Timothy J. Giese, Ryan Snyder, Zeke Piskulich, German P. Barletta, Shi Zhang, Erika McCarthy, Şölen Ekesan and Darrin M. York*,
{"title":"FE-ToolKit:一个多功能软件套件,用于分析高维自由能表面和炼金术自由能网络","authors":"Timothy J. Giese, Ryan Snyder, Zeke Piskulich, German P. Barletta, Shi Zhang, Erika McCarthy, Şölen Ekesan and Darrin M. York*, ","doi":"10.1021/acs.jcim.5c0055410.1021/acs.jcim.5c00554","DOIUrl":null,"url":null,"abstract":"<p >Free energy simulations play a pivotal role in diverse biological applications, including enzyme design, drug discovery, and biomolecular engineering. The characterization of high-dimensional free energy surfaces underlying complex enzymatic mechanisms necessitates extensive sampling through umbrella sampling or string method simulations. Accurate ranking of target-binding free energies across large ligand libraries relies on comprehensive alchemical free energy calculations organized into thermodynamic networks. The predictive accuracy of these methods hinges on robust, scalable tools for networkwide data analysis and extraction of physical properties from heterogeneous simulation data. Here, we introduce <span>FE-ToolKit</span>, a versatile software suite for the automated analysis of free energy surfaces, minimum free energy paths, and alchemical free energy networks (thermodynamic graphs).</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":"65 11","pages":"5273–5279 5273–5279"},"PeriodicalIF":5.3000,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FE-ToolKit: A Versatile Software Suite for Analysis of High-Dimensional Free Energy Surfaces and Alchemical Free Energy Networks\",\"authors\":\"Timothy J. Giese, Ryan Snyder, Zeke Piskulich, German P. Barletta, Shi Zhang, Erika McCarthy, Şölen Ekesan and Darrin M. York*, \",\"doi\":\"10.1021/acs.jcim.5c0055410.1021/acs.jcim.5c00554\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Free energy simulations play a pivotal role in diverse biological applications, including enzyme design, drug discovery, and biomolecular engineering. The characterization of high-dimensional free energy surfaces underlying complex enzymatic mechanisms necessitates extensive sampling through umbrella sampling or string method simulations. Accurate ranking of target-binding free energies across large ligand libraries relies on comprehensive alchemical free energy calculations organized into thermodynamic networks. The predictive accuracy of these methods hinges on robust, scalable tools for networkwide data analysis and extraction of physical properties from heterogeneous simulation data. Here, we introduce <span>FE-ToolKit</span>, a versatile software suite for the automated analysis of free energy surfaces, minimum free energy paths, and alchemical free energy networks (thermodynamic graphs).</p>\",\"PeriodicalId\":44,\"journal\":{\"name\":\"Journal of Chemical Information and Modeling \",\"volume\":\"65 11\",\"pages\":\"5273–5279 5273–5279\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2025-05-20\",\"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.5c00554\",\"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.5c00554","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
FE-ToolKit: A Versatile Software Suite for Analysis of High-Dimensional Free Energy Surfaces and Alchemical Free Energy Networks
Free energy simulations play a pivotal role in diverse biological applications, including enzyme design, drug discovery, and biomolecular engineering. The characterization of high-dimensional free energy surfaces underlying complex enzymatic mechanisms necessitates extensive sampling through umbrella sampling or string method simulations. Accurate ranking of target-binding free energies across large ligand libraries relies on comprehensive alchemical free energy calculations organized into thermodynamic networks. The predictive accuracy of these methods hinges on robust, scalable tools for networkwide data analysis and extraction of physical properties from heterogeneous simulation data. Here, we introduce FE-ToolKit, a versatile software suite for the automated analysis of free energy surfaces, minimum free energy paths, and alchemical free energy networks (thermodynamic graphs).
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.