{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T05:01:45Z","timestamp":1790053305773,"version":"4.0.1"},"reference-count":49,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T00:00:00Z","timestamp":1789257600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"King Abdulaziz University","id":[{"id":"https:\/\/ror.org\/02ma4wv74","id-type":"ROR","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/02ma4wv74","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Viruses"],"abstract":"<jats:p>Human immunodeficiency virus (HIV) is one of the viruses that has co-evolved within human populations for a considerable time. With the evolution of new drug-resistant HIV strains, the necessity to discover novel drugs has become an issue of great concern, especially those that have increased binding affinities and inhibitory activity towards RT enzymes. This study used an in silico approach to identify potential HIV-RT inhibitory candidates from Origanum vulgare (oregano). An initial in silico screening of approximately 820 compounds was conducted, and based on molecular docking-derived binding energy scores, four compounds (IMPHY000687, IMPHY007084, IMPHY004619, and IMPHY012021), with docking scores of \u22129.42, \u22129.32, \u22129.24, and \u22129.23 kcal\/mol, respectively, were selected as the top-ranked phytocompounds and were subsequently validated using multiple computational approaches. These compounds were geometrically optimized using quantum-chemical calculations, and detailed interaction analyses were performed using a redocking procedure. Reproducibility of the dynamic behavior was evaluated by carrying out independent replica molecular dynamics simulations for 300 ns each for all complexes. The ligand-dependent conformational dynamics were identified using RMSD and RMSF analyses, along with variations in positional changes during simulation times. PCA and FEL analyses helped in identifying the conformations sampled by the system under study. In addition, QM\/MM calculations provided complementary information on the electronic characteristics of the individual protein\u2013ligand systems. Machine learning-based quantitative structure\u2013activity relationship (QSAR) prediction of experimentally validated HIV-RT inhibitors was applied to predict inhibitory potency, yielding predicted pIC50 values for the selected phytochemicals compared with the reference molecule. All in all, comprehensive computational analyses have ranked these phytochemicals as HIV-RT inhibitors that need further experimental verification.<\/jats:p>","DOI":"10.3390\/v18091010","type":"journal-article","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T08:10:23Z","timestamp":1789373423000},"page":"1010","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Anti-HIV Potential of Origanum vulgare Compounds Targeting Viral Reverse Transcriptase with High Binding and Stability Validated by Machine Learning"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6889-0730","authenticated-orcid":false,"given":"Leena Hussein","family":"Bajrai","sequence":"first","affiliation":[{"name":"Biochemistry Department, Faculty of Science, King Abdulaziz University, Jeddah 21362, Saudi Arabia"},{"name":"Special Infectious Agents Unit-BSL3, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah 21362, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0971-5275","authenticated-orcid":false,"given":"Reem","family":"Ghazali","sequence":"additional","affiliation":[{"name":"Department of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah 21362, Saudi Arabia"},{"name":"Food, Nutrition and Lifestyle Unit, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah 21362, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,13]]},"reference":[{"key":"ref_1","unstructured":"(2025, December 29). HIV Data and Statistics. Available online: https:\/\/www.who.int\/teams\/global-hiv-hepatitis-and-stis-programmes\/hiv\/strategic-information\/hiv-data-and-statistics."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Singh, A.K., and Das, K. (2022). Insights into HIV-1 Reverse Transcriptase (RT) Inhibition and Drug Resistance from Thirty Years of Structural Studies. Viruses, 14.","DOI":"10.3390\/v14051027"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.tips.2021.10.004","article-title":"Update and latest advances in antiretroviral therapy","volume":"43","author":"Delgado","year":"2022","journal-title":"Trends Pharmacol. