Bioinformatic Analysis of Selected Natural Compounds for Antidiabetic Potential

Diabetes is a very serious, chronic, and complex metabolic disorder that is based on multiples aetiologies with both acute and chronic. There are two types of diabetes, one types 1 DM and the other is type two DM. Both T1DM and T2DM are the most serious type of chronic conditions that are typical cannot be cured. Insulin stimulates adipocytes, myocytes, and hepatocytes, which uptake glucose from the circulatory system. Antidiabetic drugs show useful effects through decreasing glucose absorption in the intestines increasing insulin levels in the body or increasing the bodys sensitivity or decreasing its resistance to insulin. Most of these plants contain bioactive compounds. Such compounds are alkaloids, flavonoids, glycosides, terpenoids, carotenoids, etc., which are frequently implicated as having an Antidiabetic effect. The different types of phytochemicals include flavonoids, saponins, phenolic acids, alkaloids, tannin, stillness, and polysaccharides. They have two types of drug design structure based drug desingand ligand based drug design. The protein is a structure based ligand, which is based on drug design for the role of significantly quantitative structure activity relationship QSAR and pharmacophore analysis. Ligand based pharmacophore model generation depends on the information regarding the known biological activity without any structural information depends on the macromolecular target. The ligand based VS is more expensive due to structure based methods. Based on the opposing chemical functionalities, and the geometric arrangement about each other, where the interactions are observed there is the pharmacophore features are placed on the ligand side. Niketa Singh | KM. Radha | Khushboo Rana | Fanish Kumar Pandey | Noopur Khare | Abhimanyu Kumar Jha "Bioinformatic Analysis of Selected Natural Compounds for Antidiabetic Potential" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42419.pdf Paper URL: https://www.ijtsrd.combiological-science/biotechnology/42419/bioinformatic-analysis-of-selected-natural-compounds-for-antidiabetic-potential/niketa-singh