Anti-HIV and anti-HCV small molecule protease inhibitors in-silico repurposing against SARS-CoV-2 Mpro for the treatment of COVID-19

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host-virus protein-protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection. Objective: This study aims to identify therapeutic target proteins in humans that could act as virus-host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors. Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 ("hCoV-2"), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient's mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein. Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein. Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention.

Structure-based molecular docking and molecular dynamics simulations study for the identification of dipeptidyl peptidase 4 inhibitors in type 2 diabetes

Inhibition of dipeptidyl peptidase-4 (DPP4) activity has emerged as a promising therapeutic approach for the treatment of type 2 diabetes mellitus (T2DM). Bioinformatics-driven approaches have emerged as crucial tools in drug discovery. Molecular docking and molecular dynamics (MD) simulations are effective tools in drug discovery, as they reduce the time and cost associated with experimental screening. In this study, we employed structure-assisted in-silico methods, including molecular docking and MD simulations, to identify SRT2183, a small molecule that may potentially inhibit the activity of DPP4 enzyme. The interaction between the small molecule "SRT2183" and DPP4 exhibited a binding affinity of -9.9 Kcal/Mol, leading to the formation of hydrogen bonds with the amino acid residues MET348, SER376, and THR351 of DPP4. The MD simulations over a period of 100 ns indicated stable protein-ligand interactions, with no significant conformational rearrangements observed within the simulated timeframe. In conclusion, our results suggest that the small molecule SRT2183 may have the potential to inhibit the DPP4 enzyme and pave the way for the therapeutics of T2DM.Communicated by Ramaswamy H. Sarma.

Inhibitory effect of natural compounds on Dihydropteroate synthase of Mycobacterium leprae: Molecular dynamic study

Leprosy is a chronic infectious disease caused by a bacillus, Mycobacterium leprae. According to official data from 139 countries in the 6 WHO Regions, there were 127558 new leprosy cases worldwide in 2020. Leprosy mainly affects the skin, the peripheral nerves, mucosa of the upper respiratory tract, and the eyes. If this disease is left untreated, can harm the skin, nerves, limbs, eyes, and skin permanently. The disease is curable with multidrug therapy. Over a period of time Mycobacterium leprae has become resistant to these drugs. Therefore, new therapeutic molecules are warranted. This study was aimed to carry out the in-silico analysis to determine the inhibitory effect of natural compounds on Dihydropteroate synthase (DHPS) of Mycobacterium leprae. The DHPS is a key enzyme in the folate biosynthesis pathway in M. leprae and acts as a competitive inhibitor of PABA. The 3D structure of DHPS protein was modeled using homology modeling and was validated. Molecular docking and simulation along with other in-silico methods were employed to determine the inhibitory effect of ligand molecules towards DHPS target protein. Results revealed ZINC03830554 molecule as a potential inhibitor of DHPS. Binding experiments and bioassays utilizing this strong inhibitor molecule against purified DHPS protein are necessary to validate these early findings.Communicated by Ramaswamy H. Sarma.