{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T19:28:51Z","timestamp":1790278131236,"version":"4.1.0"},"reference-count":64,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Council for Scientific and Technological Development (CNPq)","award":["88887.103056\/2025-00"],"award-info":[{"award-number":["88887.103056\/2025-00"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2021\/10577-0"],"award-info":[{"award-number":["2021\/10577-0"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2022\/08730-7"],"award-info":[{"award-number":["2022\/08730-7"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2021\/05262-0"],"award-info":[{"award-number":["2021\/05262-0"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2023\/13894-1"],"award-info":[{"award-number":["2023\/13894-1"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2023\/07366-2"],"award-info":[{"award-number":["2023\/07366-2"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2025\/02990-5"],"award-info":[{"award-number":["2025\/02990-5"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2024\/05454-4"],"award-info":[{"award-number":["2024\/05454-4"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["29794"],"award-info":[{"award-number":["29794"]}]},{"name":"National Council for Scientific and Technological Development (CNPq)","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["88887.103056\/2025-00"],"award-info":[{"award-number":["88887.103056\/2025-00"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2021\/10577-0"],"award-info":[{"award-number":["2021\/10577-0"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2022\/08730-7"],"award-info":[{"award-number":["2022\/08730-7"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2021\/05262-0"],"award-info":[{"award-number":["2021\/05262-0"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2023\/13894-1"],"award-info":[{"award-number":["2023\/13894-1"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2023\/07366-2"],"award-info":[{"award-number":["2023\/07366-2"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2025\/02990-5"],"award-info":[{"award-number":["2025\/02990-5"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2024\/05454-4"],"award-info":[{"award-number":["2024\/05454-4"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["29794"],"award-info":[{"award-number":["29794"]}]},{"name":"Coordination for the Improvement of Higher Education Personnel (CAPES)","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["88887.103056\/2025-00"],"award-info":[{"award-number":["88887.103056\/2025-00"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2021\/10577-0"],"award-info":[{"award-number":["2021\/10577-0"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2022\/08730-7"],"award-info":[{"award-number":["2022\/08730-7"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2021\/05262-0"],"award-info":[{"award-number":["2021\/05262-0"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2023\/13894-1"],"award-info":[{"award-number":["2023\/13894-1"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2023\/07366-2"],"award-info":[{"award-number":["2023\/07366-2"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2025\/02990-5"],"award-info":[{"award-number":["2025\/02990-5"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2024\/05454-4"],"award-info":[{"award-number":["2024\/05454-4"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["29794"],"award-info":[{"award-number":["29794"]}]},{"name":"S\u00e3o Paulo Research Foundation","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"FINEP","award":["88887.103056\/2025-00"],"award-info":[{"award-number":["88887.103056\/2025-00"]}]},{"name":"FINEP","award":["2021\/10577-0"],"award-info":[{"award-number":["2021\/10577-0"]}]},{"name":"FINEP","award":["2022\/08730-7"],"award-info":[{"award-number":["2022\/08730-7"]}]},{"name":"FINEP","award":["2021\/05262-0"],"award-info":[{"award-number":["2021\/05262-0"]}]},{"name":"FINEP","award":["2023\/13894-1"],"award-info":[{"award-number":["2023\/13894-1"]}]},{"name":"FINEP","award":["2023\/07366-2"],"award-info":[{"award-number":["2023\/07366-2"]}]},{"name":"FINEP","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"FINEP","award":["2025\/02990-5"],"award