Virtual Screening of Some Typical Guanidine Based Small Molecules Against Selected Anti-Diabetic Drug Targets
Posted: 11 Feb 2020
Date Written: February 8, 2020
Abstract
Among many non-communicable, lifestyle modifying diseases, Metabolic syndrome (Met S) occupies a remarkable position. The condition is characterized by an array of complex co-occurring abnormalities including high blood pressure, central obesity, insulin resistance, hyperglycemia, and dyslipidemia in individuals, in turn, increasing the risk of type II diabetes and obesity. Apart from distinct biochemical pathways, molecules like AMP-activated Protein Kinase (AMPK) and Peroxisome Proliferator-Activated Receptor- γ (PPAR- γ) have drawn special attention in the mission of finding reliable targeting approaches. Non-pharmacological strategies, especially like physical exercise and diet regulation, are intensely implemented with an aim to achieve better prophylaxis and quality of life. Despite the availability of several potent therapeutic classes such as sulfonylureas, thiazolidinediones, biguanides, and incretin mimetics, there is still a deficiency for the safest candidates. Among the commonly used clinical oral anti-hyperglycemic agents against Met S, Metformin of biguanide class is considered as the safest first-line agent and gold standard in the therapy with negligible adverse effects. Hence taking the therapeutic benefits of metformin into account, we have synthesized a precise library of typical guanidine based small molecules with an idea to find potent and safest leads. Further using a combination of computational tools we have successfully screened the library against crystal structures of AMPK (PDB Code: 6B1U) and PPAR-γ (PDB Code: 5Y2T) with resolutions of 2.77 Å and 1.7 Å retrieved from Protein Data Bank (PDB) for understanding and assessing the residual level interactions and docking potential. Molecular dynamic simulations were carried out for 100 nanoseconds to understand Ligand- Receptor [LR] complex stability. We hope that our study could set a stage for the identification of reliable lead molecules with desirable features that are eligible for an effective clinical translation.
Keywords: AMP activated Protein Kinase, Metabolic Syndrome, Metformin, Peroxisome Proliferator Activated Receptor- γ
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