Evolutionary chemistry approach toward finding novel inhibitors of the type 2 diabetes target glucose-6-phosphate translocase

Abstract

A genetic algorithm (GA), driven by experimentally determined biological activities as a feedback fitness function, was used to propose novel small molecules as inhibitors of glucose-6-phosphate translocase (G6PT) in iterative rounds of evolutionary optimization. A straightforward polymer-supported synthetic sequence was implemented to synthesize molecules proposed by the GA, and the biological activities of the compounds were determined by a microsomal assay. Additional compound design strategies were integrated, such as Tanimoto similarity-based selection of starting materials and transfer of favored structure elements into a new chemical scaffold to identify more active and selective inhibitors.