Reversal of insulin resistance to combat type 2 diabetes mellitus by newer thiazolidinedione's in fructose induced insulin resistant rats

Abstract

In our pursuit of discovering new antidiabetic agents to manage type 2 diabetes mellitus (T2DM), our approach aimed to identify the bioactive feature/pharmacophore responsible for PPAR-γ expression, as it is accountable for the glucose homeostasis and lipid metabolism. This was achieved by pharmacophore model generation, screening of rationally designed newer thiazolidinedione's library, identifying synthesizing and characterizing the top ten molecules (5a-5j) for their (Invitro & invivo) antidiabetic activity. Preliminary screening of all the ligands by Invitro glucose uptake assay in L6 myotubes (skeletal muscle cell line of rats) revealed compound 5b and 5f stimulated the glucose uptake with 79.29 ± 1.02 % and 74.58 ± 1.02 % respectively compared to pioglitazone with 82.36 ± 0.98 %. This was validated by PPAR-γ TF expression assay, which highlighted a dose dependent increase in transactivation of PPAR-γ. These compounds 5b and 5f were evaluated in fructose induced insulin resistance rat model. Where the treatment with 5b and 5f markedly increased the exogenous clearance of glucose and exogenous insulin via OGTT and ITT respectively, also improved the glucose utilization by significantly increasing content of glycogen and uptake of glucose in rat hemidiaphragm and reversed insulin resistance. Likewise a significant decreased in the VLDL and triglyceride levels was seen in 5b and 5f treated groups compared to insulin resistant (IR) group. It improved glycogenesis by catabolism of glucose and maintained glycaemic control. Similarly it had marked action on enzymatic oxidative biomarkers. Compound 5b displayed better, improved T_1/2 (half-life) of 4.21 h and K_el (elimination constant) of 0.381 was noticed in comparison to compound 5f indicating the pharmacokinetic profile. Insilico studies like DFT calculations refined the geometry of 5b and 5f ligands, docking and molecular simulation provided the insights in binding affinity, dynamic behaviour and stability of ligands in PPAR-γ ligand binding domain. MM/GBSA provided the energetics of 5b and 5f in binding pocket. Finally network pharmacology identified ADIPOQ (adiponectin), NR1C3 (PPAR-γ), SLC2A4 (GLUT4), and LEP (leptin) proteins associate with compound 5b and 5f and enriched in Adipocytokine pathway, and PPAR-γ signaling pathway.

Keywords: MD simulations; Network pharmacology; Thiazolidinedione's; Type 2 diabetes mellitus; insulin resistance.