Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis
Abstract The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced com...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-86016-9 |
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| author | Ganesh Sharma Neeraj Kumar Chandra Shekhar Sharma Taha Alqahtani Yewulsew Kebede Tiruneh Sharifa Sultana Gabriel Vinícius Rolim Silva Gabriela de Lima Menezes Magdi E. A. Zaki Jonas Ivan Nobre Oliveira |
| author_facet | Ganesh Sharma Neeraj Kumar Chandra Shekhar Sharma Taha Alqahtani Yewulsew Kebede Tiruneh Sharifa Sultana Gabriel Vinícius Rolim Silva Gabriela de Lima Menezes Magdi E. A. Zaki Jonas Ivan Nobre Oliveira |
| author_sort | Ganesh Sharma |
| collection | DOAJ |
| description | Abstract The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced computational techniques such as molecular docking and molecular dynamics simulations were used to screen a series of antiviral compounds for their potential inhibitory effect on the SARS-CoV-2 Mpro. A comprehensive analysis of compounds from the ChemDiv and PubChem databases was performed. The physicochemical properties, pharmacokinetics, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiles were evaluated to determine drug similarity and safety. Compound 4896 − 4038 proved to be the most promising candidate. It exhibited a favorable balance between molecular weight (491.06) and lipophilicity (logP 3.957), high intestinal absorption (92.119%), and broad tissue distribution (VDss of 0.529), indicating good oral bioavailability and therapeutic potential. Molecular docking studies showed that 4896 − 4038 has a strong binding affinity to the active site of Mpro and forms key interactions, such as hydrogen bonds, carbon-hydrogen bonds, pi-sulfur, and multiple van der Waals and pi-pi stacked bonds. The binding energy was comparable to that of the reference drug X77, indicating potential efficacy. Molecular dynamics simulations over 300 ns confirmed the stability of the Mpro/4896 − 4038 complex of protein-ligand. Free energy landscape mapping and MM/PBSA calculations further substantiated the favorable binding and stability of the complex. Importantly, 4896 − 4038 exhibited a comparatively favorable safety profile. In summary, compound 4896 − 4038 shows significant potential as a potent SARS-CoV-2 Mpro inhibitor, combining potent inhibitory activity with favorable pharmacokinetic and safety profiles. These results support the further development of 4896 − 4038 as a promising therapeutic agent in the fight against COVID-19 that warrants experimental validation and clinical investigation. |
| format | Article |
| id | doaj-art-f68adbfe10b043c9b6b103514128b9af |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-f68adbfe10b043c9b6b103514128b9af2025-01-26T12:23:48ZengNature PortfolioScientific Reports2045-23222025-01-0115111810.1038/s41598-025-86016-9Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysisGanesh Sharma0Neeraj Kumar1Chandra Shekhar Sharma2Taha Alqahtani3Yewulsew Kebede Tiruneh4Sharifa Sultana5Gabriel Vinícius Rolim Silva6Gabriela de Lima Menezes7Magdi E. A. Zaki8Jonas Ivan Nobre Oliveira9Department of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Bhupal Nobles’ UniversityDepartment of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Bhupal Nobles’ UniversityDepartment of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Bhupal Nobles’ UniversityDepartment of Pharmacology, College of Pharmacy, King Khalid UniversityDepartment: Biology, Biomedical Sciences stream Bahir Dar UniversityDepartment of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do NorteDepartment of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do NorteDepartment of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do NorteDepartment of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU)Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do NorteAbstract The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced computational techniques such as molecular docking and molecular dynamics simulations were used to screen a series of antiviral compounds for their potential inhibitory effect on the SARS-CoV-2 Mpro. A comprehensive analysis of compounds from the ChemDiv and PubChem databases was performed. The physicochemical properties, pharmacokinetics, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiles were evaluated to determine drug similarity and safety. Compound 4896 − 4038 proved to be the most promising candidate. It exhibited a favorable balance between molecular weight (491.06) and lipophilicity (logP 3.957), high intestinal absorption (92.119%), and broad tissue distribution (VDss of 0.529), indicating good oral bioavailability and therapeutic potential. Molecular docking studies showed that 4896 − 4038 has a strong binding affinity to the active site of Mpro and forms key interactions, such as hydrogen bonds, carbon-hydrogen bonds, pi-sulfur, and multiple van der Waals and pi-pi stacked bonds. The binding energy was comparable to that of the reference drug X77, indicating potential efficacy. Molecular dynamics simulations over 300 ns confirmed the stability of the Mpro/4896 − 4038 complex of protein-ligand. Free energy landscape mapping and MM/PBSA calculations further substantiated the favorable binding and stability of the complex. Importantly, 4896 − 4038 exhibited a comparatively favorable safety profile. In summary, compound 4896 − 4038 shows significant potential as a potent SARS-CoV-2 Mpro inhibitor, combining potent inhibitory activity with favorable pharmacokinetic and safety profiles. These results support the further development of 4896 − 4038 as a promising therapeutic agent in the fight against COVID-19 that warrants experimental validation and clinical investigation.https://doi.org/10.1038/s41598-025-86016-9COVID-19MproMolecular DockingSARS-CoV-23CLproMolecular dynamics, ADMET |
| spellingShingle | Ganesh Sharma Neeraj Kumar Chandra Shekhar Sharma Taha Alqahtani Yewulsew Kebede Tiruneh Sharifa Sultana Gabriel Vinícius Rolim Silva Gabriela de Lima Menezes Magdi E. A. Zaki Jonas Ivan Nobre Oliveira Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis Scientific Reports COVID-19 Mpro Molecular Docking SARS-CoV-2 3CLpro Molecular dynamics, ADMET |
| title | Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis |
| title_full | Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis |
| title_fullStr | Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis |
| title_full_unstemmed | Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis |
| title_short | Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis |
| title_sort | identification of promising sars cov 2 main protease inhibitor through molecular docking dynamics simulation and admet analysis |
| topic | COVID-19 Mpro Molecular Docking SARS-CoV-2 3CLpro Molecular dynamics, ADMET |
| url | https://doi.org/10.1038/s41598-025-86016-9 |
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