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NIH fellow uses computation, experimentation to study diabetes, obesity
Date:8/2/2011

221.10.254.64

Stephanie Nicole "Nikki" Lewis, a graduate student in the interdisciplinary doctoral program in genetics, bioinformatics, and computational biology at Virginia Tech, has been awarded the prestigious Ruth L. Kirschstein National Research Service Award for Predoctoral Research through the National Institutes of Health for her study of a cellular signaling receptor that is associated with chronic inflammatory diseases such as diabetes, obesity, and inflammatory bowel disease.

Lewis is applying a combination of computational modeling and experimental methods to identify molecules that can activate peroxisome proliferator activated receptor gamma (PPAR ), which is a therapeutic target for suppressing inflammation. The search for drugs targeting the receptor is urgently needed since use of current drugs to treat type II diabetes by binding to PPAR , like the recently restricted Avandia (GlaxoSmithKline), results in adverse side effects. A goal of Lewis' research is to identify novel, orally active naturally occurring compounds with therapeutic potential due to their insulin-sensitizing and anti-inflammatory actions. The computational methods are used to quickly and inexpensively screen large numbers of compounds, from which a small number are selected for experimental validation in vitro and through pre-clinical animal studies.

This project entitled "Virtual Screening Development to Complement Experimental Screening for PPAR Modulators to Treat Type II Diabetes Mellitus" is primarily funded through the National Institute of Diabetes and Digestive and Kidney Diseases of NIH.

Lewis is working jointly with David Bevan, professor of biochemistry in the College of Agriculture and Life Sciences, and Josep Bassaganya-Riera, associate professor in the Nutritional Immunology and Molecular Medicine Laboratory at the Virginia Bioinformatics Institute (

Contact: Lori Greiner
lgreiner@vt.edu
540-231-5863
Virginia Tech
Source:Eurekalert  

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