Rational Method for Structural Simplification as Key Step in Hit Discovery: The Case of FGFR2 and IGF1R Dual Inhibitors

Abstract

In the classic medicinal chemistry hit discovery procedure, large virtual libraries undergo different filtering and prediction steps until a small group of molecules is selected for their subsequent synthesis and biological testing. The starting molecular libraries can easily be composed of millions of molecules, hindering the selection of the most representative and promising compounds. Moreover, the resulting molecular systems tend to be overcomplex structures, hardly attainable, and often involve extrapolations of the prediction models used. We present a rational-based method to reduce the structural complexity of molecular candidates without compromising their biological activity, improving the attainability and efficiency of hit discovery. This approach has been successfully applied to identify potential tyrosine kinase dual inhibitors against Fibroblast Growth Factor Receptor 2 (FGFR2) and Insulin-Like Growth Factor 1 Receptor (IGF1R), a set of overexpressed proteins in different cancers, such as pancreatic ductal adenocarcinoma (PDAC).