{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,20]],"date-time":"2026-09-20T03:18:03Z","timestamp":1789874283211,"version":"4.0.1"},"reference-count":91,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2025,12,13]],"date-time":"2025-12-13T00:00:00Z","timestamp":1765584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100019000","name":"Ministry of National Defense Medical Affairs Bureau","doi-asserted-by":"crossref","award":["MND-MAB-C09-112035"],"award-info":[{"award-number":["MND-MAB-C09-112035"]}],"id":[{"id":"10.13039\/501100019000","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>The COVID-19 outbreak has had a tremendous socioeconomic impact around the world, and although there are currently some drugs that have been granted authorization by the U.S. FDA for the treatment of COVID-19, there are still some restrictions on their use. As a result, it is still necessary to urgently carry out related drug development research. Deep generative models and cheminformatics were used in this study to design and screen novel candidates for potential anti-SARS-CoV-2 small molecule compounds. In this study, the small molecule structure of Molnupiravir which has been authorized by the U.S. FDA for emergency use was used to be a model in a similarity search based on the BIOVIA Available Chemicals Directory (BIOVIA ACD) database using the BIOVIA Discovery Studio (DS) software (version 2022). There were 61,480 similar structures of Molnupiravir, which were used as training dataset for the deep generative model, and then the reinforcement learning model was used to generate 6000 small molecule structures. To further confirm whether those molecule structures potentially possess the ability of anti-SARS-CoV-2, cheminformatics techniques were used to assess 38 small molecule compounds with potential anti-SARS-CoV-2 activity. The suitability of 38 small molecule structures was calculated using ADMET analysis. Finally, one compound structure, Molecule_36, passed ADMET and was unpatented. This study demonstrates that Molecule_36 may have better potential than Molnupiravir does in affinity with SARS-CoV-2 RdRp and ADMET. We provide a combination of generative deep neural networks and cheminformatics for developing new anti-SARS-CoV-2 compounds. However, additional chemical refinement and experimental validation will be required to determine its stability, mechanism of action, and antiviral efficacy.<\/jats:p>","DOI":"10.3390\/ijms262412017","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T09:36:39Z","timestamp":1765791399000},"page":"12017","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Designing Novel Compound Candidates Against SARS-CoV-2 Using Generative Deep Neural Networks and Cheminformatics"],"prefix":"10.3390","volume":"26","author":[{"given":"Shang-Yang","family":"Li","sequence":"first","affiliation":[{"name":"Graduate Institute of Public Health, College of Public Health, National Defense Medical University, Taipei City 114201, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2642-2935","authenticated-orcid":false,"given":"Chin-Mao","family":"Hung","sequence":"additional","affiliation":[{"name":"Institute of Preventive Medicine, National Defense Medical University, New Taipei City 237010, Taiwan"},{"name":"Graduate Institute of Medical Sciences, College of Medicine, National Defense Medical University, Taipei City 114201, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7666-2420","authenticated-orcid":false,"given":"Hsin-Yi","family":"Hung","sequence":"additional","affiliation":[{"name":"School of Pharmacy, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih-Wei","family":"Lai","sequence":"additional","affiliation":[{"name":"College of Pharmacy, National Defense Medical University, Taipei City 114201, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng-Chang","family":"Lee","sequence":"additional","affiliation":[{"name":"Graduate Institute of Public Health, College of Public Health, National Defense Medical University, Taipei City 114201, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fisher, D., and Heymann, D. (2020). Q&A: The novel coronavirus outbreak causing COVID-19. BMC Med., 18.","DOI":"10.1186\/s12916-020-01533-w"},{"key":"ref_2","unstructured":"WHO (2023, March 31). WHO Coronavirus (COVID-19) Dashboard. Available online: https:\/\/data.who.int\/dashboards\/covid19."