用于药物发现的绝对结合自由能自动计算工作流程。

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-07-01 DOI:10.1021/acs.jcim.4c00343
Benjamin Ries, Irfan Alibay, Nithishwer Mouroug Anand, Philip C Biggin, Aniket Magarkar
{"title":"用于药物发现的绝对结合自由能自动计算工作流程。","authors":"Benjamin Ries, Irfan Alibay, Nithishwer Mouroug Anand, Philip C Biggin, Aniket Magarkar","doi":"10.1021/acs.jcim.4c00343","DOIUrl":null,"url":null,"abstract":"<p><p>Absolute binding free energies play a crucial role in drug development, particularly as part of the lead discovery process. In recent work, we showed how <i>in silico</i> predictions directly could support drug development by ranking and recommending favorable ideas over unfavorable ones. Here, we demonstrate a Python workflow that enables the calculation of ABFEs with minimal manual input effort, such as the receptor PDB and ligand SDF files, and outputs a .tsv file containing the ranked ligands and their corresponding binding free energies. The implementation uses Snakemake to structure and control the execution of tasks, allowing for dynamic control of parameters and execution patterns. We provide an example of a benchmark system that demonstrates the effectiveness of the automated workflow.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Absolute Binding Free Energy Calculation Workflow for Drug Discovery.\",\"authors\":\"Benjamin Ries, Irfan Alibay, Nithishwer Mouroug Anand, Philip C Biggin, Aniket Magarkar\",\"doi\":\"10.1021/acs.jcim.4c00343\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Absolute binding free energies play a crucial role in drug development, particularly as part of the lead discovery process. In recent work, we showed how <i>in silico</i> predictions directly could support drug development by ranking and recommending favorable ideas over unfavorable ones. Here, we demonstrate a Python workflow that enables the calculation of ABFEs with minimal manual input effort, such as the receptor PDB and ligand SDF files, and outputs a .tsv file containing the ranked ligands and their corresponding binding free energies. The implementation uses Snakemake to structure and control the execution of tasks, allowing for dynamic control of parameters and execution patterns. We provide an example of a benchmark system that demonstrates the effectiveness of the automated workflow.</p>\",\"PeriodicalId\":44,\"journal\":{\"name\":\"Journal of Chemical Information and Modeling \",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2024-07-01\",\"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://doi.org/10.1021/acs.jcim.4c00343\",\"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://doi.org/10.1021/acs.jcim.4c00343","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

绝对结合自由能在药物研发中发挥着至关重要的作用,尤其是作为先导药物发现过程的一部分。在最近的工作中,我们展示了如何通过将有利的想法与不利的想法进行排序和推荐,直接进行硅学预测,从而为药物开发提供支持。在这里,我们展示了一个 Python 工作流程,它能以最少的人工输入(如受体 PDB 和配体 SDF 文件)计算 ABFEs,并输出一个包含排序配体及其相应结合自由能的 .tsv 文件。实施过程使用 Snakemake 来构建和控制任务的执行,从而实现对参数和执行模式的动态控制。我们提供了一个基准系统示例,展示了自动化工作流程的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Automated Absolute Binding Free Energy Calculation Workflow for Drug Discovery.

Absolute binding free energies play a crucial role in drug development, particularly as part of the lead discovery process. In recent work, we showed how in silico predictions directly could support drug development by ranking and recommending favorable ideas over unfavorable ones. Here, we demonstrate a Python workflow that enables the calculation of ABFEs with minimal manual input effort, such as the receptor PDB and ligand SDF files, and outputs a .tsv file containing the ranked ligands and their corresponding binding free energies. The implementation uses Snakemake to structure and control the execution of tasks, allowing for dynamic control of parameters and execution patterns. We provide an example of a benchmark system that demonstrates the effectiveness of the automated workflow.

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.
期刊最新文献
Riboflavin-Induced DNA Damage and Anticancer Activity in Breast Cancer Cells under Visible Light: A TD-DFT and In Vitro Study. DeltaGzip: Computing Biopolymer-Ligand Binding Affinity via Kolmogorov Complexity and Lossless Compression. Enhancing Chemical Reaction Monitoring with a Deep Learning Model for NMR Spectra Image Matching to Target Compounds. CageCavityCalc (C3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages AttenGpKa: A Universal Predictor of Solvation Acidity Using Graph Neural Network and Molecular Topology.
×
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
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