{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T08:22:01Z","timestamp":1783326121193,"version":"3.54.6"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T00:00:00Z","timestamp":1783296000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T00:00:00Z","timestamp":1783296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Chumakov FSC R&D IBP RAS","award":["FNZG-2024-0005"],"award-info":[{"award-number":["FNZG-2024-0005"]}]},{"name":"Chumakov FSC R&D IBP RAS","award":["FNZG-2024-0005"],"award-info":[{"award-number":["FNZG-2024-0005"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Comput Aided Mol Des"],"DOI":"10.1007\/s10822-026-00883-6","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T08:09:44Z","timestamp":1783325384000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Two faces of drug repurposing data in machine learning-driven structure-based virtual screening supported by interaction fingerprints"],"prefix":"10.1007","volume":"40","author":[{"given":"Anastasia D.","family":"Fomina","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmitry I.","family":"Osolodkin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,6]]},"reference":[{"issue":"1","key":"883_CR1","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1002\/cmdc.200900314","volume":"5","author":"DM Kr\u00fcger","year":"2010","unstructured":"Kr\u00fcger DM, Evers A (2010) Comparison of structure- and ligand-based virtual screening protocols considering hit list complementarity and enrichment factors. ChemMedChem 5(1):148\u2013158. https:\/\/doi.org\/10.1002\/cmdc.200900314","journal-title":"ChemMedChem"},{"issue":"1","key":"883_CR2","doi-asserted-by":"publisher","first-page":"72","DOI":"10.3390\/biom14010072","volume":"14","author":"Z Li","year":"2024","unstructured":"Li Z, Huang R, Xia M, Patterson TA, Hong H (2024) Fingerprinting interactions between proteins and ligands for facilitating machine learning in drug discovery. Biomolecules 14(1):72. https:\/\/doi.org\/10.3390\/biom14010072","journal-title":"Biomolecules"},{"key":"883_CR3","doi-asserted-by":"publisher","DOI":"10.3390\/ijms22094435","author":"TB Kimber","year":"2021","unstructured":"Kimber TB, Chen Y, Volkamer A, Kimber TB, Chen Y, Volkamer A (2021) Deep learning in virtual screening: recent applications and developments. Int J Mol Sci. https:\/\/doi.org\/10.3390\/ijms22094435","journal-title":"Int J Mol Sci"},{"issue":"5","key":"883_CR4","doi-asserted-by":"publisher","first-page":"e00994","DOI":"10.1002\/prp2.994","volume":"10","author":"M Jim\u00e9nez-Ros\u00e9s","year":"2022","unstructured":"Jim\u00e9nez-Ros\u00e9s M, Morgan BA, Jimenez Sigstad M, Tran TDZ, Srivastava R, Bunsuz A, Borrega\u2010Rom\u00e1n L, Hompluem P, Cullum SA, Harwood CR, Koers EJ, Sykes DA, Styles IB, Veprintsev DB (2022) Combined Docking and Machine Learning Identify Key Molecular Determinants of Ligand Pharmacological Activity on \u03922 adrenoceptor. Pharmacol Res Perspect 10(5):e00994. https:\/\/doi.org\/10.1002\/prp2.994","journal-title":"Pharmacol Res Perspect"},{"issue":"4","key":"883_CR5","doi-asserted-by":"publisher","first-page":"bbad187","DOI":"10.1093\/bib\/bbad187","volume":"24","author":"NA Szulc","year":"2023","unstructured":"Szulc NA, Mackiewicz Z, Bujnicki JM, Stefaniak F (2023) Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA. Brief Bioinform 