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Vanangamudi, M., Palaniappan, S., Kathiravan, M.K., and Namasivayam, V. (2023). Strategies in the design and development of non-nucleoside reverse transcriptase inhibitors (NNRTIs). Viruses, 15.","DOI":"10.3390\/v15101992"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1002\/cmdc.202000849","article-title":"Advances in nucleoside and nucleotide analogues in tackling human immunodeficiency virus and hepatitis virus infections","volume":"16","author":"Ramesh","year":"2021","journal-title":"ChemMedChem"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"13596535231201162","DOI":"10.1177\/13596535231201162","article-title":"HIV drug resistance in the era of contemporary antiretroviral therapy: A clinical perspective","volume":"28","author":"Carr","year":"2023","journal-title":"Antivir. Ther."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1002\/(SICI)1098-1128(200003)20:2<129::AID-MED2>3.0.CO;2-A","article-title":"The HIV-1 reverse transcription (RT) process as target for RT inhibitors","volume":"20","author":"Jonckheere","year":"2000","journal-title":"Med. Res. Rev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1867","DOI":"10.2174\/138161206776873626","article-title":"Effects of nucleotides and nucleotide analogue inhibitors of HIV-1 reverse transcriptase in a ratchet model of polymerase translocation","volume":"12","author":"Gotte","year":"2006","journal-title":"Curr. Pharm. Des."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Raheem, I.T., Girijavallabhan, V., Fillgrove, K.L., Goh, S.L., Bahnck-Teets, C., Huang, Q., Li, F., Wan, B.-L., O\u2019Donnell, G.T., and Patteson, J.B. (2025). MK-8527 is a novel inhibitor of HIV-1 reverse transcriptase translocation with potential for extended-duration dosing. PLoS Biol., 23.","DOI":"10.1371\/journal.pbio.3003308"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Mahendra, F.R., Prakoso, I., Marzelino, A., Fadhillah, M.R., Hasibuan, M.M.A., Suparningtyas, J.F., Kristiadi, M., Setiawan, A.G., and Rahman, F.I. (2025). Optimisation of peptides targeting reverse transcriptase HIV-1 using QSAR, machine learning, and computational approaches. Front. Pharmacol., 16.","DOI":"10.3389\/fphar.2025.1707377"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1567","DOI":"10.1016\/j.apsb.2021.11.009","article-title":"Approved HIV reverse transcriptase inhibitors in the past decade","volume":"12","author":"Li","year":"2022","journal-title":"Acta Pharm. Sin. B"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1007\/s00203-024-03846-3","article-title":"Fighting nature with nature: Antiviral compounds that target retroviruses","volume":"206","author":"Siew","year":"2024","journal-title":"Arch. Microbiol."},{"key":"ref_13","first-page":"1934578X241282923","article-title":"Medicinal plants as effective antiviral agents and their potential benefits","volume":"19","author":"Atampugbire","year":"2024","journal-title":"Nat. Prod. Commun."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.2174\/1381612825666190702095612","article-title":"Essential oil and ethanol extract of oregano (Origanum vulgare L.) from Armenian flora as a natural source of terpenes, flavonoids and other phytochemicals with antiradical, antioxidant, metal chelating, tyrosinase inhibitory and antibacterial activity","volume":"25","author":"Moghrovyan","year":"2019","journal-title":"Curr. Pharm. Des."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1640","DOI":"10.2174\/1568026623666230201144522","article-title":"Exploration of computational aids for effective drug designing and management of viral diseases: A comprehensive review","volume":"23","author":"Khan","year":"2023","journal-title":"Curr. Top. Med. Chem."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2190","DOI":"10.2174\/1568026623666221019110334","article-title":"Computational approaches in the discovery and development of therapeutic and prophylactic agents for viral diseases","volume":"22","author":"Gaurav","year":"2022","journal-title":"Curr. Top. Med. Chem."},{"key":"ref_17","unstructured":"(2025, December 29). Discovery of MK-8527, a Long-Acting HIV Nucleoside Reverse Transcriptase Translocation Inhibitor. Available online: https:\/\/www.natap.org\/2024\/CROI\/croi_07.htm."