RIP2 kinase has been identified as a key signal transduction partner in the NOD2 pathway contributing to a variety of human pathologies, including immune-mediated inflammatory diseases. Small-molecule inhibitors of RIP2 kinase or its signaling partners on the NOD2 pathway that are suitable for advancement into the clinic have yet to be described. Herein, we report our discovery and profile of the prodrug clinical compound, inhibitor 3, currently in phase 1 clinical studies. Compound 3 potently binds to RIP2 kinase with good kinase specificity and has excellent activity in blocking many proinflammatory cytokine responses in vivo and in human IBD explant samples. The highly favorable physicochemical and ADMET properties of 3 combined with high potency led to a predicted low oral dose in humans.

The goal of the SAMPL (Statistical Assessment of the Modeling of Proteins and Ligands) challenge is to improve the accuracy of current computational models to estimate free energy of binding, deprotonation, distribution and other associated physical properties that are useful for the design of new pharmaceutical products. New experimental datasets of physicochemical properties provide opportunities for prospective evaluation of computational prediction methods. Here, aqueous pKa and a range of bi-phasic logD values for a variety of pharmaceutical compounds were determined through a streamlined automated process to be utilized in the SAMPL8 physical property challenge. The goal of this paper is to provide an in-depth review of the experimental methods utilized to create a comprehensive data set for the blind prediction challenge. The significance of this work involves the use of high throughput experimentation equipment and instrumentation to produce acid dissociation constants for twenty-three drug molecules, as well as distribution coefficients for eleven of those molecules.

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