Assessment of Binding Affinity via Alchemical Free-Energy Calculations

被引:128
|
作者
Kuhn, Maximilian [1 ,2 ]
Firth-Clark, Stuart [1 ]
Tosco, Paolo [1 ]
Mey, Antonia S. J. S. [2 ]
Mackey, Mark [1 ]
Michel, Julien [2 ]
机构
[1] Cresset, Litlington SG8 0SS, Cambs, England
[2] Univ Edinburgh, EaStCHEM Sch Chem, Edinburgh EH9 3FJ, Midlothian, Scotland
基金
英国工程与自然科学研究理事会; “创新英国”项目;
关键词
DRUG DISCOVERY; BLINDED PREDICTIONS; MOLECULAR-DYNAMICS; KINASE INHIBITORS; LEAD OPTIMIZATION; BACE1; INHIBITORS; POTENT; IDENTIFICATION; ACCURATE; FIELD;
D O I
10.1021/acs.jcim.0c00165
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
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 Schrodinger, 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 R-p was 0.70 +/- 0.05 and average Kendall's tau was 0.53 +/- 0.05, which are broadly comparable to or better than previously reported results using other methods.
引用
收藏
页码:3120 / 3130
页数:11
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