-info":[{"award-number":["2025\/02990-5"]}]},{"name":"FINEP","award":["2024\/05454-4"],"award-info":[{"award-number":["2024\/05454-4"]}]},{"name":"FINEP","award":["29794"],"award-info":[{"award-number":["29794"]}]},{"name":"FINEP","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"FAPESP","award":["88887.103056\/2025-00"],"award-info":[{"award-number":["88887.103056\/2025-00"]}]},{"name":"FAPESP","award":["2021\/10577-0"],"award-info":[{"award-number":["2021\/10577-0"]}]},{"name":"FAPESP","award":["2022\/08730-7"],"award-info":[{"award-number":["2022\/08730-7"]}]},{"name":"FAPESP","award":["2021\/05262-0"],"award-info":[{"award-number":["2021\/05262-0"]}]},{"name":"FAPESP","award":["2023\/13894-1"],"award-info":[{"award-number":["2023\/13894-1"]}]},{"name":"FAPESP","award":["2023\/07366-2"],"award-info":[{"award-number":["2023\/07366-2"]}]},{"name":"FAPESP","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]},{"name":"FAPESP","award":["2025\/02990-5"],"award-info":[{"award-number":["2025\/02990-5"]}]},{"name":"FAPESP","award":["2024\/05454-4"],"award-info":[{"award-number":["2024\/05454-4"]}]},{"name":"FAPESP","award":["29794"],"award-info":[{"award-number":["29794"]}]},{"name":"FAPESP","award":["2023\/18211-0"],"award-info":[{"award-number":["2023\/18211-0"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Viruses"],"abstract":"<jats:p>The SARS-CoV-2 main protease (Mpro) is a validated therapeutic target for inhibiting viral replication. Few compounds have advanced clinically, underscoring the difficulty in optimizing both target affinity and drug-like properties. To address this challenge, we integrated machine learning (ML), molecular docking, and molecular dynamics (MD) simulations to investigate the balance between pharmacodynamic (PD) and pharmacokinetic (PK) properties in Mpro inhibitor design. We developed ML models to classify Mpro inhibitors based on experimental IC50 data, combining molecular descriptors with structural insights from MD simulations. Our Support Vector Machine (SVM) model achieved strong performance (training accuracy = 0.84, ROC AUC = 0.91; test accuracy = 0.79, ROC AUC = 0.86), while our Logistic Regression model (training accuracy = 0.78, ROC AUC = 0.85; test accuracy = 0.76, ROC AUC = 0.83). Notably, PK descriptors often exhibited opposing trends to binding affinity: hydrophilic features enhanced binding affinity but compromised PK properties, whereas hydrogen bonding, hydrophobic, and \u03c0\u2013\u03c0 interactions in Mpro subsites S2 and S3\/S4 are fundamental for binding affinity. Our findings highlight the need for a balanced approach in Mpro inhibitor design, strategically targeting these subsites may balance PD and PK properties. For the first time, we demonstrate antagonistic trends between pharmacokinetic (PK) and pharmacodynamic (PD) features through the integrated application of ML\/MD. This study provides a computational framework for rational Mpro inhibitors, combining ML and MD to investigate the complex interplay between enzyme inhibition and drug likeness. These insights may guide the hit-to-lead optimization of the novel next-generation Mpro inhibitors of SARS-CoV-2 with preclinical and clinical potential.<\/jats:p>","DOI":"10.3390\/v17070935","type":"journal-article","created":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T07:55:43Z","timestamp":1751442943000},"page":"935","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Antagonistic Trends Between Binding Affinity and Drug-Likeness in SARS-CoV-2 Mpro Inhibitors Revealed by Machine Learning"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5669-1723","authenticated-orcid":false,"given":"Anacleto Silva de","family":"Souza","sequence":"first","affiliation":[{"name":"Department of Microbiology, Institute of Biomedical Sciences, University of S\u00e3o Paulo, Sao Paulo 05508-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vitor Martins de Freitas","family":"Amorim","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Institute of Biomedical Sciences, University of S\u00e3o Paulo, Sao Paulo 05508-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8420-4889","authenticated-orcid":false,"given":"Eduardo Pereira","family":"Soares","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Institute