Antiviral phytochemicals as potent inhibitors against NS3 protease of dengue virus.

Dengue, a mosquito-borne disease, has appeared as a major infectious disease globally. The virus requires its proteins to replicate and reproduce in the host cell. The NS3 protease converts the polyprotein to functional proteins with the help of the NS2B cofactor. Thus, NS3 protease is a promising target to develop antiviral inhibitors against the dengue virus. A systematic screening including ADMET properties, molecular docking, molecular dynamics (MD) simulation, binding free energy calculation, and QSAR studies is carried out to predict potent inhibitors against the NS3 protease. From the screening of 40 antiviral phytochemicals, ADMET properties analysis was used to screen out ligands that violate ADME rules and have probable toxicity. Cyanidin 3-Glucoside, Dithymoquinone, and Glabridin were predicted to be potent inhibitors against the NS3 protease according to their binding affinity. These ligands showed several noncovalent interactions, including hydrogen bond, hydrophobic interaction, electrostatic interaction, pi-sulfur interactions. The ligand-protein complexes were further scrutinized using 250 ns molecular dynamics simulation. The MM-PBSA binding free energy calculation was conducted to investigate their binding stability in dynamic conditions. The calculated pIC50(mM) value was predicted using the QSAR model with 89.91% goodness of fit. The predicted biologocal activity value for the ligands indicates they might have good potency.

Virtual screening, molecular dynamics and structure-activity relationship studies to identify potent approved drugs for Covid-19 treatment.

Computer-aided drug screening by molecular docking, molecular dynamics (MD) and structural-activity relationship (SAR) can offer an efficient approach to identify promising drug repurposing candidates for COVID-19 treatment. In this study, computational screening is performed by molecular docking of 1615 Food and Drug Administration (FDA) approved drugs against the main protease (Mpro) of SARS-CoV-2. Several promising approved drugs, including Simeprevir, Ergotamine, Bromocriptine and Tadalafil, stand out as the best candidates based on their binding energy, fitting score and noncovalent interactions at the binding sites of the receptor. All selected drugs interact with the key active site residues, including His41 and Cys145. Various noncovalent interactions including hydrogen bonding, hydrophobic interactions, pi-sulfur and pi-pi interactions appear to be dominant in drug-Mpro complexes. MD simulations are applied for the most promising drugs. Structural stability and compactness are observed for the drug-Mpro complexes. The protein shows low flexibility in both apo and holo form during MD simulations. The MM/PBSA binding free energies are also measured for the selected drugs. For pattern recognition, structural similarity and binding energy prediction, multiple linear regression (MLR) models are used for the quantitative structural-activity relationship. The binding energy predicted by MLR model shows an 82% accuracy with the binding energy determined by molecular docking. Our details results can facilitate rational drug design targeting the SARS-CoV-2 main protease.Communicated by Ramaswamy H. Sarma.