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Title: Quantitative structure activity relationship study based molecular modeling of 4-aminoquinazoline derivatives for Aurora kinase inhibition
Authors: Ranjana
Sharma, Neetu
Dwivedi, Amrita
Singh, Ajeet
Srivastava, A. K.
Keywords: Aurora kinase;Multiple linear regression analysis;Cross validation
Issue Date: Nov-2018
Publisher: NISCAIR-CSIR, India
Abstract: QSAR studies have been performed on a series of 4-aminoquinazoline-urea derivatives to understand the structural features influencing the affinity towards the Aurora kinase enzyme inhibition. These compounds displayed anti proliferative activity against four cancer cell line A-549, NCI-H661, HT-29, LoVo. 2D descriptors such as physicochemical and topological properties of molecules have been calculated by using different softwares. The calculated results reveal that the descriptors based on partition coefficient (Log p), Ghose-Crippen octanol-water partition coefficient (A Log p), index of refraction (Ior) and molecular connectivity seem to be responsible factors for the inhibition of enzyme aurora kinase. Multiple linear regression analysis has also been performed on the given series using the physicochemical parameters. The regression models have been tested for reliability, statistically significant models have also been checked by cross validation using leave one out method. The statistical data indicates that some of the descriptors provide valuable information for the prediction of the activity of the given derivatives.
Page(s): 1421-1429
ISSN: 0975-0983(Online); 0376-4699(Print)
Appears in Collections:IJC-B Vol.57B(11) [November 2018]

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