Journal of Harmonized Research in Pharmacy

DEVELOPMENT OF QSAR MODEL FOR STUDYING SULFONAMIDE DERIVATIVESAGAINST CARBONIC ANHYDRASE USING MULTIPLE LINEAR REGRESSION WITH McGOWAN VOLUME AND ALOGP AS MOLECULAR DESCRIPTORS

Abstract

Author(s): Ajeet

Here sulfonamide analogues have been used to correlate the inhibition constant with the McGowan volume and ALogP descriptors for studying the Quantitative Structure Activity Relationship (QSAR). Correlation may be an adequate predictive model which can help to provide guidance in designing and subsequently yielding greatly specific compounds that may have reduced side effects and improved pharmacological activities. We have used Multiple Linear Regression (MLR) for developing QSAR model. For the validation of the developed QSAR model, statistical analysis such as cross validation test (as internal validation), quality factor, fischers test, root mean square deviation (RMSD), standard deviation, variance, Y-randomization test etc.; have been performed and all the tests validated this QSAR model with fraction of variance r2 = 0.8138 and LOO-CV q2 = 0.7887.