In-silico guided discovery of novel CCR9 antagonists

Antagonism of CCR9 is a promising mechanism for treatment of inflammatory bowel disease, including ulcerative colitis and Crohn's disease. There is limited experimental data on CCR9 and its ligands, complicating efforts to identify new small molecule antagonists. We present here results of a successful virtual screening and rational hit-to-lead campaign that led to the discovery and initial optimization of novel CCR9 antagonists. This work uses a novel data fusion strategy to integrate the output of multiple computational tools, such as 2D similarity search, shape similarity, pharmacophore searching, and molecular docking, as well as the identification and incorporation of privileged chemokine fragments. The application of various ranking strategies, which combined consensus and parallel selection methods to achieve a balance of enrichment and novelty, resulted in 198 virtual screening hits in total, with an overall hit rate of 18%. Several hits were developed into early leads through targeted synthesis and purchase of analogs.