QSAR model development for studying carbonic anhydrase inhibitors as anticonvulsant agents

Abstract

The objective of this work was to develop quantitative structure activity relationship (QSAR) models from sulfonamide derivatives against anticonvulsant activity. For developing the model, multiple linear regression and artificial neural network (ANN) have been employed as effective and efficient methods and these models have been validated with statistical analysis such as fraction of variance, cross-validation test, quality factor, Fischer’s test, and internal validation test (Y-randomization test), where applicable. A regression-based QSAR model (linear model) has been developed with cross-validation test q 2 = 0.8324 and fraction of variance r 2 = 0.8327, all the statistical tests have validated this model. An ANN (nonlinear model)-based model has also been developed with fraction of variance r 2 = 0.8710 and cross validation test q 2 = 0.7032. So, with the help of the developed models we can predict the logKi values of novel designed molecules and alter their structural properties accordingly before synthesizing them.