Computational Discovery of SARS-CoV-2 NSP 16 Drug Candidates Based on Pharmacophore Modeling and Molecular Dynamics Simulation
| Autor: | Zahra Hesari, Sajad Moradi, Mohsen Shahlaei, Elham Tazikeh-Lemeski, Samaneh Zolghadri |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Drug 2019-20 coronavirus outbreak 030102 biochemistry & molecular biology Coronavirus disease 2019 (COVID-19) Drug discovery Chemistry Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) media_common.quotation_subject Computational biology Computer Science Applications 03 medical and health sciences 030104 developmental biology Computational Theory and Mathematics Physical and Theoretical Chemistry Pharmacophore media_common |
| Zdroj: | Journal of Computational Biophysics and Chemistry. 20:377-390 |
| ISSN: | 2737-4173 2737-4165 |
| DOI: | 10.1142/s2737416521500198 |
| Popis: | Non-Structural Protein 16 (NSP-16) is one of the most suitable targets for discovery of drugs for corona viruses including SARS-CoV-2. In this study, drug discovery of SARS-CoV-2 nsp-16 has been accomplished by pharmacophore-based virtual screening among some analogs (FDA approved drugs) and marine natural plants (MNP). The comparison of the binding energies and the inhibition constants was determined using molecular docking method. Three compounds including two FDA approved (Ibrutinib, Idelalisib) and one MNP (Kumusine) were selected for further investigation using the molecular dynamics simulations. The results indicated that Ibrutinib and Idelalisib are oral medications while Kumusine, with proper hydrophilic and solubility properties, is an appropriate candidate for nsp-16 inhibitor and can be effective to control COVID-19 disease. |
| Databáze: | OpenAIRE |
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