{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T16:50:27Z","timestamp":1786985427087,"version":"build-2736575974"},"reference-count":68,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["P2-0438"],"award-info":[{"award-number":["P2-0438"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["P1-0403"],"award-info":[{"award-number":["P1-0403"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J4-4633"],"award-info":[{"award-number":["J4-4633"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J1-50034"],"award-info":[{"award-number":["J1-50034"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J1-60001"],"award-info":[{"award-number":["J1-60001"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J1-4398"],"award-info":[{"award-number":["J1-4398"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J2-60044"],"award-info":[{"award-number":["J2-60044"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J7-50043"],"award-info":[{"award-number":["J7-50043"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["Z1-50021"],"award-info":[{"award-number":["Z1-50021"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["L7-60161"],"award-info":[{"award-number":["L7-60161"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["I0-E015"],"award-info":[{"award-number":["I0-E015"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["L2-4430"],"award-info":[{"award-number":["L2-4430"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J3-4497"],"award-info":[{"award-number":["J3-4497"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J7-4638"],"award-info":[{"award-number":["J7-4638"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J1-4414"],"award-info":[{"award-number":["J1-4414"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J3-4498"],"award-info":[{"award-number":["J3-4498"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["GC-0001"],"award-info":[{"award-number":["GC-0001"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Bioorganic & Medicinal Chemistry"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.bmc.2025.118426","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T05:57:34Z","timestamp":1759298254000},"page":"118426","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":6,"special_numbering":"C","title":["Machine learning in antiviral drug design"],"prefix":"10.1016","volume":"132","author":[{"given":"Anja","family":"Kolari\u010d","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marko","family":"Juki\u010d","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Urban","family":"Bren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.bmc.2025.118426_bb0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejmech.2024.116442","article-title":"Medicinal chemistry strategies toward broad-spectrum antiviral agents to prevent next pandemics","volume":"271","author":"L\u00fc","year":"2024","journal-title":"Eur. J. Med. Chem."},{"key":"10.1016\/j.bmc.2025.118426_bb0010","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1038\/s41551-020-00658-w","article-title":"Development of vaccines and antivirals for combating viral pandemics","volume":"4","author":"Pardi","year":"2020","journal-title":"Nat Biomed Eng"},{"key":"10.1016\/j.bmc.2025.118426_bb0015","doi-asserted-by":"crossref","DOI":"10.1177\/20587384211002621","article-title":"A review: mechanism of action of antiviral drugs","volume":"35","author":"Kausar","year":"2021","journal-title":"Int. J. Immunopathol. Pharmacol."