Combining docking, molecular dynamics simulations, AD-MET pharmacokinetics properties, and MMGBSA calculations to create specialized protocols for running effective virtual screening campaigns on the autoimmune disorder and SARS-CoV-2 main protease

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dc.authoridShallangwa, Gideon Adamu/0000-0002-0700-9898
dc.authoridYagin, Fatma Hilal/0000-0002-9848-7958
dc.authoridSamee, Nagwan Abdel/0000-0001-5957-1383
dc.authoridMahmoud, Noha F./0000-0003-0608-6661
dc.authorwosidMahmoud, Noha F/GPT-3696-2022
dc.authorwosidShallangwa, Gideon Adamu/ABF-6571-2020
dc.authorwosidYagin, Fatma Hilal/ABI-8066-2020
dc.authorwosidSamee, Nagwan Abdel/AEE-5694-2022
dc.authorwosidMahmoud, Noha F./GPT-3706-2022
dc.contributor.authorEdache, Emmanuel Israel
dc.contributor.authorUzairu, Adamu
dc.contributor.authorMamza, Paul Andrew
dc.contributor.authorShallangwa, Gideon Adamu
dc.contributor.authorYagin, Fatma Hilal
dc.contributor.authorSamee, Nagwan Abdel
dc.contributor.authorMahmoud, Noha F.
dc.date.accessioned2024-08-04T20:54:55Z
dc.date.available2024-08-04T20:54:55Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe development of novel medicines to treat autoimmune diseases and SARS-CoV-2 main protease (Mpro), a virus that can cause both acute and chronic illnesses, is an ongoing necessity for the global community. The primary objective of this research is to use CoMFA methods to evaluate the quantitative structure-activity relationship (QSAR) of a select group of chemicals concerning autoimmune illnesses. By performing a molecular docking analysis, we may verify previously observed tendencies and gain insight into how receptors and ligands interact. The results of the 3D QSAR models are quite satisfactory and give significant statistical results: Q_loo & BOTTOM;2 = 0.5548, Q_lto & BOTTOM;2 = 0.5278, R & BOTTOM;2 = 0.9990, F-test = 3,101.141, SDEC = 0.017 for the CoMFA FFDSEL, and Q_loo & BOTTOM;2 = 0.7033, Q_lto & BOTTOM;2 = 0.6827, Q_lmo & BOTTOM;2 = 0.6305, R & BOTTOM;2 = 0.9984, F-test = 1994.0374, SDEC = 0.0216 for CoMFA UVEPLS. The success of these two models in exceeding the external validation criteria used and adhering to the Tropsha and Glorbaikh criteria's upper and lower bounds can be noted. We report the docking simulation of the compounds as an inhibitor of the SARS-CoV-2 Mpro and an autoimmune disorder in this context. For a few chosen autoimmune disorder receptors (protein tyrosine phosphatase, nonreceptor type 22 (lymphoid) isoform 1 (PTPN22), type 1 diabetes, rheumatoid arthritis, and SARS-CoV-2 Mpro, the optimal binding characteristics of the compounds were described. According to their potential for effectiveness, the studied compounds were ranked, and those that demonstrated higher molecular docking scores than the reference drugs were suggested as potential new drug candidates for the treatment of autoimmune disease and SARS-CoV-2 Mpro. Additionally, the results of analyses of drug similarity, ADME (Absorption, Distribution, Metabolism, and Excretion), and toxicity were used to screen the best-docked compounds in which compound 4 scaled through. Finally, molecular dynamics (MD) simulation was used to verify compound 4's stability in the complex with the chosen autoimmune diseases and SARS-CoV-2 Mpro protein. This compound showed a steady trajectory and molecular characteristics with a predictable pattern of interactions. These findings suggest that compound 4 may hold potential as a therapy for autoimmune diseases and SARS-CoV-2 Mpro.en_US
dc.description.sponsorshipPrincess Nourah bint Abdulrahman University Researchers Supporting Project Number (PNURSP 2023R206), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. [PNURSP 2023R206]; Princess Nourah bint Abdulrahman University Researchers Supporting Project; Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabiaen_US
dc.description.sponsorshipThe authors would like to express their gratitude to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP 2023R206), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.r Princess Nourah bint Abdulrahman University Researchers Supporting Project Number (PNURSP 2023R206), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.en_US
dc.identifier.doi10.3389/fmolb.2023.1254230
dc.identifier.issn2296-889X
dc.identifier.pmid37771457en_US
dc.identifier.scopus2-s2.0-85178953622en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.3389/fmolb.2023.1254230
dc.identifier.urihttps://hdl.handle.net/11616/101705
dc.identifier.volume10en_US
dc.identifier.wosWOS:001072710300001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherFrontiers Media Saen_US
dc.relation.ispartofFrontiers in Molecular Biosciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectautoimmune disorderen_US
dc.subjecttype 1 diabetesen_US
dc.subjectrheumatoid arthritisen_US
dc.subjectSARS-CoV-2en_US
dc.subjectCoMFAen_US
dc.subjectdockingen_US
dc.subjectMD simulationsen_US
dc.titleCombining docking, molecular dynamics simulations, AD-MET pharmacokinetics properties, and MMGBSA calculations to create specialized protocols for running effective virtual screening campaigns on the autoimmune disorder and SARS-CoV-2 main proteaseen_US
dc.typeArticleen_US

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