24(4):bbad187. https:\/\/doi.org\/10.1093\/bib\/bbad187","journal-title":"Brief Bioinform"},{"issue":"16","key":"883_CR6","doi-asserted-by":"publisher","first-page":"8373","DOI":"10.1039\/D0CP00305K","volume":"22","author":"K Gao","year":"2020","unstructured":"Gao K, Nguyen DD, Sresht V, Mathiowetz AM, Tu M, Wei G-W (2020) Are 2D fingerprints still valuable for drug discovery? Phys Chem Chem Phys 22(16):8373\u20138390. https:\/\/doi.org\/10.1039\/D0CP00305K","journal-title":"Phys Chem Chem Phys"},{"issue":"2","key":"883_CR7","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1021\/jm030331x","volume":"47","author":"Z Deng","year":"2004","unstructured":"Deng Z, Chuaqui C, Singh J (2004) Structural interaction fingerprint (SIFt): a novel method for analyzing three-dimensional protein\u2013ligand binding interactions. J Med Chem 47(2):337\u2013344. https:\/\/doi.org\/10.1021\/jm030331x","journal-title":"J Med Chem"},{"issue":"1","key":"883_CR8","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1021\/ci600342e","volume":"47","author":"G Marcou","year":"2007","unstructured":"Marcou G, Rognan D (2007) Optimizing fragment and scaffold docking by use of molecular interaction fingerprints. J Chem Inf Model 47(1):195\u2013207. https:\/\/doi.org\/10.1021\/ci600342e","journal-title":"J Chem Inf Model"},{"issue":"5","key":"883_CR9","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1021\/ci900043r","volume":"49","author":"VI P\u00e9rez-Nueno","year":"2009","unstructured":"P\u00e9rez-Nueno VI, Rabal O, Borrell JI, Teixid\u00f3 J (2009) APIF: A new interaction fingerprint based on atom pairs and its application to virtual screening. J Chem Inf Model 49(5):1245\u20131260. https:\/\/doi.org\/10.1021\/ci900043r","journal-title":"J Chem Inf Model"},{"issue":"8","key":"883_CR10","doi-asserted-by":"publisher","first-page":"1334","DOI":"10.1093\/bioinformatics\/bty757","volume":"35","author":"M W\u00f3jcikowski","year":"2019","unstructured":"W\u00f3jcikowski M, Kukie\u0142ka M, Stepniewska-Dziubinska MM, Siedlecki P (2019) Development of a protein\u2013ligand extended connectivity (PLEC) fingerprint and its application for binding affinity predictions. Bioinformatics 35(8):1334\u20131341. https:\/\/doi.org\/10.1093\/bioinformatics\/bty757","journal-title":"Bioinformatics"},{"issue":"9","key":"883_CR11","doi-asserted-by":"publisher","first-page":"2555","DOI":"10.1021\/ci500319f","volume":"54","author":"C Da","year":"2014","unstructured":"Da C, Kireev D (2014) Structural protein\u2013ligand interaction fingerprints (SPLIF) for structure-based virtual screening: method and benchmark study. J Chem Inf Model 54(9):2555\u20132561. https:\/\/doi.org\/10.1021\/ci500319f","journal-title":"J Chem Inf Model"},{"issue":"7959","key":"883_CR12","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1038\/s41586-023-05993-x","volume":"617","author":"P Gainza","year":"2023","unstructured":"Gainza P, Wehrle S, Van Hall-Beauvais A, Marchand A, Scheck A, Harteveld Z, Buckley S, Ni D, Tan S, Sverrisson F, Goverde C, Turelli P, Raclot C, Teslenko A, Pacesa M, Rosset S, Georgeon S, Marsden J, Petruzzella A, Liu K, Xu Z, Chai Y, Han P, Gao GF, Oricchio E, Fierz B, Trono D, Stahlberg H, Bronstein M, Correia BE (2023) De novo design of protein interactions with learned surface fingerprints. Nature 