QSAR, ADME and docking guided semi-synthesis and in vitro evaluation of 4-hydroxy-α-tetralone analogs for anti-inflammatory activity

The compound 4-hydroxy-α-tetralone (1) is major bioactive secondary metabolite of genus Ammannia (Family- Lythraceae). The compound 1 and its various derivatives are reported to possess anti-tubercular, anti-diabetic, anti-leishmanial and bioenhancing activities. A quantitative structure activity relationship (QSAR) model for predicting anti-inflammatory activity of 4-hydroxy-α-tetralone derivatives against the tumour necrosis factor (TNF)-α, a pro-inflammatory cytokine was developed by non-linear model using artificial neural network (ANN). The regression coefficient (r2) and the leave-one-out cross-validation regression coefficient (LOO rCV2) of the QSAR model were 0.6976 and 0.4016, respectively, while the regression coefficient (r2) for the external set of experimental compounds was 0.835. The 4-hydroxy-α-tetralone virtual derivatives, which showed significant inhibition of TNF-α were subjected to docking and in-silico absorption, distribution, metabolism and excretion (ADME) studies and the results showed similar binding affinity and bioavailability in compliance with the standard drug, Diclofenac. Finally, in order to validate the developed QSAR model, the most and least active virtual derivatives were semi-synthesized, characterized on the basis of their 1H and 13C NMR spectroscopic data and in vitro tested for concentration dependent inhibition of TNF-α. The experimental results obtained, agreed well with the predicted values.