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Antitubercular activity of Sulfathiazole Derivitives series were subjected toQuantitative Structure Activity Relationship (QSAR) Analysis with an attempt toderive and understand a correlation between the Biologically Activity asdependent variable and various descriptors as independent variables. QSARmodels generated using 28 compounds. Several statistical regression expressionswere obtained using Partial Least Squares (PLS) Regression, Multiple LinearRegression (MLR) and Principal Component Regression (PCR) methods. The amongthese methods, Partial Least Square Regression (PLS) method has shown verypromising result as compare to other two methods. A QSAR model was generated bya training set of 18 molecules with correlation coefficient r (r square) of0.9191, significant cross validated correlation coefficient (q square) of0.8300, F test of 53.5783, r square for external test set pred_r square-3.6132, coefficient of correlation of predicted data set pred_r_se square1.4859 and degree of freedom 14 by Partial Least Squares Regression Method.

Predictive Comparative QSAR analysis of Sulfathiazole Analogues as Mycobacterium Tuberculosis H37RV Inhabitors