617(7959):176\u2013184. https:\/\/doi.org\/10.1038\/s41586-023-05993-x","journal-title":"Nature"},{"issue":"5","key":"883_CR13","doi-asserted-by":"publisher","first-page":"2456","DOI":"10.1021\/acs.jcim.4c01902","volume":"65","author":"C Fellinger","year":"2025","unstructured":"Fellinger C, Seidel T, Merget B, Schleifer K-J, Langer T (2025) GRADE and X-GRADE:Unveiling novel protein\u2013ligand interaction fingerprints based on GRAIL scores. J Chem Inf Model 65(5):2456\u20132475. https:\/\/doi.org\/10.1021\/acs.jcim.4c01902","journal-title":"J Chem Inf Model"},{"issue":"3","key":"883_CR14","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1021\/acsptsci.0c00215","volume":"4","author":"J Gossen","year":"2021","unstructured":"Gossen J, Albani S, Hanke A, Joseph BP, Bergh C, Kuzikov M, Costanzi E, Manelfi C, Storici P, Gribbon P, Beccari AR, Talarico C, Spyrakis F, Lindahl E, Zaliani A, Carloni P, Wade RC, Musiani F, Kokh DB, Rossetti GA (2021) Blueprint for high affinity SARS-CoV-2 Mpro inhibitors from activity-based compound library screening guided by analysis of protein dynamics. ACS Pharmacol Transl Sci 4(3):1079\u20131095. https:\/\/doi.org\/10.1021\/acsptsci.0c00215","journal-title":"ACS Pharmacol Transl Sci"},{"issue":"1","key":"883_CR15","doi-asserted-by":"publisher","first-page":"9204","DOI":"10.1038\/s41598-023-35671-x","volume":"13","author":"P Schake","year":"2023","unstructured":"Schake P, Dishnica K, Kaiser F, Leberecht C, Haupt VJ, Schroeder M (2023) An interaction-based drug discovery screen explains known SARS-CoV-2 inhibitors and predicts new compound scaffolds. Sci Rep 13(1):9204. https:\/\/doi.org\/10.1038\/s41598-023-35671-x","journal-title":"Sci Rep"},{"key":"883_CR16","doi-asserted-by":"publisher","first-page":"101428","DOI":"10.1016\/j.rechem.2024.101428","volume":"7","author":"A Yan","year":"2024","unstructured":"Yan A, Li W, Zhao X, Cao R, Li H, Chen L, Li X (2024) NoncovalentSARS-COV-2 main protease inhibitors: a virtual screening and molecular dynamic simulation study. Results Chem 7:101428. https:\/\/doi.org\/10.1016\/j.rechem.2024.101428","journal-title":"Results Chem"},{"issue":"6","key":"883_CR17","doi-asserted-by":"publisher","first-page":"325","DOI":"10.6026\/97320630009325","volume":"9","author":"M Radifar","year":"2013","unstructured":"Radifar M, Yuniarti N, Istyastono EP (2013) PyPLIF: python-based protein-ligand interaction fingerprinting. Bioinformation 9(6):325\u2013328. https:\/\/doi.org\/10.6026\/97320630009325","journal-title":"Bioinformation"},{"issue":"3","key":"883_CR18","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.jmb.2016.12.004","volume":"429","author":"HC Jubb","year":"2017","unstructured":"Jubb HC, Higueruelo AP, Ochoa-Monta\u00f1o B, Pitt WR, Ascher DB, Blundell TL (2017) Arpeggio:A web server for calculating and visualising interatomic interactions in protein structures. J Mol Biol 429(3):365\u2013371. https:\/\/doi.org\/10.1016\/j.jmb.2016.12.004","journal-title":"J Mol Biol"},{"key":"883_CR19","doi-asserted-by":"publisher","first-page":"102667","DOI":"10.1016\/j.sbi.2023.102667","volume":"82","author":"Y Duan","year":"2023","unstructured":"Duan Y, Wang H, Yuan Z, Yang H (2023) Structural biology of SARS-CoV-2 Mpro and drug discovery. Curr Opin Struct Biol 82:102667. https:\/\/doi.org\/10.1016\/j.sbi.2023.102667","journal-title":"Curr Opin Struct