of Biomedical Sciences, University of S\u00e3o Paulo, Sao Paulo 05508-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5284-4630","authenticated-orcid":false,"given":"Robson Francisco","family":"de Souza","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Institute of Biomedical Sciences, University of S\u00e3o Paulo, Sao Paulo 05508-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5664-8055","authenticated-orcid":false,"given":"Cristiane Rodrigues","family":"Guzzo","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Institute of Biomedical Sciences, University of S\u00e3o Paulo, Sao Paulo 05508-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,30]]},"reference":[{"key":"ref_1","unstructured":"(2025, June 08). World Health Organization. Available online: https:\/\/covid19.who.int."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"de Souza, A.S., de Amorim, V.M.F., Guardia, G.D.A., dos Santos, F.F., Ulrich, H., Galante, P.A.F., de Souza, R.F., and Guzzo, C.R. (2022). Severe Acute Respiratory Syndrome Coronavirus 2 Variants of Concern: A Perspective for Emerging More Transmissible and Vaccine-Resistant Strains. Viruses, 14.","DOI":"10.20944\/preprints202202.0261.v1"},{"key":"ref_3","unstructured":"(2025, January 25). GISAID Genomic Epidemiology of SARS-CoV-2 with Subsampling Focused Globally over the Past 6 Months. Available online: https:\/\/www.gisaid.org\/phylodynamics\/global\/nextstrain\/."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.1016\/j.cell.2025.01.042","article-title":"Bat-Infecting Merbecovirus HKU5-CoV Lineage 2 Can Use Human ACE2 as a Cell Entry Receptor","volume":"188","author":"Chen","year":"2025","journal-title":"Cell"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"De Amorim, V.M.F., Soares, E.P., de Ferrari, A.S.A., Merighi, D.G.S., de Souza, R.F., Guzzo, C.R., and de Souza, A.S. (2024). 3-Chymotrypsin-like Protease (3CLpro) of SARS-CoV-2: Validation as a Molecular Target, Proposal of a Novel Catalytic Mechanism, and Inhibitors in Preclinical and Clinical Trials. Viruses, 16.","DOI":"10.3390\/v16060844"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e2117142119","DOI":"10.1073\/pnas.2117142119","article-title":"Structural Basis for Replicase Polyprotein Cleavage and Substrate Specificity of Main Protease from SARS-CoV-2","volume":"119","author":"Zhao","year":"2022","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1007\/s11224-022-02089-6","article-title":"Structural Differences in 3C-like Protease (Mpro) from SARS-CoV and SARS-CoV-2: Molecular Insights Revealed by Molecular Dynamics Simulations","volume":"34","author":"Parmar","year":"2023","journal-title":"Struct. Chem."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/S0006-291X(67)80055-X","article-title":"On the Size of the Active Site in Proteases. I. Papain","volume":"27","author":"Schechter","year":"1967","journal-title":"Biochem. Biophys. Res. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"eabo7201","DOI":"10.1126\/science.abo7201","article-title":"Open Science Discovery of Potent Noncovalent SARS-CoV-2 Main Protease Inhibitors","volume":"382","author":"Boby","year":"2023","journal-title":"Science"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115772","DOI":"10.1016\/j.ejmech.2023.115772","article-title":"Structure and Function of SARS-CoV and SARS-CoV-2 Main Proteases and Their Inhibition: A Comprehensive Review","volume":"260","author":"Li","year":"2023","journal-title":"Eur. J. Med. Chem."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"103004","DOI":"10.1016\/j.jbc.2023.103004","article-title":"Structural Basis of Nirmatrelvir and Ensitrelvir Activity against Naturally Occurring Polymorphisms of the SARS-CoV-2 Main Protease","volume":"299","author":"Noske","year":"2023","journal-title":"J. Biol. Chem."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1038\/s41422-020-0356-z","article-title":"Boceprevir, GC-376, and Calpain Inhibitors II, XII Inhibit SARS-CoV-2 Viral Replication by Targeting the Viral Main Protease","volume":"30","author":"Ma","year":"2020","journal-title":"Cell Res."},{"key":"ref_13","unstructured":"(2025, January 26). ASAP AI-Driven Structure-Enabled Antiviral Platform (ASAP). Available online: https:\/\/asapdiscovery.org\/."