A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

Abstract

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization declared it a global pandemic on 11 March 2020. Many endeavors have been made to find appropriate medications to restrain the SARS-CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates. The crystallized SARS-CoV-2 main protease structure was collected from the Research Collaboratory for Structural Bioinformatics Protein Data Bank database (Protein Data Bank ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Among 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. Molecular dynamics simulation disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but further in vivo trials will require for experimental validation.

Development of Computational In Silico Model for Nano Lipid Carrier Formulation of Curcumin

“…These findings were not reported with the other compared 10 lipids. Moreover, the presence of a pi–alkyl bond in the interaction between curcumin and GMS provides the stability for the system, and the presence of the pi–sigma bond provides an extra stability to the interaction between the molecules [ 39 ]. On the other hand, oleic acid was found to be the best liquid lipid candidate to be mixed with GMS for the NLCs formulation since the high compatibility between these two lipids was found experimentally and due to the obtained docking results, which showed that oleic acid was superior compared to other liquid lipids in demonstrating a lower binding energy of −6.5 kcal/mol.…”

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

“…27,28 This research identified a total of 114 essential oil compounds, which were then investigated to see whether they had antiviral properties against SARS-CoV-2 (See extended data file for plant information of all the compounds including their binding affinity scores). 29…”