Biol"},{"key":"883_CR20","doi-asserted-by":"publisher","first-page":"773198","DOI":"10.3389\/fphar.2021.773198","volume":"12","author":"MY Zakharova","year":"2021","unstructured":"Zakharova MY, Kuznetsova AA, Uvarova VI, Fomina AD, Kozlovskaya LI, Kaliberda EN, Kurbatskaia IN, Smirnov IV, Bulygin AA, Knorre VD, Fedorova OS, Varnek A, Osolodkin DI, Ishmukhametov AA, Egorov AM, Gabibov AG, Kuznetsov NA (2021) Pre-steady-state kinetics of the SARS-CoV-2 main protease as a powerful tool for antiviral drug discovery. Front Pharmacol 12:773198. https:\/\/doi.org\/10.3389\/fphar.2021.773198","journal-title":"Front Pharmacol"},{"issue":"8","key":"883_CR21","doi-asserted-by":"publisher","first-page":"e202300279","DOI":"10.1002\/minf.202300279","volume":"43","author":"AD Fomina","year":"2024","unstructured":"Fomina AD, Uvarova VI, Kozlovskaya LI, Palyulin VA, Osolodkin DI, Ishmukhametov AA (2024) Ensemble docking based virtual screening of SARS-CoV\u20102 main protease inhibitors. Mol Inf 43(8):e202300279. https:\/\/doi.org\/10.1002\/minf.202300279","journal-title":"Mol Inf"},{"issue":"1","key":"883_CR22","doi-asserted-by":"publisher","first-page":"259","DOI":"10.3390\/ijms23010259","volume":"23","author":"Guillem Macip; Pol Garcia-Segura","year":"2021","unstructured":"Macip G, Garcia-Segura P, Mestres-Truyol J, Saldivar-Espinoza B, Pujadas G, Garcia-Vallve S (2021) A review of the current landscape of SARS-CoV-2 main protease inhibitors: have we hit the bullseye yet? Int J Mol Sci 23(1):259. https:\/\/doi.org\/10.3390\/ijms23010259","journal-title":"Int J Mol Sci"},{"key":"883_CR23","doi-asserted-by":"publisher","DOI":"10.1126\/science.abo7201","author":"ML Boby","year":"2023","unstructured":"Boby ML et al (2023) Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors. Science. https:\/\/doi.org\/10.1126\/science.abo7201","journal-title":"Science"},{"key":"883_CR24","doi-asserted-by":"publisher","first-page":"105620","DOI":"10.1016\/j.antiviral.2023.105620","volume":"217","author":"H-J Martin","year":"2023","unstructured":"Martin H-J, Melo-Filho CC, Korn D, Eastman RT, Rai G, Simeonov A, Zakharov AV, Muratov E, Tropsha A (2023) Small molecule antiviral compound collection (SMACC): a comprehensive, highly curated database to support the discovery of broad-spectrum antiviral drug molecules. Antiviral Res 217:105620. https:\/\/doi.org\/10.1016\/j.antiviral.2023.105620","journal-title":"Antiviral Res"},{"issue":"11","key":"883_CR25","doi-asserted-by":"publisher","first-page":"2324","DOI":"10.1021\/acs.jcim.5b00559","volume":"55","author":"T Sterling","year":"2015","unstructured":"Sterling T, Irwin JJ (2015) ZINC 15-ligand discovery for everyone. J Chem Inf Model 55(11):2324\u20132337. https:\/\/doi.org\/10.1021\/acs.jcim.5b00559","journal-title":"J Chem Inf Model"},{"key":"883_CR26","doi-asserted-by":"publisher","DOI":"10.18097\/PBMC20247006456","author":"AD Fomina","year":"2024","unstructured":"Fomina AD, Palyulin VA, Osolodkin DI (2024) Homology modeling of the orthoflavivirus NS1 protein for virtual screening of potential ligands. Biomeditsinskaya Khim. https:\/\/doi.org\/10.18097\/PBMC20247006456","journal-title":"Biomeditsinskaya Khim"},{"key":"883_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v109.i03","volume":"109","author":"PG Poli\u010dar","year":"2024","unstructured":"Poli\u010dar PG, Stra\u017ear M, Zupan B (2024) OpenTSNE:A modular python library for t-SNE dimensionality reduction and embedding. J Stat Softw 109:1\u201330. https:\/\/doi.org\/10.18637\/jss.v109.i03","journal-title":"J Stat Softw"},{"issue":"60","key":"883_CR28","doi-asserted-by":"publisher","first-page":"3021","DOI":"10.21105\/joss.03021","volume":"6","author":"ML Waskom","year":"2021","unstructured":"Waskom ML (2021) seaborn: Statistical data visualization. J Open Source Softw 6(60):3021. https:\/\/doi.org\/10.21105\/joss.03021","journal-title":"J Open Source Softw"},{"issue":"2","key":"883_CR29","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1021\/ci500588j","volume":"55","author":"T Sander","year":"2015","unstructured":"Sander T, Freyss J, von Korff M, Rufener C (2015) DataWarrior: An open-source program for chemistry aware data visualization and analysis. J Chem Inf Model 55(2):460\u2013473. https:\/\/doi.org\/10.1021\/ci500588j","journal-title":"J Chem Inf Model"},{"issue":"1","key":"883_CR30","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/1758-2946-3-33","volume":"3","author":"NM O\u2019Boyle","year":"2011","unstructured":"O\u2019Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open Babel: an open chemical toolbox. J Cheminformatics 3(1):33. https:\/\/doi.org\/10.1186\/1758-2946-3-33","journal-title":"J Cheminformatics"},{"issue":"15","key":"883_CR31","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.1002\/jcc.23905","volume":"36","author":"WJ Allen","year":"2015","unstructured":"Allen WJ, Balius TE, Mukherjee S, Brozell SR, Moustakas DT, Lang PT, Case DA, Kuntz ID, Rizzo RC (2015) DOCK 6: impact of new features and current docking performance. J Comput Chem 36(15):1132\u20131156. https:\/\/doi.org\/10.1002\/jcc.23905","journal-title":"J Comput Chem"},{"issue":"1","key":"883_CR32","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1038\/s41467-021-20900-6","volume":"12","author":"S-I Hattori","year":"2021","unstructured":"Hattori S-I, Higashi-Kuwata N, Hayashi H, Allu SR, Raghavaiah J, Bulut H, Das D, Anson BJ, Lendy EK, Takamatsu Y, Takamune N, Kishimoto N, Murayama K, Hasegawa K, Li M, Davis DA, Kodama EN, Yarchoan R, Wlodawer A, Misumi S, Mesecar AD, Ghosh AK, Mitsuya H (2021) A small molecule compound with an indole moiety inhibits the main protease of SARS-CoV-2 and blocks virus replication. Nat Commun 12(1):668. https:\/\/doi.org\/10.1038\/s41467-021-20900-6","journal-title":"Nat Commun"},{"issue":"8","key":"883_CR33","first-page":"2535","volume":"10","author":"Y-C Wang","year":"2020","unstructured":"Wang Y-C, Yang W-H, Yang C-S, Hou M-H, Tsai C-L, Chou Y-Z, Hung M-C, Chen Y (2020) Structural basis of SARS-CoV-2 main protease inhibition by a broad-spectrum anti-coronaviral drug. Am J Cancer Res 10(8):2535\u20132545","journal-title":"Am J Cancer Res"},{"key":"883_CR34","doi-asserted-by":"publisher","unstructured":"Malla TN, Pandey S, Aldama L, Feliz D, Noda M, Poudyal I, Phillips GN, Stojkovi\u0107 EA, Schmidt M (2021) Vitamin C Binds to SARS coronavirus-2 main protease essential for viral replication. bioRxiv https:\/\/doi.org\/10.1101\/2021.05.02.442358","DOI":"10.1101\/2021.05.02.442358"},{"issue":"Pt 5","key":"883_CR35","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1107\/S2052252522007497","volume":"9","author":"A Ebrahim","year":"2022","unstructured":"Ebrahim A, Riley BT, Kumaran