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1093\/nar\/28.1.235","article-title":"The Protein Data Bank","volume":"28","author":"Berman","year":"2000","journal-title":"Nucleic Acids Res."},{"key":"ref_19","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_20","doi-asserted-by":"crossref","first-page":"4329","DOI":"10.1038\/s41598-018-22631-z","article-title":"IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics","volume":"8","author":"Mohanraj","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"W448","DOI":"10.1093\/nar\/gkv306","article-title":"MTiOpenScreen: A web server for structure-based virtual screening","volume":"43","author":"Rey","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"W5","DOI":"10.1093\/nar\/gkab255","article-title":"ADMETlab 2.0: An integrated online platform for accurate and comprehensive predictions of ADMET properties","volume":"49","author":"Xiong","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_23","first-page":"5281","article-title":"RDKit: A software suite for cheminformatics, computational chemistry, and predictive modeling","volume":"8","author":"Landrum","year":"2013","journal-title":"Greg Landrum"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1186\/s13321-020-00456-1","article-title":"An open source chemical structure curation pipeline using RDKit","volume":"12","author":"Bento","year":"2020","journal-title":"J. Cheminform."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2175","DOI":"10.1007\/s11030-025-11332-1","article-title":"Mechanistic inhibition of FtsZ-driven bacterial cytokinesis by natural products: An integrated machine learning and advanced drug discovery approach","volume":"30","author":"Singh","year":"2025","journal-title":"Mol. Divers."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1002\/jcc.27058","article-title":"Implementation of real-time TDDFT for periodic systems in the open-source PySCF software package","volume":"44","author":"Hanasaki","year":"2023","journal-title":"J. Comput. Chem."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e1340","DOI":"10.1002\/wcms.1340","article-title":"PySCF: The Python-based simulations of chemistry framework","volume":"8","author":"Sun","year":"2018","journal-title":"WIREs Comput. Mol. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1021\/ct700248k","article-title":"Performance of B3LYP density functional methods for a large set of organic molecules","volume":"4","author":"Jorgensen","year":"2008","journal-title":"J. Chem. Theory Comput."},{"key":"ref_29","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_30","doi-asserted-by":"crossref","first-page":"e984","DOI":"10.1093\/cid\/ciag135","article-title":"Antiretroviral Activity, Pharmacokinetics, and Safety of MK-8527, an Oral Nucleoside Reverse Transcriptase Translocation Inhibitor, in Adults with HIV-1 Who Had Not Previously Taken Antiretroviral Agents: Results From 2 Open-Label, Phase 1 Studies","volume":"82","author":"Carstens","year":"2026","journal-title":"Clin. Infect. Dis."},{"key":"ref_31","first-page":"82","article-title":"Pymol: An open-source molecular graphics tool","volume":"40","author":"DeLano","year":"2002","journal-title":"CCP4 Newsl. Protein Crystallogr."},{"key":"ref_32","unstructured":"Biovia, D.S. (2019). Discovery Studio Visualizer, Dassault Syst\u00e8mes."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"6183","DOI":"10.1021\/acs.jcim.3c01153","article-title":"AmberTools","volume":"63","author":"Case","year":"2023","journal-title":"J. Chem. Inf. Model."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1007\/s00894-010-0650-7","article-title":"An improved generalized AMBER force field (GAFF) for urea","volume":"16","author":"Peukert","year":"2010","journal-title":"J. Mol. Model."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"174501","DOI":"10.1063\/1.4872239","article-title":"Structure and dynamics of TIP3P, TIP4P, and TIP5P water near smooth and atomistic walls of different hydroaffinity","volume":"140","author":"Harrach","year":"2014","journal-title":"J. Chem. Phys."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"124108","DOI":"10.1063\/1.4978807","article-title":"Application of Berendsen barostat in dissipative particle dynamics for nonequilibrium dynamic simulation","volume":"146","author":"Lin","year":"2017","journal-title":"J. Chem. Phys."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1002\/1096-987X(20010415)22:5<501::AID-JCC1021>3.0.CO;2-V","article-title":"A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations","volume":"22","year":"2001","journal-title":"J. Comput. Chem."