Molecular Docking and Molecular Dynamics Simulations Discover Curcumin Analogue as a Plausible Dual Inhibitor for SARS-CoV-2.

Recently, the world has been witnessing a global pandemic with no effective therapeutics yet, while cancer continues to be a major disease claiming many lives. The natural compound curcumin is bestowed with multiple medicinal applications in addition to demonstrating antiviral and anticancer activities. In order to elucidate the impact of curcumin on COVID-19 and cancer, the current investigation has adapted several computational techniques to unfold its possible inhibitory activity. Accordingly, curcumin and similar compounds and analogues were retrieved and assessed for their binding affinities at the binding pocket of SARS-CoV-2 main protease and DDX3. The best binding pose was escalated to molecular dynamics simulation (MDS) studies to assess the time dependent stability. Our findings have rendered one compound that has demonstrated good molecular dock score complemented by key residue interactions and have shown stable MDS results inferred by root mean square deviation (RMSD), radius of gyration (Rg), binding mode, hydrogen bond interactions, and interaction energy. Essential dynamics results have shown that the systemadapts minimum energy conformation to attain a stable state. The discovered compound (curA) could act as plausible inhibitor against SARS-CoV-2 and DDX3. Furthermore, curA could serve as a chemical scaffold for designing and developing new compounds.

Unravelling the therapeutic potential of marine drugs as SARS-CoV-2 inhibitors: An insight from essential dynamics and free energy landscape.

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic. The virus that causes the disease, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), predominantly infects the respiratory tract, which may lead to pneumonia and death in severe cases. Many marine compounds have been found to have immense medicinal value and have gained approval from the Food and Drug Administration (FDA), and some are being tested in clinical trials. In the current investigation, we redirected a number of marine compounds toward SARS-CoV-2 by targeting the main protease (Mpro, PDB ID: 6Y2F), subjecting them to several advanced computational techniques using co-crystallised ligand as the reference compound. The results of the binding affinity studies showed that two compounds, eribulin mesylate (eri) and soblidotin (sob), displayed higher docking scores than did the reference compound. When these compounds were assessed using molecular dynamics simulation, it was evident that they demonstrated stable binding at the binding pocket of the target protein. The systems demonstrated stable root mean square deviation and radius of gyration values, while occupying the binding pocket during the simulation run. Furthermore, the essential dynamics and free energy landscape exploration revealed that the protein had navigated through a minimal energy basin and demonstrated favourable conformation while binding to the proposed inhibitors. Collectively, our findings suggest that two marine compounds, namely eri and sob, show potential as SARS-CoV-2 main protease inhibitors.

Pharmacophore Modelling-Based Drug Repurposing Approaches for SARS-CoV-2 Therapeutics.

The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a devastating effect globally with no effective treatment. The swift strategy to find effective treatment against coronavirus disease 2019 (COVID-19) is to repurpose the approved drugs. In this pursuit, an exhaustive computational method has been used on the DrugBank compounds targeting nsp16/nsp10 complex (PDB code: 6W4H). A structure-based pharmacophore model was generated, and the selected model was escalated to screen DrugBank database, resulting in three compounds. These compounds were subjected to molecular docking studies at the protein-binding pocket employing the CDOCKER module available with the Discovery Studio v18. In order to discover potential candidate compounds, the co-crystallized compound S-adenosyl methionine (SAM) was used as the reference compound. Additionally, the compounds remdesivir and hydroxycholoroquine were employed for comparative docking. The results have shown that the three compounds have demonstrated a higher dock score than the reference compounds and were upgraded to molecular dynamics simulation (MDS) studies. The MDS results demonstrated that the three compounds, framycetin, kanamycin, and tobramycin, are promising candidate compounds. They have represented a stable binding mode at the targets binding pocket with an average protein backbone root mean square deviation below 0.3 nm. Additionally, they have prompted the hydrogen bonds during the entire simulations, inferring that the compounds have occupied the active site firmly. Taken together, our findings propose framycetin, kanamycin, and tobramycin as potent putative inhibitors for COVID-19 therapeutics.

Computational Approaches to Discover Novel Natural Compounds for SARS-CoV-2 Therapeutics.

Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID-19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug-like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS-CoV-2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug-like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N-71493 and STOCK1N-45683 as SARS-CoV-2 treatment regime.

Old Drugs for New Purpose—Fast Pace Therapeutic Identification for SARS-CoV-2 Infections by Pharmacophore Guided Drug Repositioning Approach

The recent outbreak, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a devastating effect globally with no effective treatment. A swift strategy to find effective therapeutics against coronavirus disease 2019 (COVID-19) is to repurpose the approved drugs with a blend of computational techniques. In this pursuit an exhaustive computational methods were applied on DrugBank compounds targeting SARS-CoV-2 main protease (Mpro). A structure-based pharmacophore model was generated considering the interactions between the target and the inhibitor N3. The validated model was subjected to screen DrugBank database yielding 35 compounds. Further, evaluating the binding affinity studies with reference drug Remdesivir has resulted six candidates with higher molecular dock scores than the reference compound. These compounds have demonstrated firm molecular dynamics simulation (MDS) results forming stable protein-drug complex demonstrating pharmacophore features. Taken together, our findings propose Viomycin, Enviomycin, Framycetin, Amikacin, Iopromide, and Paromomycin as potent putative inhibitors for COVID-19 therapeutics.