},{"key":"10.1016\/j.bmc.2025.118426_bb0020","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.1007\/s10462-021-10058-4","article-title":"Machine learning in drug discovery: a review","volume":"55","author":"Dara","year":"2022","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.bmc.2025.118426_bb0025","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.3390\/ph16091259","article-title":"Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery","volume":"16","author":"Han","year":"2023","journal-title":"Pharmaceuticals"},{"key":"10.1016\/j.bmc.2025.118426_bb0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2023.e17575","article-title":"AI in drug discovery and its clinical relevance","volume":"9","author":"Qureshi","year":"2023","journal-title":"Heliyon"},{"key":"10.1016\/j.bmc.2025.118426_bb0035","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1007\/s40259-023-00611-8","article-title":"Staying ahead of the game: how SARS-CoV-2 has accelerated the application of machine learning in pandemic management","volume":"37","author":"Williams","year":"2023","journal-title":"BioDrugs"},{"key":"10.1016\/j.bmc.2025.118426_bb0040","doi-asserted-by":"crossref","first-page":"536","DOI":"10.3923\/ijp.2024.536.546","article-title":"Revolutionizing antiviral drug discovery: the emerging role of artificial intelligence","volume":"20","author":"Kandeel","year":"2024","journal-title":"Int. J. Pharmacol."},{"key":"10.1016\/j.bmc.2025.118426_bb0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.crphar.2021.100042","article-title":"Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2","volume":"2","author":"Prasad","year":"2021","journal-title":"Curr Res Pharmacol Drug Discov"},{"key":"10.1016\/j.bmc.2025.118426_bb0050","doi-asserted-by":"crossref","first-page":"4770","DOI":"10.1109\/TNNLS.2021.3111745","article-title":"New insights into drug repurposing for COVID-19 using deep learning","volume":"32","author":"Lee","year":"2021","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10.1016\/j.bmc.2025.118426_bb0055","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbab320","article-title":"Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design","volume":"22","author":"Lv","year":"2021","journal-title":"Brief. Bioinform."},{"key":"10.1016\/j.bmc.2025.118426_bb0060","doi-asserted-by":"crossref","first-page":"926","DOI":"10.3390\/jpm11090926","article-title":"A systematic review on the contribution of artificial intelligence in the development of medicines for COVID-2019","volume":"11","author":"Pires","year":"2021","journal-title":"J Pers Med"},{"key":"10.1016\/j.bmc.2025.118426_bb0065","doi-asserted-by":"crossref","first-page":"3261","DOI":"10.3390\/ijms23063261","article-title":"Artificial intelligence technologies for COVID-19 de novo drug design","volume":"23","author":"Floresta","year":"2022","journal-title":"Int. J. Mol. Sci."},{"key":"10.1016\/j.bmc.2025.118426_bb0070","doi-asserted-by":"crossref","DOI":"10.3389\/fphar.2023.1182465","article-title":"A review of SARS-CoV-2 drug repurposing: databases and machine learning models","volume":"14","author":"Elkashlan","year":"2023","journal-title":"Front. Pharmacol."},{"key":"10.1016\/j.bmc.2025.118426_bb0075","doi-asserted-by":"crossref","first-page":"1913","DOI":"10.1016\/j.drudis.2022.05.013","article-title":"Artificial intelligence in virtual screening: models versus experiments","volume":"27","author":"Murugan","year":"2022","journal-title":"Drug Discov. Today"},{"key":"10.1016\/j.bmc.2025.118426_bb0080","doi-asserted-by":"crossref","DOI":"10.1080\/23311916.2021.1958666","article-title":"Battling COVID-19 using machine learning: A review","volume":"8","author":"Chadaga","year":"2021","journal-title":"Cogent Eng"},{"key":"10.1016\/j.bmc.2025.118426_bb0085","article-title":"Supervised machine learning in drug discovery and development: algorithms, applications, challenges, and prospects","volume":"17","author":"Obaido","year":"2024","journal-title":"Mach Learn Appl"},{"key":"10.1016\/j.bmc.2025.118426_bb0090","first-page":"1","article-title":"QSPR\/QSAR study of antiviral drugs modeled as multigraphs by using TI\u2019S and MLR method to treat COVID-19 disease","volume":"14","author":"Suresh","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.bmc.2025.118426_bb0095","article-title":"Multilinear regression analysis of antiviral medications with topological indices","author":"Manonmani","year":"2025","journal-title":"J Mol Graph Model"},{"key":"10.1016\/j.bmc.2025.118426_bb0100","doi-asserted-by":"crossref","first-page":"26805","DOI":"10.1007\/s11227-024-06434-w","article-title":"A quadratic regression model to quantify certain latest corona treatment drug molecules based on coindices of M-polynomial","volume":"80","author":"Zaman","year":"2024","journal-title":"J. Supercomput."