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"10089","DOI":"10.1063\/1.464397","article-title":"Particle mesh Ewald: An N log (N) method for Ewald sums in large systems","volume":"98","author":"Darden","year":"1993","journal-title":"J. Chem. Phys."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"107322","DOI":"10.1016\/j.compbiolchem.2020.107322","article-title":"Geo-Measures: A PyMOL plugin for protein structure ensembles analysis","volume":"87","author":"Kagami","year":"2020","journal-title":"Comput. Biol. Chem."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Singh, R., Dwivedi, V.D., and Chouhan, G. (2026). Machine learning\u2013guided discovery of spirocyclic inhibitors targeting Mycobacterium tuberculosis FtsZ. Folia Microbiol.","DOI":"10.1007\/s12223-026-01542-x"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"e74301","DOI":"10.1002\/slct.74301","article-title":"Machine Learning-Based Discovery of Natural PknB Inhibitors Against Drug-Resistant Mycobacterium tuberculosis with Multi-Scale Modeling and Quantum Mechanical Validation","volume":"11","author":"Singh","year":"2026","journal-title":"ChemistrySelect"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"D1180","DOI":"10.1093\/nar\/gkad1004","article-title":"The ChEMBL Database in 2023: A drug discovery platform spanning multiple bioactivity data types and time periods","volume":"52","author":"Zdrazil","year":"2023","journal-title":"Nucleic Acids Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1002\/jcc.21707","article-title":"PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints","volume":"32","author":"Yap","year":"2011","journal-title":"J. Comput. Chem."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"eadt8916","DOI":"10.1126\/sciadv.adt8916","article-title":"Development of enhanced HIV-1 non-nucleoside reverse transcriptase inhibitors with improved resistance and pharmacokinetic profiles","volume":"11","author":"Wang","year":"2025","journal-title":"Sci. Adv."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"36902","DOI":"10.1039\/D4RA07561G","article-title":"Synthesis, crystal structure, and antiviral evaluation of new imidazopyridine-schiff base derivatives: In vitro and in silico anti-HIV studies","volume":"14","author":"Azzouzi","year":"2024","journal-title":"RSC Adv."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"116941","DOI":"10.1016\/j.ejmech.2024.116941","article-title":"Identification of novel diarylpyrimidine derivatives as potent HIV-1 non-nucleoside reverse transcriptase inhibitors against wild-type and K103N mutant viruses","volume":"280","author":"Jiang","year":"2024","journal-title":"Eur. J. Med. Chem."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"323","DOI":"10.2174\/1570162043351093","article-title":"Conformational Changes in HIV-1 Reverse Transcriptase Induced by Nonnucleoside Reverse Transcriptase Inhibitor Binding","volume":"2","author":"Temiz","year":"2004","journal-title":"CHR"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"bpaf081","DOI":"10.1093\/biomethods\/bpaf081","article-title":"In-silico identification of phytochemical compounds from various medicinal plants as potent HIV-1 non-nucleoside reverse transcriptase inhibitors utilizing molecular docking and molecular dynamics simulations","volume":"10","author":"Danladi","year":"2025","journal-title":"Biol. Methods Protoc."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"100080","DOI":"10.1016\/j.pscia.2025.100080","article-title":"Artificial intelligence in human immunodeficiency virus mutation prediction and drug design: Advancing personalized treatment and prevention","volume":"3","author":"Oyediran","year":"2025","journal-title":"Pharm. Sci. Adv."}],"container-title":["Viruses"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4915\/18\/9\/1010\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T04:11:00Z","timestamp":1790050260000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4915\/18\/9\/1010"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,13]]},"references-count":49,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["v18091010"],"URL":"https:\/\/doi.org\/10.3390\/v18091010","relation":{},"ISSN":["1999-4915"],"issn-type":[{"value":"1999-4915","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,13]]}}}