Abstract
BiopolymersVolume 114, Issue 3 e23498 COVER IMAGEFree Access Cover Image First published: 24 March 2023 https://doi.org/10.1002/bip.23498AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Graphical Abstract Correlated mutations in a protein sequence are a hallmark of coevolution and are normally interpreted as contacts in the threedimensional structure of a protein or a protein complex. However, other factors such as function, allostery or regulatory mechanisms influence the evolutionary record of protein sequences. A new method is presented that is tuned to specifically identify such long-range evolutionary couplings by taking advantage of the recent developments in machinelearning guided protein structure prediction. DOI: 10.1002/bip.23530 Volume114, Issue3March 2023e23498 RelatedInformation
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