In silico identification of novel SARS-CoV-2 main protease and non-structural protein 13 (nsp13) inhibitors through consensus docking and free binding energy calculations.

BACKGROUND: A new strain of a novel disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been recently declared a pandemic by the World Health Organization (WHO). The virus is resulting in significant mortality and morbidity across the planet therefore novel treatments are urgently required. Recently deposited crystallographic structures of SARS-CoV-2 proteins have ignited the interest in virtual screenings of large databases. OBJECTIVE: In the current study, we evaluated the inhibitory capacity of the IMPPAT phytochemical database (8500 compounds) and the SuperDRUG2 dataset (4000 compounds) in SARS-CoV-2 main protease and helicase Nsp13 through consensus-based docking simulations. METHODS: Glide and GOLD 5.3 were implemented in the in silico process. Further MM/GBSA calculations of the top 10 inhibitors in each protein were carried out to investigate the binding free energy of the complexes. An analysis of the major ligand-protein interactions was also conducted. RESULTS: After the docking simulations we acquired 10 prominent phytochemicals, and 10 FDA-approved drugs capable of inhibiting Nsp5 and Nsp13. Delphinidin 3,5,3'-triglucoside and hirsutidin 3-O-(6-O-p-coumaroyl)glucoside demonstrated the most favorable binding free energies against Nsp5 and Nsp13, respectively. CONCLUSION: In conclusion, the analysis of the results identified that the phytochemicals demonstrated enhanced binding capacities, compared to the FDA-approved database.

Molecular docking-based virtual screening: Challenges in hits identification for Anti-SARS-Cov-2 activity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) requires finding new drugs or repurposing drugs for clinical use. Molecular docking belongs to structure-based drug design providing a fast method for identifying the hit com-pounds with antiviral activity against SARS-Cov-2. However, the weakness of the docking method is compounded by the limited crystallographic information and comparison drugs due to the novelty of this virus can present challenges in identifying hits of anti-SARS-Cov-2. In the current review, we highlighted several aspects, especially those related to the target structure, docking validation, and virtual hit selection, that need to be considered to obtain reliable docking results. Here, we discussed several cases pertaining to the issue highlighted and approaches that could be used to solve them.

Consensus docking and MM-PBSA computations identify putative furin protease inhibitors for developing potential therapeutics against COVID-19.

The coronavirus disease 2019 (COVID-19) is a pandemic that has severely posed substantial health challenges and claimed millions of lives. Though vaccines have been produced to stem the spread of this disease, the death rate remains high since drugs used for treatment have therapeutic challenges. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease, has a slew of potential therapeutic targets. Among them is the furin protease, which has a cleavage site on the virus's spike protein. The cleavage site facilitates the entry of the virus into human cells via cell-cell fusion. This critical involvement of furin in the disease pathogenicity has made it a viable therapeutic strategy against the virus. This study employs the consensus docking approach using HYBRID and AutoDock Vina to virtually screen a pre-filtered library of 3942 natural product compounds of African origin against the human furin protease (PDB: 4RYD). Twenty of these compounds were selected as hits after meeting molecular docking cut-off of - 7 kcal.mol-1, pose alignment inspection, and having favorable furin-ligand interactions. An area under the curve (AUC) value of 0.72 was computed from the receiver operator characteristic (ROC) curve, and Boltzmann-enhanced discrimination of the ROC curve (BEDROC) value of 0.65 showed that AutoDock Vina was a reasonable tool for selecting actives for this target. Seven of these hits were proposed as potential leads having had bonding interactions with catalytic triad residues Ser368, His194, and Asp153, and other essential residues in the active site with plausible binding free energies between - 189 and - 95 kJ/mol from the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations as well as favorable ADME/Tox properties. The molecules were also predicted as antiviral, anti-inflammatory, membrane permeability inhibitors, RNA synthesis inhibitors, cytoprotective, and hepatoprotective with probable activity (Pa) above 0.5 and probable inactivity values below 0.1. Some of them also have anti-influenza activity. Influenza virus has many similarities with SARS-CoV-2 in their mode of entry into human cells as both are facilitated by the furin protease. Pinobanksin 3-(E)-caffeate, one of the potential leads is a propolis compound. Propolis compounds have shown inhibitory effects against ACE2, TMPRSS2, and PAK1 signaling pathways of SARS-CoV-2 in previous studies. Likewise, quercitrin is structurally similar to isoquercetin, which is currently in clinical trials as possible medication for COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02056-1.