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1186\/1758-2946-3-33","article-title":"Open Babel: An Open Chemical Toolbox","volume":"3","author":"Banck","year":"2011","journal-title":"J. Cheminform."},{"key":"ref_15","unstructured":"The Open Babel Team (2025, January 26). Open Babel\u2014The Chemistry Toolbox\u2014Open Babel Openbabel-3-1-1 Documentation. Available online: https:\/\/openbabel.org\/."},{"key":"ref_16","unstructured":"Marvin (2025, January 26). MarvinSketch. Available online: https:\/\/docs.chemaxon.com\/display\/lts-europium\/marvinsketch-downloads.md."},{"key":"ref_17","first-page":"11339","article-title":"Quantitative Structure-Activity Relationships, Molecular Docking and Molecular Dynamics Simulations Reveal Drug Repurposing Candidates as Potent SARS-CoV-2 Main Protease Inhibitors","volume":"40","author":"Guzzo","year":"2021","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_18","unstructured":"NumPy Community (2025, January 26). NumPy Reference. Available online: https:\/\/numpy.org\/community\/."},{"key":"ref_19","unstructured":"The Pandas Development Team (2025, January 26). Pandas-Dev\/Pandas. Available online: https:\/\/github.com\/pandas-dev\/pandas."},{"key":"ref_20","unstructured":"Landrum, G., Tosco, P., Kelley, B., Rodriguez, R., Cosgrove, D., Vianello, R., Gedeck, P., Jones, G. (2025, January 25). Rdkit\/rdkit: 2024_09_6 (Q3 2024) Release. Available online: https:\/\/zenodo.org\/records\/14535873."},{"key":"ref_21","first-page":"2825","article-title":"Scikit-Learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_22","unstructured":"Plotly Technologies Inc (2025, January 25). Collaborative Data Science Publisher: Plotly Technologies Inc. Place of Publication: Montr\u00e9al, QC Date of Publication: 2015. Available online: https:\/\/plot.ly."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/MCSE.2007.55","article-title":"Matplotlib: A 2D Graphics Environment","volume":"9","author":"Hunter","year":"2007","journal-title":"Comput. Sci. Eng."},{"key":"ref_24","unstructured":"The Matplotlib Development Team (2025, January 25). Matplotlib: Visualization with Python. Available online: https:\/\/matplotlib.org\/."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.21105\/joss.03021","article-title":"Seaborn: Statistical Data Visualization","volume":"6","author":"Waskom","year":"2021","journal-title":"J. Open Source Softw."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s13321-019-0336-9","article-title":"Dimorphite-DL: An Open-Source Program for Enumerating the Ionization States of Drug-like Small Molecules","volume":"11","author":"Ropp","year":"2019","journal-title":"J. Cheminform."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Azlim Khan, A.K., and Ahamed Hassain Malim, N.H. (2023). Comparative Studies on Resampling Techniques in Machine Learning and Deep Learning Models for Drug-Target Interaction Prediction. Molecules, 28.","DOI":"10.3390\/molecules28041663"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1002\/jcc.20084","article-title":"UCSF Chimera\u2014A Visualization System for Exploratory Research and Analysis","volume":"25","author":"Pettersen","year":"2004","journal-title":"J. Comput. Chem."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate Structure Prediction of Biomolecular Interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3891","DOI":"10.1021\/acs.jcim.1c00203","article-title":"AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings","volume":"61","author":"Eberhardt","year":"2021","journal-title":"J. Chem. Inf. Model."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1002\/jcc.21334","article-title":"AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading","volume":"31","author":"Trott","year":"2010","journal-title":"J. Comput. Chem."},{"key":"ref_32","unstructured":"(2025, January 25). GROMACS 2022 Documentation. Available online: https:\/\/manual.gromacs.org\/2022\/index.html."},{"key":"ref_33","unstructured":"(2025, January 25). GROMACS 2022 Source Code. Available online: https:\/\/manual.gromacs.org\/2022\/download.html."