Identification of medicinal plant-based phytochemicals as a potential inhibitor for SARS-CoV-2 main protease (Mpro) using molecular docking and deep learning methods.

Highly transmissive and rapidly evolving Coronavirus disease-2019 (COVID-19), a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), triggered a global pandemic, which is one of the most researched viruses in the academia. Effective drugs to treat people with COVID-19 have yet to be developed to reduce mortality and transmission. Studies on the SARS-CoV-2 virus identified that its main protease (Mpro) might be a potential therapeutic target for drug development, as this enzyme plays a key role in viral replication. In search of potential inhibitors of Mpro, we developed a phytochemical library consisting of 2431 phytochemicals from 104 Korean medicinal plants that exhibited medicinal and antioxidant properties. The library was screened by molecular docking, followed by revalidation by re-screening with a deep learning method. Recurrent Neural Networks (RNN) computing system was used to develop an inhibitory predictive model using SARS coronavirus Mpro dataset. It was deployed to screen the top 12 compounds based on their docked binding affinity that ranged from -8.0 to -8.9 kcal/mol. The top two lead compounds, Catechin gallate and Quercetin 3-O-malonylglucoside, were selected depending on inhibitory potency against Mpro. Interactions with the target protein active sites, including His41, Met49, Cys145, Met165, and Thr190 were also examined. Molecular dynamics simulation was performed to analyze root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RG), solvent accessible surface area (SASA), and number of hydrogen bonds. Results confirmed the inflexible nature of the docked complexes. Absorption, distribution, metabolism, excretion, and toxicity (ADMET), as well as bioactivity prediction confirmed the pharmaceutical activities of the lead compound. Findings of this research might help scientists to optimize compatible drugs for the treatment of COVID-19 patients.

Molecular docking and dynamics study of natural compound for potential inhibition of main protease of SARS-CoV-2.

Newly emerged SARS-CoV-2 made recent pandemic situations across the globe is accountable for countless unwanted death and insufferable panic associated with co-morbidities among mass people. The scarcity of appropriate medical treatment and no effective vaccine or medicine against SARS-CoV-2 has turned the situation worst. Therefore, in this study, we made a deep literature review to enlist plant-derived natural compounds and considered their binding mechanism with the main protease of SARS-CoV-2 through combinatorial bioinformatics approaches. Among all, a total of 14 compounds were filtered where Carinol, Albanin, Myricetin were had better binding profile than the rest of the compounds with having binding energy of -8.476, -8.036, -8.439 kcal/mol, respectively. Furthermore, MM-GBSA calculations were also considered in this selection process to support docking studies. Besides, 100 ns molecular dynamics simulation endorsed the rigid nature, less conformational variation and binding stiffness. As this study, represents a perfect model for SARS-CoV-2 main protease inhibition through bioinformatics study, these potential drug candidates may assist the researchers to find a superior and effective solution against COVID-19 after future experiments.Communicated by Ramaswamy Sarma.

Comparative molecular investigation of the potential inhibitors against SARS-CoV-2 main protease: a molecular docking study.

Recent outbreak of novel coronavirus and its rapid pandemic escalation in all over the world has drawn the attention to urgent need for effective drug development. However, due to prolonged vaccine and drug development procedure against a newly emerged devastating SARS-CoV-2 virus pathogen, repurposing of existing potential pertinent drug molecules would be preferable strategy to reduce mortality immediately and further development of new drugs to combat overall global Covid-19 crisis in all over the world. Herein, we have filtered 23 prospective drug candidates through literature review. Assessing evidences from molecular docking studies, it was clearly seen that, Epirubicin, Vapreotida, and Saquinavir exhibited better binding affinity against SARS-CoV-2 Main Protease than other drug molecules among the 23 potential inhibitors. However, 50 ns molecular dynamics simulation indicated the less mobile nature of the docked complex maintaining structural integrity. Our overall prediction findings indicate that Epirubicin, Vapreotida, and Saquinavir may inhibit COVID-19 by synergistic interactions in the active cavity and those results can pave the way in drug discovery although it has to be further validated by in-vitro and in-vivo investigations.Communicated by Ramaswamy H. Sarma.