A Computational Atlas of Mutational Vulnerability Highlights Convergent Prion-Like and Aggregation-Associated Features in Neurodegenerative Proteins

A Computational Atlas of Mutational Vulnerability Highlights Convergent Prion-Like and Aggregation-Associated Features in Neurodegenerative Proteins | 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 Research Article A Computational Atlas of Mutational Vulnerability Highlights Convergent Prion-Like and Aggregation-Associated Features in Neurodegenerative Proteins Yathu Krishna Y K This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8576121/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cross-protein mutational susceptibility is not well understood, despite the fact that neurodegenerative diseases are caused by the misfolding, aggregation, and functional disruption of several proteins. Integrative analyses that combine mutational susceptibility patterns across several proteins implicated in neurodegenerative illness are lacking, despite the fact that prior research has concentrated on specific disease-associated proteins. Here, we offer a computational atlas of mutational vulnerability that includes 22 proteins associated with important neurodegenerative diseases, such as spinocerebellar ataxias, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.We conducted a cross-protein comparative analysis to find regions that are disproportionately sensitive to amino acid substitutions using curated human variant data from UniProt, prion-like domain predictions, sequence-derived mutational sensitivity profiling, and aggregation-prone region mapping. Several structurally and functionally diverse proteins, many of which are still underrepresented in naturally occurring human variation, share susceptibility regions, as our results demonstrate. Specifically, proteins like ATXN2, OPTN, and MATR3 show strong mutational sensitivity and little overlap with known human variants, indicating unknown loci with potentially harmful effects. Furthermore, mechanistic connections between intrinsic sequence instability and pathological misfolding are strengthened by the selective enrichment of susceptible residues in prion-like and aggregation-prone areas. A resource for prioritizing proteins and regions for mutational screening, structural biophysics, and therapeutic targeting is provided by this study, which unifies mutational, structural, and aggregation-prone characteristics into a unified framework. In addition to confirming established risk loci, the cross-protein mutational vulnerability atlas identifies obscure locations that require more investigation. More generally, our method creates a scalable framework for mapping sequence-derived susceptibility across protein families, providing a link between mechanistic understanding of the causes of neurodegeneration and computational predictions. This study offers a strategic roadmap for upcoming experimental and translational research in neurodegenerative illnesses and emphasizes the value of integrative, multi-protein investigations in comprehending disease causation. All findings are derived from computational analyses and are intended to guide, rather than replace, experimental validation. Computational Neuroscience Bioinformatics Computational Biology General Biochemistry Systems Biology neurodegeneration protein aggregation mutational vulnerability prion-like domains sequence hotspots computational biology UniProt variants Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8576121","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":572881255,"identity":"9e6747b1-0122-446c-b6fb-2479acde42e9","order_by":0,"name":"Yathu Krishna Y 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Integrative analyses that combine mutational susceptibility patterns across several proteins implicated in neurodegenerative illness are lacking, despite the fact that prior research has concentrated on specific disease-associated proteins. Here, we offer a computational atlas of mutational vulnerability that includes 22 proteins associated with important neurodegenerative diseases, such as spinocerebellar ataxias, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.We conducted a cross-protein comparative analysis to find regions that are disproportionately sensitive to amino acid substitutions using curated human variant data from UniProt, prion-like domain predictions, sequence-derived mutational sensitivity profiling, and aggregation-prone region mapping. Several structurally and functionally diverse proteins, many of which are still underrepresented in naturally occurring human variation, share susceptibility regions, as our results demonstrate. Specifically, proteins like ATXN2, OPTN, and MATR3 show strong mutational sensitivity and little overlap with known human variants, indicating unknown loci with potentially harmful effects. Furthermore, mechanistic connections between intrinsic sequence instability and pathological misfolding are strengthened by the selective enrichment of susceptible residues in prion-like and aggregation-prone areas. A resource for prioritizing proteins and regions for mutational screening, structural biophysics, and therapeutic targeting is provided by this study, which unifies mutational, structural, and aggregation-prone characteristics into a unified framework. In addition to confirming established risk loci, the cross-protein mutational vulnerability atlas identifies obscure locations that require more investigation. 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