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3864","DOI":"10.1021\/acs.jpcb.7b00272","article-title":"1.14*CM1A-LBCC: Localized Bond-Charge Corrected CM1A Charges for Condensed-Phase Simulations","volume":"121","author":"Dodda","year":"2017","journal-title":"J. Phys. Chem. B"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"W331","DOI":"10.1093\/nar\/gkx312","article-title":"LigParGen Web Server: An Automatic OPLS-AA Parameter Generator for Organic Ligands","volume":"45","author":"Dodda","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"6665","DOI":"10.1073\/pnas.0408037102","article-title":"Potential Energy Functions for Atomic-Level Simulations of Water and Organic and Biomolecular Systems","volume":"102","author":"Jorgensen","year":"2005","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0169-409X(00)00129-0","article-title":"Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings","volume":"46","author":"Lipinski","year":"2001","journal-title":"Adv. Drug Deliv. Rev."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1602\/neurorx.2.4.541","article-title":"Medicinal Chemical Properties of Successful Central Nervous System Drugs","volume":"2","author":"Pajouhesh","year":"2005","journal-title":"NeuroRx"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1038\/nchem.1243","article-title":"Quantifying the Chemical Beauty of Drugs","volume":"4","author":"Bickerton","year":"2012","journal-title":"Nat. Chem."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"7559","DOI":"10.1021\/jm060642i","article-title":"Structure-Brain Exposure Relationships","volume":"49","author":"Hitchcock","year":"2006","journal-title":"J. Med. Chem."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1007\/s12250-020-00288-1","article-title":"Comparative Antiviral Efficacy of Viral Protease Inhibitors against the Novel SARS-CoV-2 In Vitro","volume":"35","author":"Zhang","year":"2020","journal-title":"Virol. Sin."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1186\/s12985-020-01457-0","article-title":"Analysis of the Efficacy of HIV Protease Inhibitors against SARS-CoV-2\u2019s Main Protease","volume":"17","author":"Mahdi","year":"2020","journal-title":"Virol. J."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5014","DOI":"10.1016\/j.csbj.2022.09.002","article-title":"Deep Learning-Based Molecular Dynamics Simulation for Structure-Based Drug Design against SARS-CoV-2","volume":"20","author":"Sun","year":"2022","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/s41586-023-05905-z","article-title":"Computational Approaches Streamlining Drug Discovery","volume":"616","author":"Sadybekov","year":"2023","journal-title":"Nature"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"100434","DOI":"10.1016\/j.imr.2020.100434","article-title":"Artificial Intelligence and COVID-19: A Multidisciplinary Approach","volume":"9","author":"Ahuja","year":"2020","journal-title":"Integr. Med. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1016\/j.dsx.2020.06.068","article-title":"Application of Artificial Intelligence in COVID-19 Drug Repurposing","volume":"14","author":"Mohanty","year":"2020","journal-title":"Diabetes Metab. Syndr."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"103422","DOI":"10.1016\/j.drudis.2022.103422","article-title":"Drug Repurposing Using Real-World Data","volume":"28","author":"Tan","year":"2023","journal-title":"Drug Discov. Today"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"128933","DOI":"10.1016\/j.foodchem.2020.128933","article-title":"An in-Silico Evaluation of Different Bioactive Molecules of Tea for Their Inhibition Potency against Non Structural Protein-15 of SARS-CoV-2","volume":"346","author":"Sharma","year":"2021","journal-title":"Food Chem."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"8894","DOI":"10.1080\/07391102.2021.1922310","article-title":"Computational Basis of SARS-CoV 2 Main Protease Inhibition: An Insight from Molecular Dynamics Simulation Based Findings","volume":"40","author":"Avti","year":"2021","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"826","DOI":"10.1021\/acscombsci.0c00140","article-title":"Profiling SARS-CoV-2 Main Protease (M) Binding to Repurposed Drugs Using Molecular Dynamics Simulations in Classical and Neural Network-Trained Force Fields","volume":"22","author":"Gupta","year":"2020","journal-title":"ACS Comb. