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http://hdl.handle.net/2080/5579| Title: | Kinetic modelling of starch hydrolysis under polyphenol inhibition: an in silico study in pre-diabetic and diabetic patients |
| Authors: | Nath, Ankita Avvari, Ravi Kant |
| Keywords: | Polyphenols Starch digestion Enzyme inhibition Postprandial glucose Diabetes management |
| Issue Date: | Dec-2025 |
| Publisher: | Springer |
| Citation: | International Conference on Advances in Biotechnology, Bioprocessing, and Structural Biology (ICABSB), Roorkee, India, 11-14 December 2025 |
| Abstract: | Polyphenols are naturally occurring plant-derived secondary metabolites that influence postprandial glucose homeostasis by modulating enzymatic starch breakdown. Polyphenols, particularly flavonoids and phenolic acids, are reported to enhance insulin action and lower postprandial glucose levels by modulating oxidative stress, inflammation, and enzymatic pathways of starch hydrolysis. The present study investigates the inhibitory effect of selected dietary polyphenols on starch hydrolysis using the developed mathematical model of in silico gastrointestinal digestion, in pre-diabetic and diabetic patients. The mathematical simulations were employed to model starch digestion and glucose formation under in vivo conditions using MATLAB. Polyphenols, such as tannic acid and gallic acid, exhibited inhibitory effects on α-amylase and α-glucosidase, thereby reducing the kinetics of starch breakdown and the postprandial glycemic rise. Kinetic modelling based on rate-law equations and Michaelis–Menten dynamics predicted enzyme inhibition and metabolite formation, with simulation results confirming that polyphenols act as competitive inhibitors at higher concentrations. Additionally, the polyphenols were found to influence glucose transporter activities across intestinal membranes, further slowing glucose absorption and attenuating hyperglycemic spikes. These findings highlight the potential of polyphenols as natural anti-diabetic nutraceuticals for starch digestion, with combined experimental and computational approaches offering therapeutic insights for diabetes management. |
| Description: | Copyright belongs to proceedings publisher. |
| URI: | http://hdl.handle.net/2080/5579 |
| Appears in Collections: | Conference Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2025_ICABSB_ANath_Kinetic Modeling.pdf | PPT Presentation | 1.45 MB | Adobe PDF | View/Open Request a copy |
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