Computational Design of a Multi-Epitope Peptide Vaccine Against the Opportunistic Fungus Aspergillus fumigatus in Lung Cancer Patients

Computational Design of a Multi-Epitope Peptide Vaccine Against the Opportunistic Fungus Aspergillus fumigatus in Lung Cancer Patients | 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 Computational Design of a Multi-Epitope Peptide Vaccine Against the Opportunistic Fungus Aspergillus fumigatus in Lung Cancer Patients Syed Arslan Haider, Prince Danan Biniyam, Isfa Sarfraz, Muhammad Nouman Majeed, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8141196/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 Opportunistic Aspergillus fumigatus infections pose a serious threat to immunocompromised individuals, particularly lung cancer patients undergoing chemotherapy or immunosuppressive therapy. This study reports the in-silico design of a multi-epitope peptide vaccine targeting two extracellular cell-wall enzymes, Crh-like protein 5 and 1,3-β-glucanosyltransferase, identified through proteome screening and subcellular localization analysis. Linear and conformational B-cell, CTL, and HTL epitopes were predicted and filtered for antigenicity, non-allergenicity, and non-toxicity, yielding six rationally assembled constructs with suitable adjuvants and linkers. Molecular docking with TLR5 and HLA-DR1, followed by structural validation and physicochemical profiling, identified Construct-3 as the most stable and antigenic (VaxiJen = 1.16, non-allergenic, non-toxic). Molecular dynamics simulations (100 ns) confirmed stable receptor binding with minimal conformational fluctuations, and population-coverage analysis predicted ~ 59% global HLA representation. These results highlight Construct-3 as a structurally validated and immunogenically robust vaccine candidate warranting experimental evaluation against A. fumigatus in lung cancer patients. Biological sciences/Biotechnology Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Biological sciences/Drug discovery Biological sciences/Immunology Biological sciences/Microbiology Full Text Additional Declarations No competing interests reported. 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-8141196","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":557834603,"identity":"5a27a324-04ad-408f-8acb-3431fff28f79","order_by":0,"name":"Syed Arslan Haider","email":"","orcid":"","institution":"University of Okara","correspondingAuthor":false,"prefix":"","firstName":"Syed","middleName":"Arslan","lastName":"Haider","suffix":""},{"id":557834604,"identity":"0c23fdb9-2318-4e17-a428-cfd43528c3dc","order_by":1,"name":"Prince Danan 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This study reports the in-silico design of a multi-epitope peptide vaccine targeting two extracellular cell-wall enzymes, Crh-like protein 5 and 1,3-β-glucanosyltransferase, identified through proteome screening and subcellular localization analysis. Linear and conformational B-cell, CTL, and HTL epitopes were predicted and filtered for antigenicity, non-allergenicity, and non-toxicity, yielding six rationally assembled constructs with suitable adjuvants and linkers. Molecular docking with TLR5 and HLA-DR1, followed by structural validation and physicochemical profiling, identified Construct-3 as the most stable and antigenic (VaxiJen\u0026thinsp;=\u0026thinsp;1.16, non-allergenic, non-toxic). Molecular dynamics simulations (100 ns) confirmed stable receptor binding with minimal conformational fluctuations, and population-coverage analysis predicted\u0026thinsp;~\u0026thinsp;59% global HLA representation. 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