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Murgolo, N., Therien, A.G., Howell, B., Klein, D., Koeplinger, K., Lieberman, L.A., Adam, G.C., Flynn, J., McKenna, P., and Swaminathan, G. (2021). SARS-CoV-2 tropism, entry, replication, and propagation: Considerations for drug discovery and development. PLoS Pathog., 17.","DOI":"10.1371\/journal.ppat.1009225"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"n2713","DOI":"10.1136\/bmj.n2713","article-title":"COVID-19: Pfizer\u2019s paxlovid is 89% effective in patients at risk of serious illness, company reports","volume":"375","author":"Mahase","year":"2021","journal-title":"BMJ"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"n2697","DOI":"10.1136\/bmj.n2697","article-title":"COVID-19: UK becomes first country to authorise antiviral molnupiravir","volume":"375","author":"Mahase","year":"2021","journal-title":"BMJ"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.jhealeco.2016.01.012","article-title":"Innovation in the pharmaceutical industry: New estimates of R&D costs","volume":"47","author":"DiMasi","year":"2016","journal-title":"J. Health Econ."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mouchlis, V.D., Afantitis, A., Serra, A., Fratello, M., Papadiamantis, A.G., Aidinis, V., Lynch, I., Greco, D., and Melagraki, G. (2021). Advances in de Novo Drug Design: From Conventional to Machine Learning Methods. Int. J. Mol. Sci., 22.","DOI":"10.3390\/ijms22041676"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.drudis.2020.10.010","article-title":"Artificial intelligence in drug discovery and development","volume":"26","author":"Paul","year":"2021","journal-title":"Drug Discov. Today"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1002\/med.21764","article-title":"Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions","volume":"41","author":"Vatansever","year":"2021","journal-title":"Med. Res. Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"10520","DOI":"10.1021\/acs.chemrev.8b00728","article-title":"Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery","volume":"119","author":"Yang","year":"2019","journal-title":"Chem. Rev."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Pirzada, R.H., Javaid, N., and Choi, S. (2020). The Roles of the NLRP3 Inflammasome in Neurodegenerative and Metabolic Diseases and in Relevant Advanced Therapeutic Interventions. Genes, 11.","DOI":"10.3390\/genes11020131"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.1007\/s11030-021-10217-3","article-title":"Artificial intelligence to deep learning: Machine intelligence approach for drug discovery","volume":"25","author":"Gupta","year":"2021","journal-title":"Mol. Divers."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1021\/acscentsci.7b00572","article-title":"Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules","volume":"4","author":"Wei","year":"2018","journal-title":"ACS Cent. Sci."},{"key":"ref_14","unstructured":"De Cao, N.K., and Kipf, T. (2022). MolGAN: An implicit generative model for small molecular graphs. arXiv."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/s13321-017-0235-x","article-title":"Molecular de-novo design through deep reinforcement learning","volume":"9","author":"Olivecrona","year":"2017","journal-title":"J. Cheminform."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.1038\/s41587-019-0224-x","article-title":"GENTRL (Deep learning enables rapid identification of potent DDR1 kinase inhibitors)","volume":"37","author":"Zhavoronkov","year":"2019","journal-title":"Nat. Biotechnol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhavoronkov, A., Zagribelnyy, B., Zhebrak, A., Aladinskiy, V., Terentiev, V., Vanhaelen, Q., Bezrukov, D.S., Polykovskiy, D., Shayakhmetov, R., and Filimonov, A. (2020). Potential non-covalent SARS-CoV-2 3C-like protease inhibitors designed using generative deep learning approaches and reviewed by human medicinal chemist in virtual reality. ChemRxiv.","DOI":"10.26434\/chemrxiv.12301457.v1"},{"key":"ref_18","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":"2024","journal-title":"J. Chem. Inf. Model"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"575","DOI":"10.4155\/fmc-2020-0262","article-title":"De novo design of new chemical entities for SARS-CoV-2 using artificial intelligence","volume":"13","author":"Bung","year":"2021","journal-title":"Future Med. Chem."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Andrianov, A.M., Shuldau, M.A., Furs, K.V., Yushkevich, A.M., and Tuzikov, A.V. (2023). AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24098083"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"105728","DOI":"10.1016\/j.compbiomed.2022.105728","article-title":"De Novo design of potential inhibitors against SARS-CoV-2 Mpro","volume":"147","author":"Li","year":"2022","journal-title":"Comput. Biol. Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"104967","DOI":"10.1016\/j.compbiomed.2021.104967","article-title":"De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations","volume":"139","author":"Arshia","year":"2021","journal-title":"Comput. Biol. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"4261","DOI":"10.3390\/cimb45050271","article-title":"De Novo Design of Anti-COVID Drugs Using Machine Learning-Based Equivariant Diffusion Model Targeting the Spike Protein","volume":"45","author":"Niranjan","year":"2023","journal-title":"Curr. Issues Mol. Biol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Khan, A., Bhrdwaj, A., Sharma, K., Arugonda, R., Kaur, N., Chaudhary, R., Shaheen, U., Panwar, U., Natchimuthu, V., and Kumar, A. (Med. Chem., 2025). Potential Inhibitors of SARS-CoV-2 Developed through Machine Learning, Molecular Docking, and MD Simulation, Med. Chem., Online ahead of print.","DOI":"10.2174\/0115734064370188250527043536"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"8853056","DOI":"10.1155\/2021\/8853056","article-title":"An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19","volume":"2021","author":"Gurung","year":"2021","journal-title":"Biomed. Res. Int."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1186\/s12967-020-02439-0","article-title":"Analysis of SARS-CoV-2 RNA-dependent RNA polymerase as a potential therapeutic drug target using a computational approach","volume":"18","author":"Aftab","year":"2020","journal-title":"J. Transl. Med."},{"key":"ref_27","first-page":"967","article-title":"Evaluation of molnupiravir analogues as novel coronavirus (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) inhibitors\u2014An in silico docking and admet simulation study","volume":"25","year":"2021","journal-title":"J. Res. Pharm."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3572","DOI":"10.1021\/jm020266b","article-title":"Prediction of aqueous solubility of a diverse set of compounds using quantitative structure-property relationships","volume":"46","author":"Cheng","year":"2003","journal-title":"J. Med. Chem."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3867","DOI":"10.1021\/jm000292e","article-title":"Prediction of drug absorption using multivariate statistics","volume":"43","author":"Egan","year":"2000","journal-title":"J. Med. Chem."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.1038\/nprot.2007.303","article-title":"Determination of drug permeability and prediction of drug absorption in Caco-2 monolayers","volume":"2","author":"Hubatsch","year":"2007","journal-title":"Nat. Protoc."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Nguyen, T.-T.-L., Duong, V.-A., and Maeng, H.-J. (2021). Pharmaceutical Formulations with P-Glycoprotein Inhibitory Effect as Promising Approaches for Enhancing Oral Drug Absorption and Bioavailability. Pharmaceutics, 13.","DOI":"10.3390\/pharmaceutics13071103"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3164","DOI":"10.1021\/jm0492002","article-title":"A bioavailability score","volume":"48","author":"Martin","year":"2005","journal-title":"J. Med. Chem."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5691","DOI":"10.1021\/acs.jmedchem.5b00201","article-title":"Volume of distribution in drug design: Miniperspective","volume":"58","author":"Smith","year":"2015","journal-title":"J. Med. Chem."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1038\/nrd1032","article-title":"ADMET in silico modelling: Towards prediction paradise?","volume":"2","author":"Gifford","year":"2003","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1517\/17425255.2014.876006","article-title":"The role of drug metabolizing enzymes in clearance","volume":"10","author":"Di","year":"2014","journal-title":"Expert. Opin. Drug Metab. Toxicol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1308","DOI":"10.1021\/ci030283p","article-title":"Use of robust classification techniques for the prediction of human cytochrome P450 2D6 inhibition","volume":"43","author":"Susnow","year":"2003","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"ref_37","first-page":"391","article-title":"The effect of cytochrome P450 metabolism on drug response, interactions, and adverse effects","volume":"76","author":"Lynch","year":"2007","journal-title":"Am. Fam. Physician"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.jmgm.2005.10.004","article-title":"Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods","volume":"24","author":"Yap","year":"2006","journal-title":"J. Mol. Graph. Model"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1124\/pr.118.015578","article-title":"Organic Cation Transporters in Health and Disease","volume":"72","author":"Koepsell","year":"2020","journal-title":"Pharmacol. Rev."