The potent and selective RIPK2 inhibitor BI 706039 improves intestinal inflammation in the TRUC mouse model of inflammatory bowel disease.

Mouse and human data implicate the NOD1 and NOD2 sensors of the intestinal microbiome and the associated signal transduction via the receptor interacting protein kinase 2 (RIPK2) as a potential key signaling node for the development of inflammatory bowel disease (IBD) and an attractive target for pharmacological intervention. The TRUC mouse model of IBD was strongly indicated for evaluating RIPK2 antagonism for its effect on intestinal inflammation based on previous knockout studies with NOD1, NOD2, and RIPK2. We identified and profiled the BI 706039 molecule as a potent and specific functional inhibitor of both human and mouse RIPK2 and with favorable pharmacokinetic properties. We dosed BI 706039 in the spontaneous TRUC mouse model from age 28 to 56 days. Oral, daily administration of BI 706039 caused dose-responsive and significant improvement in colonic histopathological inflammation, colon weight, and terminal levels of protein-normalized fecal lipocalin (all P values <0.001). These observations correlated with dose responsively increasing systemic levels of the BI 706039 compound, splenic molecular target engagement of RIPK2, and modulation of inflammatory genes in the colon. This demonstrates that a relatively low oral dose of a potent and selective RIPK2 inhibitor can modulate signaling in the intestinal immune system and significantly improve disease associated intestinal inflammation.NEW & NOTEWORTHY The RIPK2 kinase at the apex of microbiome immunosensing is an attractive target for pharmacological intervention. A low oral dose of a RIPK2 inhibitor leads to significantly improved intestinal inflammation in the murine TRUC model of colitis. A selective and potent inhibitor of the RIPK2 kinase may represent a new class of therapeutics that target microbiome-driven signaling for the treatment of IBD.

Multiscale computational model predicts how environmental changes and drug treatments affect microvascular remodeling in fibrotic disease.

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired due to loss of alveolar structures and lung function declines. Here, we integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (ECs) and pericytes, the cells that comprise microvessels. Nintedanib, an FDA-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition (PMT) in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can explain how cell decisions affect tissue changes during disease and in response to treatments.