Abstract

Aldose reductase (ALR2) is a target enzyme for the treatment of diabetic complications. Owing to the limited number of currently available drugs for the treatment of diabetic complications, the discovery of new inhibitors of ALR2 that can potentially be optimized as drugs appears highly desirable. In this study, a molecular docking analysis of the structures of more than 127,000 organic compounds contained in the National Cancer Institute database was performed to find and score molecules that are complementary to ALR2. Besides retrieving several carboxylic acid derivatives, which are known to generally inhibit aldose reductase, docking proposed other families of putative inhibitors such as sulfonic acids, nitro-derivatives, sulfonamides and carbonyl derivatives. Twenty-five compounds, chosen as the highest-scoring representatives of each of these families, were tested as aldose reductase inhibitors. Five of them were found to inhibit aldose reductase in the micromolar range. For these active compounds, selectivity with respect to the closely-related aldehyde reductase was determined by measuring the corresponding inhibitory activities. The structures of the complexes between the new lead inhibitors and aldose reductase, here refined with molecular mechanics and molecular dynamics calculations, suggest that new pharmacophoric groups can bind aldose reductase very efficiently. In the case of the family of the nitro-derivative inhibitors, a class of particularly interesting compounds, a round of optimizations was performed with the synthesis and biological evaluation of a series of derivatives aimed at testing the proposed binding mode and at improving interaction with active site residues. Starting from a hit compound having an IC50 of 42μM, the most potent compound synthesized showed a 10-fold increase in inhibitory activity and 10-fold selectivity with respect to ALR1, and structure–activity relationships of the designed compounds were in agreement with the proposed mode of binding at the active site.

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