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Abstract

2D QSAR MODEL BASED ON PYRIDINECARBOXAMIDE AND BENZAMIDE DERIVATIVES AS GLUCOKINASE ACTIVATOR

Dhanraj Patidar*, Ashish Jain and Pradeep Kumar Mohanty

ABSTRACT

Background: 58 compounds were chosen from the published article having two basic moieties i.e. pyridinecarboxamide and benzamide derivatives. Method: Work station was a computer with operating system and mass storage facility integrated with graphical display. All the computational studies were performed on a Microsoft Window XP running on Pentium-D- processor. QSAR study has been done by using the Vlife MDS software provided by Vlife Sciences Technologies Pvt. Ltd. Pune, India. Results: From this plot it has been seen that model is able to predict the activity of the training set quite well (all points are close to regression line) as well as external test set (all points of test set are close to regression line and well covered by training points), providing confidence in predictive ability of the model. Conclusion: Statistic of model DP1 reveals correlation coefficient (r2 = 0.9017), internal predictive ability (q2 = 0.8617) and external predictive ability for the test molecules (Pred r2 = 0.8138). The low standard error i.e. r2 se = 0.24, q2 se = 0.29 and Pred r2se = 0.28 demonstrates accuracy of the model. Values of different statistical parameters of model DP1 are within the limit for providing the best fit.

Keywords: Quantitative structure activity relationship, Diabetes mellitus, Glucokinase enzyme, Glucokinase activator, Optimization.


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