{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T22:32:29Z","timestamp":1785537149715,"version":"3.56.0"},"reference-count":96,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T00:00:00Z","timestamp":1743638400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p><jats:italic>Francisella tularensis<\/jats:italic> is a category A potential thread agent, making the development of vaccines and countermeasures a high priority. Therefore, identifying new vaccine candidates and novel drug targets is essential for addressing this significant public health concern.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This study presents an <jats:italic>in silico<\/jats:italic> analysis of two strategies against <jats:italic>F. tularensis<\/jats:italic> infection: the development of a multi-epitope vaccine (MEV) and the identification of novel drug targets. Outer membrane proteins (OMPs) were predicted using subcellular localization tools and immunogenicity was evaluated using a reverse vaccinology pipeline. Epitopes from these OMPs were combined to create candidate MEV for prophylactic protection. Concurrently, cytoplasmic proteins were subjected to rigorous analysis to identify potential novel drug targets.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of 1,921 proteins, we identified 12 promising protein vaccine candidates from <jats:italic>F. tularensis<\/jats:italic> OMPs and proposed a multi-epitope vaccine (MEV) designed using seven immunodominant epitopes derived from four of these OMPs, including two hypothetical proteins (WP_003026145.1 and WP_003029346.1), an OmpA family protein (WP_003020808.1), and PD40 (WP_003021546.1). In addition, we proposed 10 novel drug targets for <jats:italic>F. tularensis<\/jats:italic>: Asp-tRNA (Asn)\/Glu-tRNA (Gln) amidotransferase subunit GatC (WP_003017413.1), NAD(P)-binding protein (WP_042522581.1), 30S ribosomal protein S16 (WP_003023081.1), Class I SAM-dependent methyltransferase (WP_003022345.1), haloacid dehalogenase (WP_003014157.1), uroporphyrinogen-III synthase (WP_003022220.1), and four hypothetical proteins (WP_003017784.1, WP_003020080.1, WP_003020066.1, and WP_003022350.1).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study designed an MEV and proposed novel drug targets to address tularemia, offering broad protection against various <jats:italic>F. tularensis<\/jats:italic> strains. MEV, with favorable physicochemical properties, showed strong potential through molecular docking and dynamic simulations. Immune simulations suggest that it may elicit robust responses against pathogens. The identification of novel drug targets can lead to the discovery of new antimicrobial agents. However, further <jats:italic>in vitro<\/jats:italic> and <jats:italic>in vivo<\/jats:italic> studies are required to validate their efficacy and capability.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2025.1479862","type":"journal-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T05:15:32Z","timestamp":1743657332000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Development of a multi-epitope vaccine from outer membrane proteins and identification of novel drug targets against Francisella tularensis: an In Silico approach"],"prefix":"10.3389","volume":"16","author":[{"given":"Safoura","family":"Moradkasani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saber","family":"Esmaeili","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Reza","family":"Asadi 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