格方法,正成为计算机辅助药物设计工具库的重要组成部分。在本章中,我们对这些方法进行了总体概述,并介绍了QFEP模块,它是基于我们的分子动力学(MD)软件包Q的开源API工作流程。QligFEP模块可用于估计配体系列的相对结合亲和力,而QresFEP模块则用于估计由蛋白质单点突变引起的结合亲和力变化。我们在此根据从配体设计项目中提取的数据,为每个模块的使用提供指导。虽然这些模块是独立的,但在药物设计项目中联合使用这两个工作流程,可以从互补的角度看待配体结合问题,可谓是同一枚硬币的两面。所选的案例研究说明了如何使用QFEP来解决与配体结合预测相关的两个关键问题:从不同的备选方案中识别出最有利的结合模式,以及建立结构-亲和力关系以实现对先导化合物的合理优化。

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