LAUSR

In recent years, multistep hybrid computational protocols have attracted attention for their application in the drug discovery of enzyme inhibitors. So far, there are large collections of human carbonic anhydrase (hCA) inhibitors, but only a few of them selectively inhibit the mitochondrial isoforms hCA VA and VB as potential therapeutics in obesity treatment. Most sulfonamide‐based inhibitors show poor selectivity for inhibiting isoforms of therapeutic interest over ubiquitous hCA I and hCA II. Herein, we propose a combination of ligand‐ and structure‐based approaches to generate pharmacophore models for hCA VA inhibitors. Then, we performed a virtual screening (VS) campaign on a database of commercially available sulfonamides. Finally, the in silico screening followed by docking studies suggested several “hit compounds” that demonstrated to inhibit hCA VA at a low nanomolar concentration in a stopped‐flow CO2 hydrase assay. Notably, the best candidate, 2‐(3,4‐dihydro‐2H‐quinolin‐1‐yl)‐N‐(4‐sulfamoylphenyl)acetamide (code name VAME‐28) proved to be a potent hCA VA inhibitor (Ki value of 54.8 nM) and a more selective agent over hCA II when compared to the reference compound topiramate.