},{"key":"10.1016\/j.bmc.2025.118426_bb0105","series-title":"Machine Learning","author":"Zhou","year":"2021"},{"key":"10.1016\/j.bmc.2025.118426_bb0110","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.drudis.2014.10.012","article-title":"Machine-learning approaches in drug discovery: methods and applications","volume":"20","author":"Lavecchia","year":"2015","journal-title":"Drug Discov. Today"},{"key":"10.1016\/j.bmc.2025.118426_bb0115","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1080\/14756366.2022.2132486","article-title":"Ligand-based discovery of coronavirus main protease inhibitors using MACAW molecular embeddings","volume":"38","author":"Dong","year":"2023","journal-title":"J Enzyme Inhib Med Chem"},{"key":"10.1016\/j.bmc.2025.118426_bb0120","doi-asserted-by":"crossref","first-page":"4590","DOI":"10.1021\/acs.jmedchem.1c01372","article-title":"Efficient identification of anti-SARS-CoV-2 compounds using chemical structure-and biological activity-based modeling","volume":"65","author":"Xu","year":"2022","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.bmc.2025.118426_bb0125","series-title":"Xgboost: A scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD Int Conf on Knowl Discov Data Min","first-page":"785","author":"Chen","year":"2016"},{"key":"10.1016\/j.bmc.2025.118426_bb0130","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2214168120","article-title":"Turning high-throughput structural biology into predictive inhibitor design","volume":"120","author":"Saar","year":"2023","journal-title":"PNAS"},{"key":"10.1016\/j.bmc.2025.118426_bb0135","doi-asserted-by":"crossref","first-page":"1338","DOI":"10.1021\/acs.jcim.4c02126","article-title":"Applications of machine learning approaches for the discovery of SARS-CoV-2 PLpro inhibitors","volume":"65","author":"Pal","year":"2025","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.bmc.2025.118426_bb0140","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1016\/j.drudis.2017.01.005","article-title":"The application of principal component analysis to drug discovery and biomedical data","volume":"22","author":"Giuliani","year":"2017","journal-title":"Drug Discov. Today"},{"key":"10.1016\/j.bmc.2025.118426_bb0145","doi-asserted-by":"crossref","first-page":"3134","DOI":"10.3390\/biomedicines11123134","article-title":"How deep learning in antiviral molecular profiling identified anti-SARS-CoV-2 inhibitors","volume":"11","author":"Ali","year":"2023","journal-title":"Biomedicines"},{"key":"10.1016\/j.bmc.2025.118426_bb0150","doi-asserted-by":"crossref","first-page":"88","DOI":"10.3390\/v16010088","article-title":"Computer-selected antiviral compounds: assessing in vitro efficacies against Rift Valley fever virus","volume":"16","author":"Alkan","year":"2024","journal-title":"Viruses"},{"key":"10.1016\/j.bmc.2025.118426_bb0155","doi-asserted-by":"crossref","first-page":"14011","DOI":"10.1021\/acs.jmedchem.1c00927","article-title":"Generative models for de novo drug design","volume":"64","author":"Tong","year":"2021","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.bmc.2025.118426_bb0160","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1038\/s41467-024-46569-1","article-title":"A dual diffusion model enables 3D molecule generation and lead optimization based on target pockets","volume":"15","author":"Huang","year":"2024","journal-title":"Nat. Commun."