Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis
Background: Due to the constant mutation of virus and the lack of specific therapeutic drugs, the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a huge threat to the health of people, especially those with underlyin...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2022.961154/full |
| _version_ | 1817998486173384704 |
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| author | Jiawei Liu Ling Zhang Jian Gao Baochen Zhang Xiaoli Liu Ninghui Yang Xiaotong Liu Xifu Liu Yu Cheng |
| author_facet | Jiawei Liu Ling Zhang Jian Gao Baochen Zhang Xiaoli Liu Ninghui Yang Xiaotong Liu Xifu Liu Yu Cheng |
| author_sort | Jiawei Liu |
| collection | DOAJ |
| description | Background: Due to the constant mutation of virus and the lack of specific therapeutic drugs, the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a huge threat to the health of people, especially those with underlying diseases. Therefore, drug discovery against the SARS-CoV-2 remains of great significance.Methods: With the main protease of virus as the inhibitor target, 9,614 genistein derivatives were virtually screened by LeDock and AutoDock Vina, and the top 20 compounds with highest normalized scores were obtained. Molecular dynamics simulations were carried out for studying interactions between these 20 compounds and the target protein. The drug-like properties, activity, and ADMET of these compounds were also evaluated by DruLiTo software or online server.Results: Twenty compounds, including compound 11, were screened by normalized molecular docking, which could bind to the target through multiple non-bonding interactions. Molecular dynamics simulation results showed that compounds 2, 4, 5, 11, 13, 14, 17, and 18 had the best binding force with the target protein of SARS-CoV-2, and the absolute values of binding free energies all exceeded 50 kJ/mol. The drug-likeness properties indicated that a variety of compounds including compound 11 were worthy of further study. The results of bioactivity score prediction found that compounds 11 and 12 had high inhibitory activities against protease, which indicated that these two compounds had the potential to be further developed as COVID-19 inhibitors. Finally, compound 11 showed excellent predictive ADMET properties including high absorption and low toxicity.Conclusion: These in silico work results show that the preferred compound 11 (ZINC000111282222), which exhibited strong binding to SARS-CoV-2 main protease, acceptable drug-like properties, protease inhibitory activity and ADMET properties, has great promise for further research as a potential therapeutic agent against COVID-19. |
| first_indexed | 2024-04-14T02:54:48Z |
| format | Article |
| id | doaj.art-74f1f0bff1b842fc8ffc891e9864b984 |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-04-14T02:54:48Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj.art-74f1f0bff1b842fc8ffc891e9864b9842022-12-22T02:16:10ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122022-08-011310.3389/fphar.2022.961154961154Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysisJiawei Liu0Ling Zhang1Jian Gao2Baochen Zhang3Xiaoli Liu4Ninghui Yang5Xiaotong Liu6Xifu Liu7Yu Cheng8Center for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaSchool of Chemical Technology, Shijiazhuang University, Shijiazhuang, ChinaCollege of Plant Protection, Southwest University, Chongqing, ChinaCenter for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaCenter for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaCenter for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaCenter for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaCenter for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaCenter for Drug Innovation and Discovery, College of Life Science, Hebei Normal University, Shijiazhuang, ChinaBackground: Due to the constant mutation of virus and the lack of specific therapeutic drugs, the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a huge threat to the health of people, especially those with underlying diseases. Therefore, drug discovery against the SARS-CoV-2 remains of great significance.Methods: With the main protease of virus as the inhibitor target, 9,614 genistein derivatives were virtually screened by LeDock and AutoDock Vina, and the top 20 compounds with highest normalized scores were obtained. Molecular dynamics simulations were carried out for studying interactions between these 20 compounds and the target protein. The drug-like properties, activity, and ADMET of these compounds were also evaluated by DruLiTo software or online server.Results: Twenty compounds, including compound 11, were screened by normalized molecular docking, which could bind to the target through multiple non-bonding interactions. Molecular dynamics simulation results showed that compounds 2, 4, 5, 11, 13, 14, 17, and 18 had the best binding force with the target protein of SARS-CoV-2, and the absolute values of binding free energies all exceeded 50 kJ/mol. The drug-likeness properties indicated that a variety of compounds including compound 11 were worthy of further study. The results of bioactivity score prediction found that compounds 11 and 12 had high inhibitory activities against protease, which indicated that these two compounds had the potential to be further developed as COVID-19 inhibitors. Finally, compound 11 showed excellent predictive ADMET properties including high absorption and low toxicity.Conclusion: These in silico work results show that the preferred compound 11 (ZINC000111282222), which exhibited strong binding to SARS-CoV-2 main protease, acceptable drug-like properties, protease inhibitory activity and ADMET properties, has great promise for further research as a potential therapeutic agent against COVID-19.https://www.frontiersin.org/articles/10.3389/fphar.2022.961154/fullSARS-CoV-2genisteinmolecular dockingmolecular dynamics simulationADMET |
| spellingShingle | Jiawei Liu Ling Zhang Jian Gao Baochen Zhang Xiaoli Liu Ninghui Yang Xiaotong Liu Xifu Liu Yu Cheng Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis Frontiers in Pharmacology SARS-CoV-2 genistein molecular docking molecular dynamics simulation ADMET |
| title | Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis |
| title_full | Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis |
| title_fullStr | Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis |
| title_full_unstemmed | Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis |
| title_short | Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis |
| title_sort | discovery of genistein derivatives as potential sars cov 2 main protease inhibitors by virtual screening molecular dynamics simulations and admet analysis |
| topic | SARS-CoV-2 genistein molecular docking molecular dynamics simulation ADMET |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2022.961154/full |
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