炼金术增强取样 (ACES) 方法提高了相对结合自由能计算的精度

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Hsu-Chun Tsai, James Xu, Zhenyu Guo, Yinhui Yi, Chuan Tian, Xinyu Que, Timothy Giese, Tai-Sung Lee, Darrin M. York*, Abir Ganguly* and Albert Pan*, 
{"title":"炼金术增强取样 (ACES) 方法提高了相对结合自由能计算的精度","authors":"Hsu-Chun Tsai,&nbsp;James Xu,&nbsp;Zhenyu Guo,&nbsp;Yinhui Yi,&nbsp;Chuan Tian,&nbsp;Xinyu Que,&nbsp;Timothy Giese,&nbsp;Tai-Sung Lee,&nbsp;Darrin M. York*,&nbsp;Abir Ganguly* and Albert Pan*,&nbsp;","doi":"10.1021/acs.jcim.4c0046410.1021/acs.jcim.4c00464","DOIUrl":null,"url":null,"abstract":"<p >Accurate <i>in silico</i> predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3–0.4 kcal/mol) and the average replicate spread by over 25% (0.2–0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":"64 18","pages":"7046–7055 7046–7055"},"PeriodicalIF":5.3000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach\",\"authors\":\"Hsu-Chun Tsai,&nbsp;James Xu,&nbsp;Zhenyu Guo,&nbsp;Yinhui Yi,&nbsp;Chuan Tian,&nbsp;Xinyu Que,&nbsp;Timothy Giese,&nbsp;Tai-Sung Lee,&nbsp;Darrin M. York*,&nbsp;Abir Ganguly* and Albert Pan*,&nbsp;\",\"doi\":\"10.1021/acs.jcim.4c0046410.1021/acs.jcim.4c00464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Accurate <i>in silico</i> predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3–0.4 kcal/mol) and the average replicate spread by over 25% (0.2–0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.</p>\",\"PeriodicalId\":44,\"journal\":{\"name\":\"Journal of Chemical Information and Modeling \",\"volume\":\"64 18\",\"pages\":\"7046–7055 7046–7055\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Chemical Information and Modeling \",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.jcim.4c00464\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jcim.4c00464","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

摘要

对小分子与蛋白质的结合强度进行精确的硅学预测,如相对结合自由能(RBFE)计算所提供的预测,可以大大提高药物发现过程中从 "命中到先导 "和 "先导优化 "阶段的效率。然而,这种计算的成功在很大程度上取决于其精确度。在这里,我们展示了最近开发的一种炼金术增强采样(ACES)方法,它可以持续提高大量不同蛋白质和小分子配体的 RBFE 计算精度。在传统的 RBFE 计算中加入 ACES 后,一组 10 个蛋白质目标和 213 个小分子的平均滞后降低了 35% 以上(0.3-0.4 kcal/mol),平均重复差降低了 25% 以上(0.2-0.3 kcal/mol),同时保持了相似或更高的精度。我们在原子细节中展示了 ACES 如何通过加强对重要的缓慢转变配体自由度的采样来改善几个代表性 RBFE 计算的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach

Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach

Accurate in silico predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3–0.4 kcal/mol) and the average replicate spread by over 25% (0.2–0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信