},{"key":"10.1016\/j.bmc.2025.118426_bb0165","doi-asserted-by":"crossref","first-page":"2733","DOI":"10.1021\/acs.jcim.3c00536","article-title":"Transformer-based molecular generative model for antiviral drug design","volume":"64","author":"Mao","year":"2023","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.bmc.2025.118426_bb0170","doi-asserted-by":"crossref","first-page":"4546","DOI":"10.1038\/s41467-025-59870-4","article-title":"A novel, covalent broad-spectrum inhibitor targeting human coronavirus Mpro","volume":"16","author":"Sun","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.bmc.2025.118426_bb0175","doi-asserted-by":"crossref","first-page":"519","DOI":"10.3390\/biology12040519","article-title":"Virtual and in vitro screening of natural products identifies indole and benzene derivatives as inhibitors of SARS-CoV-2 Main protease (Mpro)","volume":"12","author":"Ang","year":"2023","journal-title":"Biology"},{"key":"10.1016\/j.bmc.2025.118426_bb0180","doi-asserted-by":"crossref","DOI":"10.3389\/fphar.2023.1297924","article-title":"Identification of oral therapeutics using an AI platform against the virus responsible for COVID-19, SARS-CoV-2","volume":"14","author":"Bess","year":"2023","journal-title":"Front. Pharmacol."},{"key":"10.1016\/j.bmc.2025.118426_bb0185","first-page":"1","article-title":"Deep learning for drug design: an artificial intelligence paradigm for drug discovery in the big data era","volume":"20","author":"Jing","year":"2018","journal-title":"AAPS"},{"key":"10.1016\/j.bmc.2025.118426_bb0190","doi-asserted-by":"crossref","first-page":"1767","DOI":"10.1080\/07391102.2021.2024260","article-title":"Identification of SARS-CoV-2 main protease inhibitors from FDA-approved drugs by artificial intelligence-supported activity prediction system","volume":"41","author":"Komatsu","year":"2023","journal-title":"J. Biomol. Struct. Dyn."},{"key":"10.1016\/j.bmc.2025.118426_bb0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2021.105049","article-title":"Combined deep learning and molecular docking simulations approach identifies potentially effective FDA approved drugs for repurposing against SARS-CoV-2","volume":"141","author":"Anwaar","year":"2022","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.bmc.2025.118426_bb0200","doi-asserted-by":"crossref","first-page":"8562","DOI":"10.1021\/acs.jcim.4c01110","article-title":"AI promoted virtual screening, structure-based hit optimization, and synthesis of novel COVID-19 S-RBD domain inhibitors","volume":"64","author":"Gkekas","year":"2024","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.bmc.2025.118426_bb0205","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejmech.2024.116885","article-title":"Utilizing artificial intelligence for precision exploration of N protein targeting phenanthridine sars-cov-2 inhibitors: A novel approach","volume":"279","author":"Xiang","year":"2024","journal-title":"Eur. J. Med. Chem."},{"key":"10.1016\/j.bmc.2025.118426_bb0210","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1007\/s12033-023-00670-w","article-title":"In silico design and experimental validation of novel oxazole derivatives against varicella zoster virus","volume":"66","author":"Kovalishyn","year":"2024","journal-title":"Mol. Biotechnol."},{"key":"10.1016\/j.bmc.2025.118426_bb0215","doi-asserted-by":"crossref","first-page":"2866","DOI":"10.1021\/acs.jcim.3c00409","article-title":"AI-driven discovery of SARS-CoV-2 main protease fragment-like inhibitors with antiviral activity in vitro","volume":"63","author":"Saramago","year":"2023","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.bmc.2025.118426_bb0220","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/s10822-023-00509-1","article-title":"Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV-2 main protease","volume":"37","author":"Varikoti","year":"2023","journal-title":"J. Comput. Aided Mol. Des."},{"key":"10.1016\/j.bmc.2025.118426_bb0225","doi-asserted-by":"crossref","DOI":"10.1016\/j.antiviral.2024.106012","article-title":"Large-scale deep learning identifies the antiviral potential of PKI-179 and MTI-31 against coronaviruses","volume":"231","author":"van der Horst","year":"2024","journal-title":"Antivir. Res."