Therapeutic Potential of Antiviral Peptides against the NS2B/NS3 Protease of Zika Virus.

The NS2B/NS3 protease is highly conserved among various proteases of the Zika virus, making it an important therapeutic target for developing broad-spectrum antiviral drugs. The NS2B/NS3 protease is a crucial enzyme in the replication cycle of Zika virus and plays a significant role in viral maturation and assembly. Inhibiting the activity of this protease can potentially prevent viral replication, making it an attractive target for developing therapies against Zika virus infection. This work screens 429 antiviral peptides in comparison with substrate peptide against the NS2B/NS3 of Zika virus using molecular docking and molecular dynamics (MD) simulation. Based on the docking screening, MD simulation conducted for the best four peptides including AVP0239, AVP0642, AVP0660, and AVP2044, could be effective against NS2B/NS3. These results were compared with the control substrate peptide. Further analysis indicates that AVP0642 and AVP2044 are the most promising candidates. The interaction analysis showed that the catalytic site residues including His51, Asp75, Ser135 and other non-catalytic residues such as Asp129, Asp83, and Asp79 contribute substantial interactions. Hydrogen bonds (41%) and hydrophobic interactions (33%) are observed as the prominent non-covalent interaction prompting the peptide-protein complex formation. Furthermore, the structure-activity relationship (SAR) illustrates that positively charged (Lys, Arg) residues in the peptides dominate the interactions. This study provides the basis for developing novel peptide-based protease inhibitors for Zika virus.

Phytochemicals-based targeting RdRp and main protease of SARS-CoV-2 using docking and steered molecular dynamic simulation: A promising therapeutic approach for Tackling COVID-19.

The ongoing COVID-19 pandemic has affected millions of people worldwide and caused substantial socio-economic losses. Few successful vaccine candidates have been approved against SARS-CoV-2; however, their therapeutic efficacy against the mutated strains of the virus remains questionable. Furthermore, the limited supply of vaccines and promising antiviral drugs have created havoc in the present scenario. Plant-based phytochemicals (bioactive molecules) are promising because of their low side effects and high therapeutic value. In this study, we aimed to screen for suitable phytochemicals with higher therapeutic value using the two most crucial proteins of SARS-CoV-2, the RNA-dependent RNA polymerase (RdRp) and main protease (Mpro). We used computational tools such as molecular docking and steered molecular dynamics simulations to gain insights into the different types of interactions and estimated the relative binding forces between the phytochemicals and their respective targets. To the best of our knowledge, this is the first report that not only involves a search for a therapeutic bioactive molecule but also sheds light on the mechanisms underlying target inhibition in terms of calculations of force and work needed to extractthe ligand from the pocket of its target. The complexes showing higher binding forces were subjected to 200 ns molecular dynamic simulations to check the stability of the ligand inside the binding pocket. Our results suggested that isoskimmiwallin and terflavin A are potential inhibitors of RdRp, whereas isoquercitrin and isoorientin are the lead molecules against Mpro. Collectively, our findings could potentially aid in the development of novel therapeutics against COVID-19.

The investigation of nonsynonymous SNPs of human SLC6A4 gene associated with depression: An in silico approach.

Genetic polymorphism of the SLC6A4 gene is associated with several behavioral disorders, including depression. Since studying the total nonsynonymous single nucleotide polymorphisms (nsSNPs) of the SLC6A4 gene at the population level is a difficult task, we aim to utilize in silico approach to detect the most deleterious nsSNPs of the SLC6A4 gene. In our study, 7 computational tools were used in the initial stage, including SIFT, Polyphen-2, PROVEAN, SNAP2, PhD-SNP, PANTHER, and SNPs&GO to find out the most damaging nsSNPs. In the second phase, we performed structural, functional, and stability analysis of SLC6A4 protein by popular computation tools, including I-Mutant 2.0 and MutPred2. Also, the ConSurf server was utilized to find the conserved region of the SLC6A4 protein to determine the relationship between these conserved regions with high-risk nsSNPs. Based on these analyses, 5 high-risk mutations of the SLC6A4 protein were selected. Then, we carried out comparative modeling by using the Robetta server and aligned the mutant protein model with the native protein structure. Later, we performed the post-translational modification and functional domain analysis of the SLC6A4 protein. This study concludes that Arginine → Tryptophan at position 79 and Arginine → Cysteine at position 104 are the two significant mutations in SLC6A4 protein which might play an essential role in causing diseases. Future studies should take these high-risk nsSNPs (rs1221448303, rs200953188) into consideration while exploring diseases related to the SLC6A4 gene. Besides, our research is the first-ever comprehensive in silico investigation of the SLC6A4 gene. Thus, the findings of this study could be beneficial for developing precision medicines against diseases caused by SLC6A4 malfunction. Furthermore, extensive wet-lab research and experiments on various model organisms might be helpful to investigate the precise role of these damaging nsSNPs of the SLC6A4 gene.