Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations
The main protease of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known as 3CL<sup>pro</sup>, is crucial in the virus’s life cycle and plays a pivotal role in COVID-19. Understanding how small molecules inhibit 3CL<sup>pro</sup>’s activity is vital for de...
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2025-02-01
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| author | Jianzhong Chen Jian Wang Wanchun Yang Lu Zhao Xiaoyan Xu |
| author_facet | Jianzhong Chen Jian Wang Wanchun Yang Lu Zhao Xiaoyan Xu |
| author_sort | Jianzhong Chen |
| collection | DOAJ |
| description | The main protease of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known as 3CL<sup>pro</sup>, is crucial in the virus’s life cycle and plays a pivotal role in COVID-19. Understanding how small molecules inhibit 3CL<sup>pro</sup>’s activity is vital for developing anti-COVID-19 therapeutics. To this end, we employed Gaussian accelerated molecular dynamics (GaMD) simulations to enhance the sampling of 3CL<sup>pro</sup> conformations and conducted correlation network analysis (CNA) to explore the interactions between different structural domains. Our findings indicate that a CNA-identified node in domain II of 3CL<sup>pro</sup> acts as a conduit, transferring conformational changes from the catalytic regions in domains I and II, triggered by the binding of inhibitors (7YY, 7XB, and Y6G), to domain III, thereby modulating 3CL<sup>pro</sup>’s activity. Normal mode analysis (NMA) and principal component analysis (PCA) revealed that inhibitor binding affects the structural flexibility and collective movements of the catalytic sites and domain III, influencing 3CL<sup>pro</sup>’s function. The binding free energies, predicted by both MM-GBSA and QM/MM-GBSA methods, showed a high correlation with experimental data, validating the reliability of our analyses. Furthermore, residues L27, H41, C44, S46, M49, N142, G143, S144, C145, H163, H164, M165, and E166, identified through residue-based free energy decomposition, present promising targets for the design of anti-COVID-19 drugs and could facilitate the development of clinically effective 3CL<sup>pro</sup> inhibitors. |
| format | Article |
| id | doaj-art-ea334146fb2e4c0ab7381fcfe80f0740 |
| institution | DOAJ |
| issn | 1420-3049 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj-art-ea334146fb2e4c0ab7381fcfe80f07402025-08-20T03:12:09ZengMDPI AGMolecules1420-30492025-02-0130480510.3390/molecules30040805Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA CalculationsJianzhong Chen0Jian Wang1Wanchun Yang2Lu Zhao3Xiaoyan Xu4School of Science, Shandong Jiaotong University, Jinan 250357, ChinaSchool of Science, Shandong Jiaotong University, Jinan 250357, ChinaSchool of Science, Shandong Jiaotong University, Jinan 250357, ChinaSchool of Science, Shandong Jiaotong University, Jinan 250357, ChinaSchool of Science, Shandong Jiaotong University, Jinan 250357, ChinaThe main protease of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known as 3CL<sup>pro</sup>, is crucial in the virus’s life cycle and plays a pivotal role in COVID-19. Understanding how small molecules inhibit 3CL<sup>pro</sup>’s activity is vital for developing anti-COVID-19 therapeutics. To this end, we employed Gaussian accelerated molecular dynamics (GaMD) simulations to enhance the sampling of 3CL<sup>pro</sup> conformations and conducted correlation network analysis (CNA) to explore the interactions between different structural domains. Our findings indicate that a CNA-identified node in domain II of 3CL<sup>pro</sup> acts as a conduit, transferring conformational changes from the catalytic regions in domains I and II, triggered by the binding of inhibitors (7YY, 7XB, and Y6G), to domain III, thereby modulating 3CL<sup>pro</sup>’s activity. Normal mode analysis (NMA) and principal component analysis (PCA) revealed that inhibitor binding affects the structural flexibility and collective movements of the catalytic sites and domain III, influencing 3CL<sup>pro</sup>’s function. The binding free energies, predicted by both MM-GBSA and QM/MM-GBSA methods, showed a high correlation with experimental data, validating the reliability of our analyses. Furthermore, residues L27, H41, C44, S46, M49, N142, G143, S144, C145, H163, H164, M165, and E166, identified through residue-based free energy decomposition, present promising targets for the design of anti-COVID-19 drugs and could facilitate the development of clinically effective 3CL<sup>pro</sup> inhibitors.https://www.mdpi.com/1420-3049/30/4/805SARS-CoV2-3CL<sup>pro</sup>GaMD simulationscorrelation network analysisnormal mode analysisMM-GBSA |
| spellingShingle | Jianzhong Chen Jian Wang Wanchun Yang Lu Zhao Xiaoyan Xu Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations Molecules SARS-CoV2-3CL<sup>pro</sup> GaMD simulations correlation network analysis normal mode analysis MM-GBSA |
| title | Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations |
| title_full | Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations |
| title_fullStr | Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations |
| title_full_unstemmed | Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations |
| title_short | Identifying Inhibitor-SARS-CoV2-3CL<sup>pro</sup> Binding Mechanism Through Molecular Docking, GaMD Simulations, Correlation Network Analysis and MM-GBSA Calculations |
| title_sort | identifying inhibitor sars cov2 3cl sup pro sup binding mechanism through molecular docking gamd simulations correlation network analysis and mm gbsa calculations |
| topic | SARS-CoV2-3CL<sup>pro</sup> GaMD simulations correlation network analysis normal mode analysis MM-GBSA |
| url | https://www.mdpi.com/1420-3049/30/4/805 |
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