},{"key":"10.1016\/j.bmc.2025.118426_bb0230","doi-asserted-by":"crossref","first-page":"48505","DOI":"10.1021\/acsomega.4c07194","article-title":"Discovering influenza virus neuraminidase inhibitors via computational and experimental studies","volume":"9","author":"Nguyen","year":"2024","journal-title":"ACS Omega"},{"key":"10.1016\/j.bmc.2025.118426_bb0235","first-page":"22","article-title":"A review of unsupervised artificial neural networks with applications","volume":"181","author":"Fabiyi","year":"2019","journal-title":"Int. J. Comput. Appl."},{"key":"10.1016\/j.bmc.2025.118426_bb0240","series-title":"2018 IEEE international conference on cyborg and bionic systems (CBS)","first-page":"322","article-title":"Unsupervised learning based on artificial neural network: a review","author":"Dike","year":"2018"},{"key":"10.1016\/j.bmc.2025.118426_bb0245","doi-asserted-by":"crossref","first-page":"12800","DOI":"10.1080\/07391102.2021.1977181","article-title":"In silico and in vitro assays reveal potential inhibitors against 3CL pro main protease of SARS-CoV-2","volume":"40","author":"Iype","year":"2022","journal-title":"J. Biomol. Struct. Dyn."},{"key":"10.1016\/j.bmc.2025.118426_bb0250","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1021\/acs.jcim.2c01377","article-title":"Ai-accelerated design of targeted covalent inhibitors for SARS-CoV-2","volume":"63","author":"Joshi","year":"2023","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.bmc.2025.118426_bb0255","doi-asserted-by":"crossref","first-page":"240","DOI":"10.3390\/ph17020240","article-title":"Identification of SARS-CoV-2 Main protease inhibitors using chemical similarity analysis combined with machine learning","volume":"17","author":"Ju\u00e1rez-Mercado","year":"2024","journal-title":"Pharmaceuticals"},{"key":"10.1016\/j.bmc.2025.118426_bb0260","doi-asserted-by":"crossref","first-page":"6468","DOI":"10.3390\/ijms23126468","article-title":"A study of drug repurposing to identify SARS-CoV-2 main protease (3CLpro) inhibitors","volume":"23","author":"Jo","year":"2022","journal-title":"Int. J. Mol. Sci."},{"key":"10.1016\/j.bmc.2025.118426_bb0265","doi-asserted-by":"crossref","first-page":"2442","DOI":"10.1016\/j.csbj.2022.05.023","article-title":"Potential drug discovery for COVID-19 treatment targeting Cathepsin L using a deep learning-based strategy","volume":"20","author":"Yang","year":"2022","journal-title":"Comput Struct Biotechnol"},{"key":"10.1016\/j.bmc.2025.118426_bb0270","doi-asserted-by":"crossref","first-page":"5545","DOI":"10.1093\/bioinformatics\/btaa1005","article-title":"DeepPurpose: a deep learning library for drug\u2013target interaction prediction","volume":"36","author":"Huang","year":"2020","journal-title":"Bioinformatics"},{"key":"10.1016\/j.bmc.2025.118426_bb0275","doi-asserted-by":"crossref","first-page":"12166","DOI":"10.1021\/acs.jpcb.1c06437","article-title":"3D-scaffold: a deep learning framework to generate 3D coordinates of drug-like molecules with desired scaffolds","volume":"125","author":"Joshi","year":"2021","journal-title":"J. Phys. Chem. B"},{"key":"10.1016\/j.bmc.2025.118426_bb0280","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s13065-021-00737-2","article-title":"De novo design and bioactivity prediction of SARS-CoV-2 main protease inhibitors using recurrent neural network-based transfer learning","volume":"15","author":"Santana","year":"2021","journal-title":"BMC Chem"},{"key":"10.1016\/j.bmc.2025.118426_bb0285","doi-asserted-by":"crossref","first-page":"891","DOI":"10.3390\/v15040891","article-title":"Discovery of potential inhibitors of SARS-CoV-2 main protease by a transfer learning method","volume":"15","author":"Zhang","year":"2023","journal-title":"Viruses"},{"key":"10.1016\/j.bmc.2025.118426_bb0290","article-title":"ChemBERTa: large-scale self-supervised pretraining for molecular property prediction","author":"Chithrananda","year":"2020","journal-title":"arXiv preprint arXiv"},{"key":"10.1016\/j.bmc.2025.118426_bb0295","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1080\/14786419.2023.2194647","article-title":"Antiviral activity of curcumin and its analogs selected by an artificial intelligence-supported activity prediction system in SARS-CoV-2-infected VeroE6 cells","volume":"38","author":"Teshima","year":"2024","journal-title":"Nat. Prod. Res."