Identification of Novel Potential Inhibitors of Aldose Reductase: A Multistage Computational Filtering Approach

Publication: Recent Advance in Diabetes Treatment
Software: ADMET Predictor®


The aldose reductase (AR) is a rate limiting enzyme in the polyol pathway, for the conversion of glucose to sorbitol. The identification of a potent inhibitor is the need of the hour. There are only few marketed drugs presently in use and majority of the potential inhibitors has not yet reached in drug stores due to the toxic effects. The present study applied multistage filtering approach for identifying potent inhibitors with least toxicity as well as maintaining the important interactions with catalytic residues of aldose reductase. Different filters at various stages are employed to narrow down the preferable lead ligands in screening of TCM compound library. A novel method of using an overlapping common pharmacophore feature and an ADMET toxicity predictor are used to identify lead compounds with least toxicity. The toxicity prediction at an early stage is desirable to avoid future rejection of molecules due to toxicity alone. The final shortlisted candidates are subjected to Molecular Dynamics simulations to substantiate their stability compared to the well tested inhibitor characteristics.