Exploration of QSAR modelling techniques and their combination to rationalize the physicochemical characters of nitrophenyl derivatives towards aldose reductase inhibition.

The quantitative structure-activity relationship (QSAR) analysis of nitrophenyls active as aldose reductase inhibitors (ARIs) has been performed employing Fujita-Ban, classical Hansch approach and physicochemical properties. The multivariant regression expressions were developed using sequential multiple linear regression (SEQ-MLR) techniques considering adjustable correlation coefficient (r(2)(adj)). The statistical quality of SEQ-MLR equations were evaluated considering parameters like correlation coefficient (r), standard error of estimation (SEE), and variance ratio (F) at explicit degree of freedom (df). Orthogonality of the descriptors in SEQ-MLR was established through variance inflation factor (VIF).The QSAR analysis gave insight to some common important structural feature i.e. the hydroxyl group is crucial for hydrogen bond interaction with the receptor. Similarly electro-negative substitution is essential for polar interaction with charge region of the receptor. Moreover analysis inferred that diarylsulphides can be explored for optimization of the analogs.