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In-Silico Identification of Natural Compounds from Traditional Medicine as Potential Drug Leads against SARS-CoV-2 Through Virtual Screening.

ABSTRACT: The novel coronavirus strain SARS-CoV-2 is the virus responsible for the recent global health crisis, as it causes the coronavirus disease-19 (COVID-19) in humans. Due to its high rate of spreading and significant fatality rates, the situation has escalated to a pandemic, which is the cause of immense disruption in daily life. In this study, we have taken a docking-based virtual screening approach to select natural molecules (from plants) with possible therapeutic potential. For this purpose, AUTODOCK Vina-based determination of binding affinity values (blind and active-site oriented) was obtained to short-list molecules with possible inhibitory potential against the main Mpro in SARS-CoV-2 (PDB ID 6Y2F -the monomeric form). The 4 molecules selected were Chebuloside (-8.2; -8.2), Acetoside (-8.0; -8.0), Corilagin (-8.1; -7.7) and Arjunolic Acid (-8.0; -7.6) (blind and active-site oriented docking scores (Kcal/mol) in parenthesis, respectively). Further, a comparative search, with FDA-approved drugs, has shown that Ouabain was comparable to Chebuloside with a similarity score of 0.227. This in silico finding with respect to Ouabain is significant, since this polycyclic glycoside has been shown to treat COVID-19 positive patients with a cardiovascular disease. Hydrocortisone was similar to Arjunolic acid with a score of 0.539. Again, this likeness is worthy of mention, since hydrocortisone has been used earlier for the treatment of SARS-CoV1 and MERS. However, further experimentation and validation of the results, in suitable biological model systems, are necessary to gain more insight and relevance as well as provide corroborative evidence for our in-silico findings.

Supplementary information

The online version contains supplementary material available at 10.1007/s40011-021-01292-5.

SUBMITTER: Mithilesh S

PROVIDER: S-EPMC8741561 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It has six open reading frames (orf1ab, orf3a, orf6, orf7a, orf8, and orf10), a spike protein, a membrane protein, an envelope small membrane protein, and a nucleocapsid protein, out of which, orf1ab is the largest ORF coding different important non-structural proteins. In this study, an effort was made to evaluate the susceptibility of different animals against SARS-CoV-2 by analyzing the interactions of Spike and ACE2 proteins of the animals and propose a list of potential natural compounds binding to orf1ab of SARS-CoV-2. Here, we analyzed structural interactions between spike proteins of SARS-CoV-2 and the ACE2 receptor of 16 different hosts. A simulation for 50 ns was performed on these complexes. Based on post-simulation analysis, Chelonia mydas was found to have a more stable complex, while Bubalus bubalis, Aquila chrysaetos chrysaetos, Crocodylus porosus, and Loxodonta africana were found to have the least stable complexes with more fluctuations than all other organisms. Apart from that, we performed domain assignment of orf1ab of SARS-CoV-2 and identified 14 distinct domains. Out of these, Domain 3 (DNA/RNA polymerases) was selected as a target, as it showed no similarities with host proteomes and was validated in silico. Then, the top 10 molecules were selected from the virtual screening of ∼1.8 lakh molecules from the ZINC database, based on binding energy, and validated for ADME and toxicological properties. Three molecules were selected and analyzed further. The structural analysis showed that these molecules were residing within the pocket of the receptor. Finally, a simulation for 200 ns was performed on complexes with three selected molecules. Based on post-simulation analysis (RMSD, RMSF, Rg, SASA, and energies), the molecule ZINC000103666966 was found as the most suitable inhibitory compound against Domain 3. As this is an in silico prediction, further experimental studies could unravel the potential of the proposed molecule against SARS-CoV-2.

Project description:The widespread transmission of SARS-CoV-2 has sparked alarm worldwide. Attaining the best drugs to treat COVID-19 at the shortest possible time is one of the most critical issues in this urgent situation. Molecular docking investigation of the therapeutic potential of marketed drugs is a fast and cost-effective approach to provide a solution to this problem. The recent research efforts have led to the resolving of the 3CLpro structure as a key protease in the lifecycle of coronavirus, which could facilitate in silico evaluation of drug candidates. Herein, the similarity between the SARS-CoV-2-3CL main protease and the other SARS-CoV receptors was evaluated via multiple sequence alignment and phylogenetic tree. The reported structure of the 3CLpro was considered as a target to identify potential inhibitors for treating COVID-19 using molecular docking based virtual screening protocol. Accordingly, a database of 50 synthetic compounds with various pharmacological usage such as antiviral, anti-inflammatory, anti-human immunodeficiency viruses, antimalarial, antibacterial, anticancer, and antioxidant including approved drugs and those undergoing clinical trials, and 40 natural compounds particularly those employed in traditional Iranian medicine was constructed. The output of multiple sequence alignment analysis showed that SARS-CoV-2 main protease shares a similarity of 96% with SARS-CoV. Also, the docking results indicated that the licofelone acyl glucuronide as an anti-inflammatory drug and delta-bilirubin as an antioxidant and anti-inflammatory agent as well as kappa-carrageenan conformer, beta-D-galactopyranosyl and calycosin 7-O-glucoside as natural compounds with minimal side-effects, according to in vitro studies, are good candidates to block the enzymatic activity of SARS-CoV-2 3CLpro. Moreover, the compound 1 with the highest negative binding energy is a chemical compound that due to its favorable interactions with the 3CLpro can be identified as a representative potential drug candidate for COVID-19. Graphic abstract Supplementary Information The online version contains supplementary material available at 10.1007/s13738-021-02235-7.

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In-Silico Identification of Natural Compounds from Traditional Medicine as Potential Drug Leads against SARS-CoV-2 Through Virtual Screening.

Supplementary information

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