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In Silico Analysis of New Potent Anti-hyperglycemic Molecule for Diabetes Type 2 Management

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Abstract Diabetes mellitus Type 2 happens to be one of the most challenging health concerns in recent times and has spiked an alarming rise taking it into epidemic category. For… Click to show full abstract

Abstract Diabetes mellitus Type 2 happens to be one of the most challenging health concerns in recent times and has spiked an alarming rise taking it into epidemic category. For management of this epidemic, sulphonylureas have been cornerstone in its treatment. The inefficiency and impairment of insulin to function has been compensated by treatment with anti-hyperglycemic agents (glibenclamide). However, this has been linked with cases of hypoglycemia. In order to rectify this, the present study focuses on development of better drug analogue. Sulphonylurea receptor (SUR1) was modeled with reliable efficiency and confirmed for structural validation. The docking results were strongly supported by molecular dynamics data and molecular mechanics-generalized born surface area (MM-GBSA) calculations. Successful docking of predicted sulphonylurea receptor with designed analogue (C 24 H 26 ClN 3 O 4 S) was illustrated with stronger binding energy (− 8.3 kcal/mol) having seven hydrophobic contacts and two hydrogen bonds (Ile 103 and Leu 116 ) with the receptor protein. In case of SUR1-glibenclamide complex, a binding energy of − 7.1 kcal/mol was contributed from four hydrophobic contacts and three hydrogen bonds. The predicted molecule when scrutinized for pharmacophore and QSAR properties, like polar surface area, molar refractivity, oral bioavailability, solubility, transport across the gut, resistance to blood brain barrier and intestinal absorption, showed values mostly falling in prescribed range. It also highlighted that the inhibitor is non-toxic and non-carcinogenic property. Therefore, C 24 H 26 ClN 3 O 4 S can be used as a better and potent drug for treatment of diabetes Type 2 in comparison to glibenclamide. Graphic Abstract

Keywords: molecule; silico analysis; management; diabetes type; analysis new; anti hyperglycemic

Journal Title: International Journal of Peptide Research and Therapeutics
Year Published: 2019

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