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1078\/0944-7113-00044","article-title":"Comparative study of the assay of Artemia salina L. and the estimate of the medium lethal dose (LD50 value) in mice, to determine oral acute toxicity of plant extracts","volume":"8","author":"Parra","year":"2001","journal-title":"Phytomedicine"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"112290","DOI":"10.1016\/j.ejmech.2020.112290","article-title":"hERG toxicity assessment: Useful guidelines for drug design","volume":"195","author":"Garrido","year":"2020","journal-title":"Eur. J. Med. Chem."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/1758-2946-1-8","article-title":"Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions","volume":"1","author":"Ertl","year":"2009","journal-title":"J. Cheminform."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Faisal, S., Badshah, S.L., Kubra, B., Sharaf, M., Emwas, A.H., Jaremko, M., and Abdalla, M. (2021). Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition. Molecules, 27.","DOI":"10.3390\/molecules27010223"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"118252","DOI":"10.1016\/j.biopha.2025.118252","article-title":"Targeting SARS-CoV-2 RNA-dependent RNA polymerase with the coumarin derivative BPR2-D2: Evidence from cell-based and enzymatic studies","volume":"189","author":"Tang","year":"2025","journal-title":"Biomed. Pharmacother."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1038\/s41586-020-2368-8","article-title":"Structure of replicating SARS-CoV-2 polymerase","volume":"584","author":"Hillen","year":"2020","journal-title":"Nature"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1177\/2472555220942123","article-title":"RNA-Dependent RNA Polymerase as a Target for COVID-19 Drug Discovery","volume":"25","author":"Zhu","year":"2020","journal-title":"SLAS Discov."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"18356","DOI":"10.1021\/acsomega.0c02096","article-title":"Prediction of Small Molecule Inhibitors Targeting the Severe Acute Respiratory Syndrome Coronavirus-2 RNA-dependent RNA Polymerase","volume":"5","author":"Ahmad","year":"2020","journal-title":"ACS Omega"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"e04502","DOI":"10.1016\/j.heliyon.2020.e04502","article-title":"SARS-CoV-2 RNA Dependent RNA polymerase (RdRp)\u2014A drug repurposing study","volume":"6","author":"Ahmad","year":"2020","journal-title":"Heliyon"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"6039","DOI":"10.1080\/07391102.2021.1875886","article-title":"RNA dependent RNA polymerase (RdRp) as a drug target for SARS-CoV2","volume":"40","author":"Mishra","year":"2022","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1126\/science.abb7498","article-title":"Structure of the RNA-dependent RNA polymerase from COVID-19 virus","volume":"368","author":"Gao","year":"2020","journal-title":"Science"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"104793","DOI":"10.1016\/j.antiviral.2020.104793","article-title":"Remdesivir and SARS-CoV-2: Structural requirements at both nsp12 RdRp and nsp14 Exonuclease active-sites","volume":"178","author":"Shannon","year":"2020","journal-title":"Antiviral. Res."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Latosi\u0144ska, M., and Latosi\u0144ska, J.N. (2024). Favipiravir Analogues as Inhibitors of SARS-CoV-2 RNA-Dependent RNA Polymerase, Combined Quantum Chemical Modeling, Quantitative Structure-Property Relationship, and Molecular Docking Study. Molecules, 29.","DOI":"10.3390\/molecules29020441"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"104613","DOI":"10.1016\/j.compbiomed.2021.104613","article-title":"In silico investigation on the inhibitory effect of fungal secondary metabolites on RNA dependent RNA polymerase of SARS-CoV-II: A docking and molecular dynamic simulation study","volume":"135","author":"Ebrahimi","year":"2021","journal-title":"Comput. Biol. Med."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"6290","DOI":"10.1080\/07391102.2020.1796804","article-title":"Investigating the binding affinity, interaction, and structure-activity-relationship of 76 prescription antiviral drugs targeting RdRp and Mpro of SARS-CoV-2","volume":"39","author":"Ahmed","year":"2021","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"29015","DOI":"10.1039\/D1RA04460E","article-title":"Comparative assessment of RNA-dependent RNA polymerase (RdRp) inhibitors under clinical trials to control SARS-CoV2 using rigorous computational workflow","volume":"11","author":"Goswami","year":"2021","journal-title":"RSC Adv."