Phytochemical Compound Screening to Identify Novel Small Molecules against Dengue Virus: A Docking and Dynamics Study.

The spread of the Dengue virus over the world, as well as multiple outbreaks of different serotypes, has resulted in a large number of deaths and a medical emergency, as no viable medications to treat Dengue virus patients have yet been found. In this paper, we provide an in silico virtual screening and molecular dynamics-based analysis to uncover efficient Dengue infection inhibitors. Based on a Google search and literature mining, a large phytochemical library was generated and employed as ligand molecules. In this investigation, the protein target NS2B/NS3 from Dengue was employed, and around 27 compounds were evaluated in a docking study. Phellodendroside (-63 kcal/mole), quercimeritrin (-59.5 kcal/mole), and quercetin-7-O-rutinoside (-54.1 kcal/mole) were chosen based on their binding free energy in MM-GBSA. The tested compounds generated numerous interactions at Lys74, Asn152, and Gln167 residues in the active regions of NS2B/NS3, which is needed for the protein's inhibition. As a result, the stable mode of docked complexes is defined by various descriptors from molecular dynamics simulations, such as RMSD, SASA, Rg, RMSF, and hydrogen bond. The pharmacological properties of the compounds were also investigated, and no toxicity was found in computational ADMET properties calculations. As a result, this computational analysis may aid fellow researchers in developing innovative Dengue virus inhibitors.

Computational screening of 645 antiviral peptides against the receptor-binding domain of the spike protein in SARS-CoV-2.

The receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein plays a vital role in binding and internalization through the alpha-helix (AH) of human angiotensin-converting enzyme 2 (hACE2). Thus, it is a potential target for designing and developing antiviral agents. Inhibition of RBD activity of the S protein may be achieved by blocking RBD interaction with hACE2. In this context, inhibitors with large contact surface area are preferable as they can form a potentially stable complex with RBD of S protein and would not allow RBD to come in contact with hACE2. Peptides represent excellent features as potential anti-RBD agents due to better efficacy, safety, and tolerability in humans compared to that of small molecules. The present study has selected 645 antiviral peptides known to inhibit various viruses and computationally screened them against the RBD of SARS-CoV-2 S protein. In primary screening, 27 out of 645 peptides exhibited higher affinity for the RBD of S protein compared to that of AH of the hACE2 receptor. Subsequently, AVP1795 appeared as the most promising candidate that could inhibit hACE2 recognition by SARS-CoV 2 as was predicted by the molecular dynamics simulation. The critical residues in RBD found for protein-peptide interactions are TYR 489, GLY 485, TYR 505, and GLU 484. Peptide-protein interactions were substantially influenced by hydrogen bonding and hydrophobic interactions. This comprehensive computational screening may provide a guideline to design the most effective peptides targeting the spike protein, which could be studied further in vitro and in vivo for assessing their anti-SARS CoV-2 activity.