D, Andi B, Fuchs MR, McSweeney S, Keedy DA (2022) The temperature-dependent conformational ensemble of SARS-CoV-2 main protease (Mpro). IUCrJ 9(Pt 5):682\u2013694. https:\/\/doi.org\/10.1107\/S2052252522007497","journal-title":"IUCrJ"},{"issue":"9","key":"883_CR36","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1007\/s13238-021-00883-2","volume":"13","author":"Y Zhao","year":"2022","unstructured":"Zhao Y, Fang C, Zhang Q, Zhang R, Zhao X, Duan Y, Wang H, Zhu Y, Feng L, Zhao J, Shao M, Yang X, Zhang L, Peng C, Yang K, Ma D, Rao Z, Yang H (2022) Crystal structure of SARS-CoV-2 Main Protease in Complex with Protease Inhibitor PF-07321332. Protein Cell 13(9):689\u2013693. https:\/\/doi.org\/10.1007\/s13238-021-00883-2","journal-title":"Protein Cell"},{"issue":"19","key":"883_CR37","doi-asserted-by":"publisher","first-page":"14702","DOI":"10.1021\/acs.jmedchem.1c01214","volume":"64","author":"AK Ghosh","year":"2021","unstructured":"Ghosh AK, Raghavaiah J, Shahabi D, Yadav M, Anson BJ, Lendy EK, Hattori S-I, Higashi-Kuwata N, Mitsuya H, Mesecar AD (2021) Indole chloropyridinyl ester-derived SARS-CoV-2 3CLpro inhibitors: enzyme inhibition, antiviral efficacy, structure-activity relationship, and X-ray structural studies. J Med Chem 64(19):14702\u201314714 https:\/\/doi.org\/10.1021\/acs.jmedchem.1c01214","journal-title":"J Med Chem"},{"key":"883_CR38","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1186\/s13321-015-0078-2","volume":"7","author":"M W\u00f3jcikowski","year":"2015","unstructured":"W\u00f3jcikowski M, Zielenkiewicz P, Siedlecki P (2015) Open drug discovery toolkit (ODDT): a new open-source player in the drug discovery field. J Cheminformatics 7:26. https:\/\/doi.org\/10.1186\/s13321-015-0078-2","journal-title":"J Cheminformatics"},{"key":"883_CR39","doi-asserted-by":"publisher","unstructured":"RDKit, Landrum G et al (2024) Rdkit Release 2024_03_5 (Q1) 2024. https:\/\/www.rdkit.orghttps:\/\/doi.org\/10.5281\/zenodo.12782092","DOI":"10.5281\/zenodo.12782092"},{"key":"883_CR40","doi-asserted-by":"publisher","unstructured":"Lundberg S, Lee S-I (2017) A unified approach to interpreting model predictions. In: Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS'17). Curran Associates Inc., Red Hook, NY, USA, 4768\u20134777. https:\/\/doi.org\/10.5555\/3295222.3295230","DOI":"10.5555\/3295222.3295230"},{"key":"883_CR41","doi-asserted-by":"publisher","DOI":"10.1093\/database\/bay139","volume":"2019","author":"AA Nikitina","year":"2019","unstructured":"Nikitina AA, Orlov AA, Kozlovskaya LI, Palyulin VA, Osolodkin DI (2019) Enhanced taxonomy annotation of antiviral activity data from ChEMBL. Database 2019:bay139. https:\/\/doi.org\/10.1093\/database\/bay139","journal-title":"Database"},{"issue":"25","key":"883_CR42","doi-asserted-by":"publisher","first-page":"15039","DOI":"10.1021\/acsomega.0c00857","volume":"5","author":"EA Sosnina","year":"2020","unstructured":"Sosnina EA, Sosnin S, Nikitina AA, Nazarov I, Osolodkin DI, Fedorov MV (2020) Recommender systems in antiviral drug discovery. ACS Omega 5(25):15039\u201315051. https:\/\/doi.org\/10.1021\/acsomega.0c00857","journal-title":"ACS Omega"},{"issue":"5","key":"883_CR43","doi-asserted-by":"publisher","first-page":"1800166","DOI":"10.1002\/minf.201800166","volume":"38","author":"AA Orlov","year":"2019","unstructured":"Orlov AA, Khvatov