Naslov
QSAR study on polyphenols and their derivates isolated from plant materials and food as inhibitors of a-glucosidase

Autori
Nikolić, Sonja ; Rastija, Vesna ; Bešlo, Drago ; Amić, Dragan

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
18th European Symposium on Quantitative Structure– Activity Relationships : Book of Abstract / - , 2010, 344-344

Skup
European Symposium on Quantitative Structure– Activity Relationships (18 ; 2010)

Mjesto i datum
Rodos, Grčka, 19.09.2010. - 24.09.2010

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
QSAR ; polifenoli ; inhibicija ; alfa-glukozidaza ; diabetes
(QSAR ; polyphenols ; inhibition ; alpha-glucosidase ; diabetes)

Sažetak
Diabetes mellitus is a chronic disease caused by inherited and/or acquired deficiency in insulin secretion and/or by decreased responsiveness of the organs to secreted insulin. Such a deficiency results in increased blood glucose levels that in turn can damage many of the body's systems, including blood vessels and nerves. Small intestinal a- glucosidase and pancreatic a-amylase are key enzymes of dietary carbohydrate digestion in humans. Inhibitors of these enzymes may be effective in retarding carbohydrate digestion and glucose absorption to suppress postprandial hyperglycaemia. Some polyphenols are well known inhibitors of intestinal a-glucosidase. The aim of this study was to derive a Quantitative Structure-Activity Relationship (QSAR) analysis for a-glucosidase inhibition potential of 48 polyphenols and their derivates. “Two- dimensional” (2D), “three-dimensional” (3D) molecular descriptors, quantum chemical descriptors, and physicochemical parameters, derived from optimised three-dimensional structure, have been calculated applying the PCLIENT (an on-line version of Dragon program) and HyperChem 8.0. Multiple regression analysis was performed using STATISTICA 7.0. Selection of predictor variables for multiple regression was performed by best-subset method. Dataset was divided into training set and test by manual selection and by cluster analysis, and then both method have been compared. The generated QSPR models were validated by leave- one-out cross-validation procedure using the CROMRsel (Rugjer Bošković Institute, Zagreb). Presented QSAR could be a useful for the design of new molecules more efficient in inhibition of enzymes responsible for the glucose production from carbohydrates. Also, this study will be helpful in illumination of antihyperglycemic effects of certain medicinal plants and food.

Izvorni jezik
Engleski

Znanstvena područja
Kemija

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