{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T22:23:50Z","timestamp":1792794230441,"version":"4.5.0"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"vor","delay-in-days":147,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Xunta de Galicia through the collaboration","id":[{"id":"https:\/\/ror.org\/0181xnw06","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Conseller\u00eda de Cultura, Educaci\u00f3n, Formaci\u00f3n Profesional e Universidades","id":[{"id":"https:\/\/ror.org\/03gq5rs15","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Galician universities for the strengthening of research centers in the Galician University System","id":[{"id":"https:\/\/ror.org\/033tgbx59","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Consolidation and Structuring of Competitive Research Units","award":["ED431C 2022\/46"],"award-info":[{"award-number":["ED431C 2022\/46"]}]},{"name":"Xunta de Galicia endowed with EU FEDER","id":[{"id":"https:\/\/ror.org\/0181xnw06","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Universidade da Coru\u00f1a\/CISUG","id":[{"id":"https:\/\/ror.org\/01qckj285","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To confront this challenge, we developed Viral Sentry AI, an autonomous agent designed to close the gap between viral emergence and therapeutic response. Unlike static analysis tools, Viral Sentry AI operates as a continuous sentinel, automatically scanning the National Center for Biotechnology Information public databases for new viral genomes and executing a three-stage agentic surveillance workflow, with distinct, specialized artificial intelligence architectures for generated text, macromolecule sequences, and drug chemical data. First, the system is using a Large Language Model (Gemma4) to parse unstructured submission records and extract the host information if it is not available in the dedicated field. In the second stage, the system employs a novel deep-learning topology, virsentai-v3-hyena-dna-16k, a fine-tuned HyenaDNA model capable of processing complete viral genomes up to 160\u00a0000 bases. This architecture captures subtle, long-range genomic dependencies to predict human infectivity with high precision. Upon predicting the possible human infection of the scanned viruses, the agent autonomously triggers a downstream therapeutic module as the stage three. It extracts National Center for Biotechnology Information RefSeq viral protein sequences and utilizes a pretrained Protein-Ligand Affinity Prediction Transformer model to calculate affinity interactions against 2092 ChEMBL-approved drugs, instantly identifying candidates for drug repurposing. In rigorous cross-validation on a curated dataset of 33\u00a0426 complete viral genomes, the surveillance module demonstrated robust discriminatory power, achieving an Area Under the Receiver Operating Characteristic Curve of 0.88 in classifying human host potential. By integrating state-of-the-art genomic modeling with automated lead compound screening, Viral Sentry AI offers a proactive, end-to-end research prototype for pandemic preparedness. The platform is freely accessible at https:\/\/muntisa.github.io\/virsentai (source code: https:\/\/github.com\/muntisa\/virsentai).<\/jats:p>","DOI":"10.1093\/biomethods\/bpag026","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T11:21:26Z","timestamp":1779794486000},"source":"Crossref","is-referenced-by-count":2,"title":["Viral Sentry AI\u2014Automated zoonotic surveillance and drug repurposing agent"],"prefix":"10.1093","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5628-2268","authenticated-orcid":false,"given":"Cristian R","family":"Munteanu","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, Universidade da Coru\u00f1a RNASA-IMEDIR Research Group, Department of Computer Science and Information Technology, , Elvi\u00f1a , 15071 A Coru\u00f1a,","place":["Spain"]},{"name":"CITIC, Research Centre in Information and Communication Technologies, Universidade da Coru\u00f1a , 15009 A 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