TITLE

Molecular Descriptors Analysis of Oxyiminoalkanoic Acid Analogs towards PPARγ Agonist Activity

AUTHOR(S)
Pandey, Jyoti; Gupta, Arun Kumar
PUB. DATE
March 2016
SOURCE
International Journal of Pharmacy & Life Sciences;Mar2016, Vol. 7 Issue 3, p4942
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Diabetes mellitus have reached global pandemic proportions with India being designated 'diabetes capital' of the world. Diabetes is a multi-system disorder comprising metabolic and vascular abnormalities resulting from insulin deficiency, with or without insulin resistance. There are a number of groups that endeavor to produce new antidiabetic agents. In view of above and as a part of our effort to develop newer anti-diabetic agents, molecular modeling analysis was performed to developed QSAR models that show substantial predictive promise for oxyiminoalkanoic acid analogs. The QSAR model explains 81.9 percent variance in activity with standard error of estimation (0.405). Model showed statistical significant internal predictivity (Q2=0.709) and external predictivity (r2pred=0.603) values. The detailed structural investigation revealed that the PPARγ agonist activity is predominantly explained by the 2D-autocorrelation descriptors (MATS8e & MATS8v) and eigenvalue-based descriptors (BEHp5 & VRA1). The structural insights gleaned from the study are helpful in design of agonist with enhanced potency.
ACCESSION #
114795792

 

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