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"e2000113","DOI":"10.1002\/minf.202000113","article-title":"QSAR Modeling of SARS-CoV M 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":"ref_52","doi-asserted-by":"crossref","first-page":"101262","DOI":"10.1016\/j.jscs.2021.101262","article-title":"Prediction of Inhibitory Constants of Compounds against SARS-CoV 3CLpro Enzyme with 2D-QSAR Model","volume":"25","author":"Yu","year":"2021","journal-title":"J. Saudi Chem. Soc."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zaki, M.E.A., Al-Hussain, S.A., Masand, V.H., Akasapu, S., Bajaj, S.O., El-Sayed, N.N.E., Ghosh, A., and Lewaa, I. (2021). Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis. Pharmaceuticals, 14.","DOI":"10.3390\/ph14040357"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"123708","DOI":"10.1016\/j.molliq.2023.123708","article-title":"Improved SAR and QSAR Models of SARS-CoV-2 Mpro Inhibitors Based on Machine Learning","volume":"394","author":"Tong","year":"2024","journal-title":"J. Mol. Liq."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2146","DOI":"10.1039\/D4MD00106K","article-title":"Identification of SARS-CoV-2 Mpro Inhibitors through Deep Reinforcement Learning for Drug Design and Computational Chemistry Approaches","volume":"15","author":"Hazemann","year":"2024","journal-title":"RSC Med. Chem."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1007\/s11224-022-02008-9","article-title":"SMILES-Based 2D-QSAR and Similarity Search for Identification of Potential New Scaffolds for Development of SARS-CoV-2 MPRO Inhibitors","volume":"33","author":"Costa","year":"2022","journal-title":"Struct. Chem."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1007\/s43153-023-00332-z","article-title":"In Silico Prediction of the Inhibition of New Molecules on SARS-CoV-2 3CL Protease by Using QSAR: PSOSVR Approach","volume":"41","author":"Madani","year":"2023","journal-title":"Braz. J. Chem. Eng."},{"key":"ref_58","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_59","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_60","doi-asserted-by":"crossref","first-page":"2830","DOI":"10.1038\/s41598-025-86016-9","article-title":"Identification of Promising SARS-CoV-2 Main Protease Inhibitor through Molecular Docking, Dynamics Simulation, and ADMET Analysis","volume":"15","author":"Sharma","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"e0267471","DOI":"10.1371\/journal.pone.0267471","article-title":"Computational Prediction of Potential Inhibitors for SARS-CoV-2 Main Protease Based on Machine Learning, Docking, MM-PBSA Calculations, and Metadynamics","volume":"17","author":"Santana","year":"2022","journal-title":"PLoS ONE"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"29683","DOI":"10.1039\/D4RA04502E","article-title":"Identification of Lead Inhibitors for 3CLpro of SARS-CoV-2 Target Using Machine Learning Based Virtual Screening, ADMET Analysis, Molecular Docking and Molecular Dynamics Simulations","volume":"14","author":"Chhetri","year":"2024","journal-title":"RSC Adv."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.1126\/science.abl4784","article-title":"An Oral SARS-CoV-2 M Inhibitor Clinical Candidate for the Treatment of COVID-19","volume":"374","author":"Owen","year":"2021","journal-title":"Science"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1021\/acsmedchemlett.4c00146","article-title":"SARS-CoV-2 Main Protease Inhibitors That Leverage Unique Interactions with the Solvent Exposed S3 Site of the Enzyme","volume":"15","author":"Blankenship","year":"2024","journal-title":"ACS Med. Chem. Lett."}],"container-title":["Viruses"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4915\/17\/7\/935\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:01:49Z","timestamp":1760032909000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4915\/17\/7\/935"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":64,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["v17070935"],"URL":"https:\/\/doi.org\/10.3390\/v17070935","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2025.05.14.654028","asserted-by":"object"}]},"ISSN":["1999-4915"],"issn-type":[{"value":"1999-4915","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,30]]}}}