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bioRxiv · 10.1101/2023.06.10.542647

Computational prediction of gamma-oryzanol as potential agonist of human peroxisome proliferator-activated receptor gamma (ppar-γ)

Abstract

Diabetes mellitus is one of the complex metabolic disorders associated with individuals leading sedentary lifestyles. It leads to several complications rendering the normal function of vital organs like heart, liver, kidney, eye and brain. Scientists and doctors across the globe are involved in research for understanding the complex genetics of this disorder and formulating newer therapeutics accordingly. The finding of potential chemical entities and their underlying agonists or antagonist activities significantly controls the disorder but with some consequences. Thus there is demand for natural compounds and indigenous treatment methods for controlling the disorder with least or no adverse consequences. In the current work we present computational prediction of gamma-oryzanol as potential agonist of human peroxisome proliferator-activated receptor gamma (PPAR-{gamma}). A group of four gamma-oryzanol compound structures reported in PubChem database were downloaded and docked in the ligand binding site of five different human PPAR-{gamma} structures reported in PDB database. It was observed that most of the gamma-oryzanol compounds occupied themselves in the ligand binding P1, P2, P3, P4 sites with similar orientations as that of co-crystal agonists. Their binding conformations were assisted by some reasonable docking scores (-7 to -11 kcal/mol) and hydrogen bond interactions with some important conserved amino acid residues lining the ligand binding site. Additionally we have done a comparative molecular dynamics studies to reveal the flexibility of gamma-oryzanol in the ligand binding site in comparison to the co-crystal agonist and a scaffold analysis using the structure of six agonists and gamma-oryzanol for fetching potential scaffolds which may helpful in designing of new chemical entities.

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BibTeXRIS

Biswal, P. K., Behera, S., Mohapatra, S., Kar, D. M., Samanta, L., Behera, P. M., Kar, R. K.. 2023-06-11. Computational prediction of gamma-oryzanol as potential agonist of human peroxisome proliferator-activated receptor gamma (ppar-γ). https://doi.org/10.1101/2023.06.10.542647

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