},{"key":"10.1016\/j.bmc.2025.118426_bb0305","doi-asserted-by":"crossref","DOI":"10.1002\/minf.202000113","article-title":"QSAR modeling of SARS-CoV M pro inhibitors identifies Sufugolix, Cenicriviroc, Proglumetacin, and other drugs as candidates for repurposing against SARS-CoV-2","volume":"40","author":"Alves","year":"2021","journal-title":"Mol Inform"},{"key":"10.1016\/j.bmc.2025.118426_bb0310","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1021\/acscombsci.0c00058","article-title":"Targeting the dimerization of the Main protease of coronaviruses: A potential broad-Spectrum therapeutic strategy","volume":"22","author":"Goyal","year":"2020","journal-title":"ACS Comb. Sci."},{"key":"10.1016\/j.bmc.2025.118426_bb0315","doi-asserted-by":"crossref","first-page":"eado4288","DOI":"10.1126\/sciadv.ado4288","article-title":"Discovery of SARS-CoV-2 papain-like protease (PLpro) inhibitors with efficacy in a murine infection model","volume":"10","author":"Garnsey","year":"2024","journal-title":"Sci. Adv."},{"key":"10.1016\/j.bmc.2025.118426_bb0320","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1038\/s41467-020-20718-8","article-title":"The complex structure of GRL0617 and SARS-CoV-2 PLpro reveals a hot spot for antiviral drug discovery","volume":"12","author":"Fu","year":"2021","journal-title":"Nat. Commun."},{"key":"10.1016\/j.bmc.2025.118426_bb0325","doi-asserted-by":"crossref","first-page":"2212","DOI":"10.1021\/acs.jcim.1c01130","article-title":"Scaffold-retained structure generator to exhaustively create molecules in an arbitrary chemical space","volume":"62","author":"Kaitoh","year":"2022","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.bmc.2025.118426_bb0330","doi-asserted-by":"crossref","first-page":"8036","DOI":"10.1039\/D1SC00163A","article-title":"DeepFrag: a deep convolutional neural network for fragment-based lead optimization","volume":"12","author":"Green","year":"2021","journal-title":"Chem. Sci."},{"key":"10.1016\/j.bmc.2025.118426_bb0335","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1080\/1062936X.2023.2232992","article-title":"Design and experimental validation of the oxazole and thiazole derivatives as potential antivirals against of human cytomegalovirus","volume":"34","author":"Kovalishyn","year":"2023","journal-title":"SAR QSAR Environ. Res."},{"key":"10.1016\/j.bmc.2025.118426_bb0340","article-title":"AtomNet: A deep convolutional neural network for bioactivity prediction in structure-based drug discovery","author":"Wallach","year":"2015","journal-title":"arXiv preprint arXiv"},{"key":"10.1016\/j.bmc.2025.118426_bb0345","doi-asserted-by":"crossref","DOI":"10.1016\/j.antiviral.2024.105818","article-title":"Discovery of new antiviral agents through artificial intelligence: in vitro and in vivo results","volume":"222","author":"Izmailyan","year":"2024","journal-title":"Antivir. Res."}],"container-title":["Bioorganic & Medicinal Chemistry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0968089625003670?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0968089625003670?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:01:58Z","timestamp":1780635718000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0968089625003670"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":68,"alternative-id":["S0968089625003670"],"URL":"https:\/\/doi.org\/10.1016\/j.bmc.2025.118426","relation":{},"ISSN":["0968-0896"],"issn-type":[{"value":"0968-0896","type":"print"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Machine learning in antiviral drug design","name":"articletitle","label":"Article Title"},{"value":"Bioorganic & Medicinal Chemistry","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bmc.2025.118426","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"118426"}}