EV, Koruchekov AA, Nikitina AA, Zolotareva AD, Eletskaya AA, Kozlovskaya LI, Palyulin VA, Horvath D, Osolodkin DI, Varnek A (2019) Getting to know the neighbours with GTM: the case of antiviral compounds. Mol Inf 38(5):1800166. https:\/\/doi.org\/10.1002\/minf.201800166","journal-title":"Mol Inf"},{"key":"883_CR44","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-022-01532-x","volume":"9","author":"A Zaliani","year":"2022","unstructured":"Zaliani A, Vangeel L, Reinshagen J, Iaconis D, Kuzikov M, Keminer O, Wolf M, Ellinger B, Esposito F, Corona A, Tramontano E, Manelfi C,Herzog K, Jochmans D, De Jonghe S, Chiu W, Francken T, Schepers J, Collard C, Abbasi K, Claussen C, Summa V, Beccari AR, Neyts J, Gribbon P, Leyssen P (2022) Cytopathic SARS-CoV-2 screening on VERO-E6 cells in a large-scale repurposing effort. Sci. Data 9: 405. https:\/\/doi.org\/10.1038\/s41597-022-01532-x","journal-title":"Sci Data"},{"issue":"1","key":"883_CR45","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1021\/acs.jcim.8b00363","volume":"59","author":"S Liu","year":"2019","unstructured":"Liu S, Alnammi M, Ericksen SS, Voter AF, Ananiev GE, Keck JL, Hoffmann FM, Wildman SA, Gitter A (2019) Practical model selection for prospective virtual screening. J Chem Inf Model 59(1):282\u2013293. https:\/\/doi.org\/10.1021\/acs.jcim.8b00363","journal-title":"J Chem Inf Model"},{"issue":"1","key":"883_CR46","doi-asserted-by":"publisher","first-page":"6086","DOI":"10.1038\/s41598-024-56706-x","volume":"14","author":"O Rainio","year":"2024","unstructured":"Rainio O, Teuho J, Kl\u00e9n R (2024) Evaluation metrics and statistical tests for machine learning. Sci Rep 14(1):6086. https:\/\/doi.org\/10.1038\/s41598-024-56706-x","journal-title":"Sci Rep"},{"issue":"1","key":"883_CR47","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1038\/s42003-023-05071-y","volume":"6","author":"M Lin","year":"2023","unstructured":"Lin M, Zeng X, Duan Y, Yang Z, Ma Y, Yang H, Yang X, Liu X (2023) Molecular mechanism of ensitrelvir inhibiting SARS-CoV-2 main protease and its variants. Commun Biol 6(1):694. https:\/\/doi.org\/10.1038\/s42003-023-05071-y","journal-title":"Commun Biol"},{"key":"883_CR48","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/471371","author":"T-T Nguyen","year":"2015","unstructured":"Nguyen T-T, Huang JZ, Nguyen TT (2015) Unbiased feature selection in learning random forests for high-dimensional data. Sci World J. https:\/\/doi.org\/10.1155\/2015\/471371","journal-title":"Sci World J"}],"container-title":["Journal of Computer-Aided Molecular Design"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10822-026-00883-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10822-026-00883-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10822-026-00883-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T08:09:45Z","timestamp":1783325385000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10822-026-00883-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,6]]},"references-count":48,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["883"],"URL":"https:\/\/doi.org\/10.1007\/s10822-026-00883-6","relation":{},"ISSN":["1573-4951"],"issn-type":[{"value":"1573-4951","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,6]]},"assertion":[{"value":"1 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"173"}}