A Combined Approach of Pharmacophore Modeling, QSAR Study, Molecular Docking and In silico ADME/Tox Prediction of 4-Arylthio & 4-Aryloxy-3- Iodopyridine-2(1H)-one Analogs to Identify Potential Reverse Transcriptase Inhibitor: Anti-HIV Agents.

BACKGROUND: Reverse transcriptase is an important therapeutic target to treat AIDS caused by the Human Immunodeficiency Virus (HIV). Despite many effective anti-HIV drugs, reverse transcriptase (RT) inhibitors remain the cornerstone of the drug regimen to treat AIDS. In the present work, we have expedited the use of different computational modules and presented an easy, costeffective, and high throughput screening method to identify potential reverse transcriptase inhibitors. METHODS: A congeneric series of 4-Arylthio & 4-Aryloxy-3- Iodopyridine-2(1H)-one analogs having anti-HIV activity were subjected to structure-based 2D, 3D QSAR, Pharmacophore Modeling, and Molecular Docking to elucidate the structural properties required for the design of potent HIV-RT inhibitors. Prediction of preliminary Pharmacokinetic and the Drug Likeliness profile was performed for these compounds by in silico ADME study. RESULTS: The 2D and 3D- QSAR models were developed by correlating two and three-dimensional descriptors with activity (pIC50) by sphere exclusion method and k-nearest neighbor molecular field analysis approach, respectively. The significant 2D- QSAR model developed by Partial Least Square is associated with the Sphere Exclusion method (PLS-SE), having r2 and q2 values 0.9509 and 0.8038, respectively. The 3D-QSAR model by Step Wise variable selection method (SW-kNN MFA) is more significant, which has a cross-validated squared correlation coefficient q2= 0.8509 and a non-crossvalidated correlation coefficient pred_r2= 0.8102. The pharmacophore hypothesis was developed, which comprised 5 features includes 3 aliphatic regions (Ala), 1 H-bond donor (HDr) and 1 H-bond acceptor (HAc). Docking studies of the selected inhibitors with the active site of reverse transcriptase enzyme showed hydrogen bond and π - π interaction with LYS-101, LYS-103, TYR- 181, TYR-188 and TRP-229 residues present at the active site. All the candidates with good bioavailability and ADMET drug likeliness properties. CONCLUSION: The results of the present work provide more useful information and important structural insights for the discovery, design of novel and potent reverse transcriptase inhibitors with high therapeutic windows in the future.

The interaction of the bioflavonoids with five SARS-CoV-2 proteins targets: An in silico study.

Flavonoids have been shown to have antioxidant, anti-inflammatory, anti-proliferative, antibacterial and antiviral efficacy. Therefore, in this study, we choose 85 flavonoid compounds and screened them to determine their in-silico interaction with protein targets crucial for SARS-CoV-2 infection. The five important targets chosen were the main protease (Mpro), Spike receptor binding domain (Spike-RBD), RNA - dependent RNA polymerase (RdRp or Nsp12), non-structural protein 15 (Nsp15) of SARS-CoV-2 and the host angiotensin converting enzyme-2 (ACE-2) spike-RBD binding domain. The compounds were initially docked at the selected sites and further evaluated for binding free energy, using the molecular mechanics/generalized Born surface area (MMGBSA) method. The three compounds with the best binding scores were subjected to molecular dynamics (MD) simulations. The compound, tribuloside, had a high average binding free energy of -86.99 and -88.98 kcal/mol for Mpro and Nsp12, respectively. The compound, legalon, had an average binding free energy of -59.02 kcal/mol at the ACE2 spike-RBD binding site. The compound, isosilybin, had an average free binding energy of -63.06 kcal/mol for the Spike-RBD protein. Overall, our results suggest that tribuloside, legalon and isosilybin should be evaluated in future studies to determine their efficacy to inhibit SARS-CoV-2 infectivity.