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通过热力学计算评估结合亲和力。

Assessment of Binding Affinity via Alchemical Free-Energy Calculations.

机构信息

Cresset, New Cambridge House, Bassingbourn Road, Litlington SG8 0SS, Cambridgeshire, U.K.

EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K.

出版信息

J Chem Inf Model. 2020 Jun 22;60(6):3120-3130. doi: 10.1021/acs.jcim.0c00165. Epub 2020 Jun 3.

Abstract

Free-energy calculations have seen increased usage in structure-based drug design. Despite the rising interest, automation of the complex calculations and subsequent analysis of their results are still hampered by the restricted choice of available tools. In this work, an application for automated setup and processing of free-energy calculations is presented. Several sanity checks for assessing the reliability of the calculations were implemented, constituting a distinct advantage over existing open-source tools. The underlying workflow is built on top of the software Sire, SOMD, BioSimSpace, and OpenMM and uses the AMBER 14SB and GAFF2.1 force fields. It was validated on two datasets originally composed by Schrödinger, consisting of 14 protein structures and 220 ligands. Predicted binding affinities were in good agreement with experimental values. For the larger dataset, the average correlation coefficient was 0.70 ± 0.05 and average Kendall's τ was 0.53 ± 0.05, which are broadly comparable to or better than previously reported results using other methods.

摘要

自由能计算在基于结构的药物设计中得到了越来越多的应用。尽管人们对此越来越感兴趣,但由于可用工具的选择有限,这些复杂计算的自动化以及对其结果的后续分析仍然受到阻碍。在这项工作中,提出了一种用于自动设置和处理自由能计算的应用程序。实现了几个用于评估计算可靠性的合理性检查,这与现有的开源工具相比具有明显的优势。基础工作流程建立在 Sire、SOMD、BioSimSpace 和 OpenMM 软件之上,并使用 AMBER 14SB 和 GAFF2.1 力场。它在最初由 Schrödinger 组成的两个数据集上进行了验证,其中包含 14 个蛋白质结构和 220 个配体。预测的结合亲和力与实验值吻合良好。对于较大的数据集,平均相关系数为 0.70 ± 0.05,平均 Kendall's τ 为 0.53 ± 0.05,与使用其他方法报告的结果大致相当或更好。

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