{"title":"描述分子过程的自由能方法。","authors":"Christophe Chipot","doi":"10.1146/annurev-biophys-062722-093258","DOIUrl":null,"url":null,"abstract":"<p><p>Efforts to combine theory and experiment to advance our knowledge of molecular processes relevant to biophysics have been considerably enhanced by the contribution of statistical-mechanics simulations. Key to the understanding of such molecular processes is the underlying free-energy change. Being able to accurately predict this change from first principles represents an appealing prospect. Over the past decades, the synergy between steadily growing computational resources and unrelenting methodological developments has brought free-energy calculations into the arsenal of tools commonly utilized to tackle important questions that experiment alone has left unresolved. The continued emergence of new options to determine free energies has also bred confusion amid the community of users, who may find it difficult to choose the best-suited algorithm to address the problem at hand. In an attempt to clarify the current landscape, this review recounts how the field has been shaped and how the broad gamut of methods available today is rooted in a few foundational principles laid down many years ago.Three examples of molecular processes central to biophysics illustrate where free-energy calculations stand and what are the conceptual and practical obstacles that we must overcome to increase their predictive power.</p>","PeriodicalId":50756,"journal":{"name":"Annual Review of Biophysics","volume":null,"pages":null},"PeriodicalIF":10.4000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Free Energy Methods for the Description of Molecular Processes.\",\"authors\":\"Christophe Chipot\",\"doi\":\"10.1146/annurev-biophys-062722-093258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Efforts to combine theory and experiment to advance our knowledge of molecular processes relevant to biophysics have been considerably enhanced by the contribution of statistical-mechanics simulations. Key to the understanding of such molecular processes is the underlying free-energy change. Being able to accurately predict this change from first principles represents an appealing prospect. Over the past decades, the synergy between steadily growing computational resources and unrelenting methodological developments has brought free-energy calculations into the arsenal of tools commonly utilized to tackle important questions that experiment alone has left unresolved. The continued emergence of new options to determine free energies has also bred confusion amid the community of users, who may find it difficult to choose the best-suited algorithm to address the problem at hand. In an attempt to clarify the current landscape, this review recounts how the field has been shaped and how the broad gamut of methods available today is rooted in a few foundational principles laid down many years ago.Three examples of molecular processes central to biophysics illustrate where free-energy calculations stand and what are the conceptual and practical obstacles that we must overcome to increase their predictive power.</p>\",\"PeriodicalId\":50756,\"journal\":{\"name\":\"Annual Review of Biophysics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.4000,\"publicationDate\":\"2023-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Biophysics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-biophys-062722-093258\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Biophysics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1146/annurev-biophys-062722-093258","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOPHYSICS","Score":null,"Total":0}
Free Energy Methods for the Description of Molecular Processes.
Efforts to combine theory and experiment to advance our knowledge of molecular processes relevant to biophysics have been considerably enhanced by the contribution of statistical-mechanics simulations. Key to the understanding of such molecular processes is the underlying free-energy change. Being able to accurately predict this change from first principles represents an appealing prospect. Over the past decades, the synergy between steadily growing computational resources and unrelenting methodological developments has brought free-energy calculations into the arsenal of tools commonly utilized to tackle important questions that experiment alone has left unresolved. The continued emergence of new options to determine free energies has also bred confusion amid the community of users, who may find it difficult to choose the best-suited algorithm to address the problem at hand. In an attempt to clarify the current landscape, this review recounts how the field has been shaped and how the broad gamut of methods available today is rooted in a few foundational principles laid down many years ago.Three examples of molecular processes central to biophysics illustrate where free-energy calculations stand and what are the conceptual and practical obstacles that we must overcome to increase their predictive power.
期刊介绍:
The Annual Review of Biophysics, in publication since 1972, covers significant developments in the field of biophysics, including macromolecular structure, function and dynamics, theoretical and computational biophysics, molecular biophysics of the cell, physical systems biology, membrane biophysics, biotechnology, nanotechnology, and emerging techniques.