Protein Electrostatic Properties are Fine-Tuned Through Evolution

Protein Electrostatic Properties are Fine-Tuned Through Evolution | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Protein Electrostatic Properties are Fine-Tuned Through Evolution Jana Shen, Mingzhe Shen, Guy Dayhoff II This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6471091/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Protein ionization states provide electrostatic forces to modulate protein structure, stability, solubility, and function. Until now, predicting ionization states and understanding protein electrostatics have relied on structural information. Here we demonstrate that primary sequence alone enables remarkably accurate pKa predictions through KaML-ESM, a model that leverages evolutionary representations from ultra-large protein language models ESMs and pretraining with a synthetic pKa dataset. The KaML-ESM model achieves RMSEs approaching the experimental precision limit of 0.5 pH units for Asp, Glu, His, and Lys residues, while reducing Cys prediction errors to 1.1 units – with further improvement expected as the training dataset expands. The state-of-the-art performance of KaML-ESM was further validated through external evaluations, including a proteome-wide analysis of protein pKa values. Our results support the notation that protein sequence encodes not only structure and function but also electrostatic properties, which may have been co-optimized through evolution. Lastly, we provide KaML, a sequence-based end-toend ML platform that enables researchers to map protein electrostatic landscapes, facilitating applications ranging from drug design and protein engineering to molecular simulations. Biological sciences/Biophysics/Computational biophysics Biological sciences/Computational biology and bioinformatics/Machine learning Full Text Additional Declarations There is NO Competing Interest. Supplementary Files KaMLESMSIsubmit.pdf Supporting Information Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6471091","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":448128275,"identity":"6c722abb-103e-4ced-ada7-b01d7ec255f7","order_by":0,"name":"Jana Shen","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-3234-0769","institution":"University of Maryland School of Pharmacy","correspondingAuthor":true,"prefix":"","firstName":"Jana","middleName":"","lastName":"Shen","suffix":""},{"id":448128276,"identity":"dfb47bad-6838-40db-9ea6-929cf9f9304b","order_by":1,"name":"Mingzhe Shen","email":"","orcid":"","institution":"University of Maryland School of Pharmacy","correspondingAuthor":false,"prefix":"","firstName":"Mingzhe","middleName":"","lastName":"Shen","suffix":""},{"id":448128277,"identity":"e39b8beb-27b7-4a88-9d18-427d1b445290","order_by":2,"name":"Guy Dayhoff II","email":"","orcid":"","institution":"University of Maryland School of Pharmacy","correspondingAuthor":false,"prefix":"","firstName":"Guy","middleName":"Dayhoff","lastName":"II","suffix":""}],"badges":[],"createdAt":"2025-04-17 11:05:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6471091/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6471091/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88474797,"identity":"4131e2c8-57ef-4d86-923e-ba62cac5fc3a","added_by":"auto","created_at":"2025-08-06 20:44:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":912017,"visible":true,"origin":"","legend":"Article File","description":"","filename":"KaMLESMsubmit.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6471091/v1_covered_32d85afb-5ea2-4e66-aed9-b85343e5286e.pdf"},{"id":81498561,"identity":"4955debd-e2c0-462d-88f7-06f3e8fde462","added_by":"auto","created_at":"2025-04-28 03:12:32","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4314443,"visible":true,"origin":"","legend":"Supporting Information","description":"","filename":"KaMLESMSIsubmit.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6471091/v1/bf064827801e163127372b16.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Protein Electrostatic Properties are Fine-Tuned Through Evolution","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6471091/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6471091/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Protein ionization states provide electrostatic forces to modulate protein structure, stability, solubility, and function. 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