Extracting Atomic Contributions to Binding Free Energy Using Molecular Dynamics Simulations with Mixed Solvents (MDmix).

Q3 Pharmacology, Toxicology and Pharmaceutics Current drug discovery technologies Pub Date : 2022-01-01 DOI:10.2174/1570163819666211223162829
Daniel Alvarez-Garcia, Peter Schmidtke, Elena Cubero, Xavier Barril
{"title":"Extracting Atomic Contributions to Binding Free Energy Using Molecular Dynamics Simulations with Mixed Solvents (MDmix).","authors":"Daniel Alvarez-Garcia,&nbsp;Peter Schmidtke,&nbsp;Elena Cubero,&nbsp;Xavier Barril","doi":"10.2174/1570163819666211223162829","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Mixed solvents MD (MDmix) simulations have proved to be a useful and increasingly accepted technique with several applications in structure-based drug discovery. One of the assumptions behind the methodology is the transferability of free energy values from the simulated cosolvent molecules to larger drug-like molecules. However, the binding free energy maps (ΔGbind) calculated for the different moieties of the cosolvent molecules (e.g. a hydroxyl map for the ethanol) are largely influenced by the rest of the solvent molecule and do not reflect the intrinsic affinity of the moiety in question. As such, they are hardly transferable to different molecules.</p><p><strong>Method: </strong>To achieve transferable energies, we present here a method for decomposing the molecular binding free energy into accurate atomic contributions.</p><p><strong>Result: </strong>We demonstrate with two qualitative visual examples how the corrected energy maps better match known binding hotspots and how they can reveal hidden hotspots with actual drug design potential.</p><p><strong>Conclusion: </strong>Atomic decomposition of binding free energies derived from MDmix simulations provides transferable and quantitative binding free energy maps.</p>","PeriodicalId":10858,"journal":{"name":"Current drug discovery technologies","volume":"19 2","pages":"62-68"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/4d/ee/CDDT-19-231221199369.PMC9906626.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current drug discovery technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1570163819666211223162829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 1

Abstract

Background: Mixed solvents MD (MDmix) simulations have proved to be a useful and increasingly accepted technique with several applications in structure-based drug discovery. One of the assumptions behind the methodology is the transferability of free energy values from the simulated cosolvent molecules to larger drug-like molecules. However, the binding free energy maps (ΔGbind) calculated for the different moieties of the cosolvent molecules (e.g. a hydroxyl map for the ethanol) are largely influenced by the rest of the solvent molecule and do not reflect the intrinsic affinity of the moiety in question. As such, they are hardly transferable to different molecules.

Method: To achieve transferable energies, we present here a method for decomposing the molecular binding free energy into accurate atomic contributions.

Result: We demonstrate with two qualitative visual examples how the corrected energy maps better match known binding hotspots and how they can reveal hidden hotspots with actual drug design potential.

Conclusion: Atomic decomposition of binding free energies derived from MDmix simulations provides transferable and quantitative binding free energy maps.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用混合溶剂(MDmix)分子动力学模拟提取原子对结合自由能的贡献。
背景:混合溶剂MD (MDmix)模拟已被证明是一种有用且越来越被接受的技术,在基于结构的药物发现中有几种应用。该方法背后的一个假设是自由能值从模拟的共溶剂分子转移到更大的类药物分子。然而,为共溶剂分子的不同部分计算的结合自由能图(ΔGbind)(例如乙醇的羟基图)在很大程度上受到溶剂分子其余部分的影响,并不能反映所讨论的部分的内在亲和力。因此,它们很难转移到不同的分子中。方法:为了获得可转移的能量,我们提出了一种将分子结合自由能分解成精确的原子贡献的方法。结果:我们用两个定性的视觉例子证明了修正后的能量图如何更好地匹配已知的结合热点,以及它们如何揭示具有实际药物设计潜力的隐藏热点。结论:由MDmix模拟得到的结合自由能的原子分解提供了可转移和定量的结合自由能图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Current drug discovery technologies
Current drug discovery technologies Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
3.70
自引率
0.00%
发文量
48
期刊介绍: Due to the plethora of new approaches being used in modern drug discovery by the pharmaceutical industry, Current Drug Discovery Technologies has been established to provide comprehensive overviews of all the major modern techniques and technologies used in drug design and discovery. The journal is the forum for publishing both original research papers and reviews describing novel approaches and cutting edge technologies used in all stages of drug discovery. The journal addresses the multidimensional challenges of drug discovery science including integration issues of the drug discovery process.
期刊最新文献
Harnessing the Therapeutic Potential of Dillenia indica: An Overview of Recent Dosage Form Developments. New 1,3,4‒oxadiazole Quinazolines as Potential Anticancer Agents: Design, Synthesis, Biological Evaluation, and In silico Studies. Nanoencapsulation of Ruthenium Complex Ru(ThySMet): A Strategy to Improve Selective Cytotoxicity against Breast Tumor Cells in 2D and 3D Culture Models. CBD: A Potential Lead against Hair Loss, Alopecia, and its Potential Mechanisms. The Nanotech Potential of Curcumin in Pharmaceuticals: An Overview.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1