Abstract

Rinky Chawla and Surya Prakash Gupta^*

DOI : http://dx.doi.org/10.13005/ojc/390317

The objective of the present investigation was to obtain a QSAR model to predict the antiurease activity of a series of 1,2,4-triazole congeners with reported IC50 values in order to design new and better congeners. The calculation of descriptors was done using CDK package and the correlation matrix was developed using all the descriptors. All the variables were subjected to blind simulation in order to select the independent variables with least inter-correlation and high correlation with the anti-urease action. A total of 14 descriptors were finalized for QSAR model generation using Ezqsar. The MLR method was used to obtain the equation and fit of the equation to predict the anti-urease activity of the congeneric compounds. The QSAR model generated for the series was presented 14 independent variables affecting the urease inhibition action.With a regression coefficient of 0.9976 (R2), the created model was determined to have strong predictive power.

Polarizability; QSAR; SMILES; Taft steric parameter; 1,2,4-triazole; Urease

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