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1002\/wcms.14","article-title":"Cation\u2013\u03c0 and anion\u2013\u03c0 interactions","volume":"1","author":"Frontera","year":"2011","journal-title":"WIREs Comput. Mol. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3984","DOI":"10.1039\/D2SC00763K","article-title":"Mining anion-aromatic interactions in the Protein Data Bank","volume":"13","author":"Glanowski","year":"2022","journal-title":"Chem. Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"304","DOI":"10.6026\/97320630018304","article-title":"Molecular docking analysis and dynamics simulation of salbutamol with the monoamine oxidase B (MAO-B) enzyme","volume":"18","year":"2022","journal-title":"Bioinformation"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1039\/D3RA08147H","article-title":"Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets","volume":"14","author":"Voitsitskyi","year":"2024","journal-title":"RSC Adv."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Khan, F.I., Kang, T., Ali, H., and Lai, D. (2021). Remdesivir Strongly Binds to RNA-Dependent RNA Polymerase, Membrane Protein, and Main Protease of SARS-CoV-2: Indication From Molecular Modeling and Simulations. Front. Pharmacol., 12, https:\/\/doi.org\/10.3389\/fphar.2021.710778. Erratum in Front. Pharmacol. 2022, 13, 1027099.","DOI":"10.3389\/fphar.2021.710778"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1021\/acs.chemrev.7b00305","article-title":"Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation","volume":"118","author":"Zhou","year":"2018","journal-title":"Chem. Rev."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1038\/s41467-020-20542-0","article-title":"Mechanism of SARS-CoV-2 polymerase stalling by remdesivir","volume":"12","author":"Kokic","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1038\/s41598-018-36987-9","article-title":"N(+)-C-H\u00b7\u00b7\u00b7O Hydrogen bonds in protein-ligand complexes","volume":"9","author":"Itoh","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1970","DOI":"10.1039\/C7MD00381A","article-title":"A systematic analysis of atomic protein-ligand interactions in the PDB","volume":"8","author":"Schapira","year":"2017","journal-title":"Medchemcomm"},{"key":"ref_65","first-page":"793","article-title":"The mechanism of RNA capping by SARS-CoV-2","volume":"609","author":"Park","year":"2022","journal-title":"Nature"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Koulgi, S., Jani, V., Uppuladinne, V.N.M., Sonavane, U., and Joshi, R. (2021). Natural plant products as potential inhibitors of RNA dependent RNA polymerase of Severe Acute Respiratory Syndrome Coronavirus-2. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0251801"},{"key":"ref_67","first-page":"3204","article-title":"SARS-CoV-2 RNA dependent RNA polymerase (RdRp) targeting: An in silico perspective","volume":"39","author":"Elfiky","year":"2021","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"19986","DOI":"10.1038\/s41598-022-24695-4","article-title":"Discovering new potential inhibitors to SARS-CoV-2 RNA dependent RNA polymerase (RdRp) using high throughput virtual screening and molecular dynamics simulations","volume":"12","author":"Brunt","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1002\/prot.10567","article-title":"N-H...O, O-H...O, and C-H...O hydrogen bonds in protein-ligand complexes: Strong and weak interactions in molecular recognition","volume":"54","author":"Sarkhel","year":"2004","journal-title":"Proteins"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"e2021946118","DOI":"10.1073\/pnas.2021946118","article-title":"Structure of the SARS-CoV-2 RNA-dependent RNA polymerase in the presence of favipiravir-RTP","volume":"118","author":"Naydenova","year":"2021","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1186\/s40364-025-00758-2","article-title":"Integrating artificial intelligence in drug discovery and early drug development: A transformative approach","volume":"13","author":"Ocana","year":"2025","journal-title":"Biomark. Res."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"117592","DOI":"10.1016\/j.lfs.2020.117592","article-title":"Ribavirin, Remdesivir, Sofosbuvir, Galidesivir, and Tenofovir against SARS-CoV-2 RNA dependent RNA polymerase (RdRp): A molecular docking study","volume":"253","author":"Elfiky","year":"2020","journal-title":"Life Sci."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1080\/13543776.2021.1880568","article-title":"SARS-CoV-2 RNA-dependent RNA polymerase as a therapeutic target for COVID-19","volume":"31","author":"Vicenti","year":"2021","journal-title":"Expert. Opin. Ther. Pat."