Molecular insights on analogs of HIV PR inhibitors toward HTLV‐1 PR through QM/MM interactions and molecular dynamics studies: comparative structure analysis of wild and mutant HTLV‐1 PR

Abstract

Retroviruses HTLV-1 and HIV-1 are the primary causative agents of fatal adult T-cell leukemia and acquired immune deficiency syndrome (AIDS) disease. Both retroviruses are similar in characteristics mechanism, and it encodes for protease that mainly involved in the viral replication process. On the basis of the therapeutic success of HIV-1 PR inhibitors, the protease of HTLV-1 is mainly considered as a potential target for chemotherapy. At the same time, structural similarities in both enzymes that originate HIV PR inhibitors can also be an HTLV-1 PR inhibitor. But the expectations failed because of rejection of HIV PR inhibitors from the HTLV-1 PR binding pocket. In this present study, the reason for the HIV PR inhibitor rejection from the HTLV-1 binding site was identified through sequence analysis and molecular dynamics simulation method. Functional analysis of M37A mutation in HTLV PR clearly shows that the MET37 specificity and screening of potential inhibitors targeting MET37 is performed by using approved 90% similar HIV PR inhibitor compounds. From this approach, we report few compounds with a tendency to accept/donate electron specifically to an important site residue MET37 in HTLV-1 PR binding pocket.

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“…Number of atoms, volume, and temperature (NVT) was performed for 1 ns, and the minimized structure was equilibrated with the timescale of 10 ns. The results of the RMSD, most fluctuated residues (RMSF) were performed using the Gromacs analysis (Selvaraj et al , ). Ti exhibits the protein movement in the simulation event, and the structure of protein remains stable with respect to RMSD variation.…”

A selectivity study of sodium-dependent glucose cotransporter 2/sodium-dependent glucose cotransporter 1 inhibitors by molecular modeling

“…Molecular dynamic simulation can be further used to optimize and understand the protein structures dynamically. It also helps us to understand the physiological effect and mechanism of action by investigating the interactions of proteins or protein‐ligand complex through time (Maharana et al, ; Panigrahi et al, ; Selvaraj et al, ). In addition, three‐dimensional quantitative structure–activity relationship (3D‐QSAR), which has been demonstrated its ability to summarize the structure–activity relationship and to guide the optimization of lead compounds, provides us a ligand‐based way to reveal the pharmacological action (Beger and Wilkes, ).…”

“…investigating the interactions of proteins or protein-ligand complex through time (Maharana et al, 2014;Panigrahi et al, 2014;Selvaraj et al, 2014). In addition, three-dimensional quantitative structure-activity relationship (3D-QSAR), which has been demonstrated its ability to summarize the structure-activity relationship and to guide the optimization of lead compounds, provides us a ligand-based way to reveal the pharmacological action (Beger and Wilkes, 2002).…”

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