20.500.12556/DKUM-95737 Machine learning in antiviral drug design Viral infections pose a significant health threat worldwide. Due to the high mutation rates of many viruses and their reliance on host cellular machinery, the development of effective antiviral therapies is particularly difficult. As a result, only a limited number of antiviral agents is currently available. In parallel to modern vaccines, traditional antiviral drug development is both time-consuming and costly, underscoring the need for faster, more efficient approaches. In recent years, particularly since the beginning of the COVID-19 pandemic, machine learning (ML) together with broader artificial intelligence (AI), have emerged as powerful methodologies for drug discovery and offer the potential to accelerate the identification and development of antiviral agents. This review examines the application of ML in the early stages of antiviral drug discovery, with a particular focus on recent studies where ML methods have successfully identified hit compounds with experimentally demonstrated activity in biological assays. By highlighting these successful case studies, the review illustrates the growing impact of ML in advancing the discovery of urgently needed novel antivirals. machine learning artificial intelligence antiviral compounds biological activity strojno učenje umetna inteligenca biološke aktivnosti protivirusne spojine true false true Elsevier Angleški jezik Slovenski jezik https://www.sciencedirect.com/journal/bioorganic-and-medicinal-chemistry © 2025 The Authors Članek v reviji 2025-10-17 11:59:42 2025-10-17 11:59:43 2025-10-18 03:21:13 0000-00-00 00:00:00 2026 0 0 36 str. [Article no.] 118426 Vol. 132 1 jan. 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-07-28 2025-09-29 2025-09-30 577 253578755 10.1016/j.bmc.2025.118426 1464-3391 1-s2.0-S0968089625003670-main.pdf 1-s2.0-S0968089625003670-main.pdf 1 F388D7DA92006627C527B1F61F8DA4E7 cddafb6aef3c7c8285c565bf4c691787c19240b8528ae3db670282faa7cc66ba a18f9450-ab40-11f0-a0a8-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=199966 Fakulteta za kemijo in kemijsko tehnologijo 0 0 0