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"100042","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":"ref_75","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1007\/s10796-021-10131-x","article-title":"The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic","volume":"23","author":"Piccialli","year":"2021","journal-title":"Inf. Syst. Front."},{"key":"ref_76","unstructured":"Shin, B., Park, S., Kang, K., and Ho, J.C. (2019, January 8\u201310). Self-attention based molecule representation for predicting drug-target interaction. Proceedings of the Machine Learning for Healthcare Conference, Ann Arbor, MI, USA."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1016\/j.csbj.2020.03.025","article-title":"Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model","volume":"18","author":"Beck","year":"2020","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"e1468","DOI":"10.1002\/wcms.1468","article-title":"Next generation 3D pharmacophore modeling","volume":"10","author":"Schaller","year":"2020","journal-title":"Wiley Interdiscip. Rev. Comput. Mol. Sci."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Maia, E.H.B., Assis, L.C., De Oliveira, T.A., Da Silva, A.M., and Taranto, A.G. (2020). Structure-based virtual screening: From classical to artificial intelligence. Front. Chem., 8.","DOI":"10.3389\/fchem.2020.00343"},{"key":"ref_80","unstructured":"BIOVIA (2025, August 12). Discovery Studio Software Version. Available online: https:\/\/www.3ds.com\/products\/biovia."},{"key":"ref_81","unstructured":"NIH (2023, February 19). PubChem, Available online: https:\/\/pubchem.ncbi.nlm.nih.gov."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"2897","DOI":"10.1021\/ci900437n","article-title":"Computer Software Review: Reaxys","volume":"49","author":"Goodman","year":"2009","journal-title":"J. Chem. Inf. Model."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1186\/s13321-016-0148-0","article-title":"Comparing structural fingerprints using a literature-based similarity benchmark","volume":"8","author":"Sayle","year":"2016","journal-title":"J. Cheminform."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1152","DOI":"10.1039\/C7MD00063D","article-title":"Identification of steroid-like natural products as antiplasmodial agents by 2D and 3D similarity-based virtual screening","volume":"8","author":"Pavadai","year":"2017","journal-title":"Medchemcomm"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.ddtec.2004.11.007","article-title":"Lead-and drug-like compounds: The rule-of-five revolution","volume":"1","author":"Lipinski","year":"2004","journal-title":"Drug Discov. Today Technol."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"6696012","DOI":"10.1155\/2021\/6696012","article-title":"Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2","volume":"2021","author":"Yassine","year":"2021","journal-title":"Biomed. Res. Int."},{"key":"ref_87","unstructured":"PDB, R. (2022, September 03). RCSB Protein Data Bank. Available online: https:\/\/www.rcsb.org\/structure\/7OZV."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1002\/jcc.10306","article-title":"Detailed analysis of grid-based molecular docking: A case study of CDOCKER\u2014A CHARMm-based MD docking algorithm","volume":"24","author":"Wu","year":"2003","journal-title":"J. Comput. Chem."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"42717","DOI":"10.1038\/srep42717","article-title":"SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules","volume":"7","author":"Daina","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"4066","DOI":"10.1021\/acs.jmedchem.5b00104","article-title":"pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures","volume":"58","author":"Pires","year":"2015","journal-title":"J. Med. Chem."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.csbj.2019.02.006","article-title":"Ligand-based Pharmacophore Modeling, Virtual Screening and Molecular Docking Studies for Discovery of Potential Topoisomerase I Inhibitors","volume":"17","author":"Pal","year":"2019","journal-title":"Comput. Struct. Biotechnol. J."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/24\/12017\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T05:28:59Z","timestamp":1765949339000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/24\/12017"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,13]]},"references-count":91,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["ijms262412017"],"URL":"https:\/\/doi.org\/10.3390\/ijms262412017","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,13]]}}}