Identification of direct target engagement biomarkers for kinase-targeted therapeutics

鉴定激酶靶向治疗的直接靶点结合生物标志物

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Abstract

Pharmacodynamic (PD) biomarkers are an increasingly valuable tool for decision-making and prioritization of lead compounds during preclinical and clinical studies as they link drug-target inhibition in cells with biological activity. They are of particular importance for novel, first-in-class mechanisms, where the ability of a targeted therapeutic to impact disease outcome is often unknown. By definition, proximal PD biomarkers aim to measure the interaction of a drug with its biological target. For kinase drug discovery, protein substrate phosphorylation sites represent candidate PD biomarkers. However, substrate phosphorylation is often controlled by input from multiple converging pathways complicating assessment of how potently a small molecule drug hits its target based on substrate phoshorylation measurements alone. Here, we report the use of quantitative, differential mass-spectrometry to identify and monitor novel drug-regulated phosphorylation sites on target kinases. Autophosphorylation sites constitute clinically validated biomarkers for select protein tyrosine kinase inhibitors. The present study extends this principle to phosphorylation sites in serine/threonine kinases looking beyond the T-loop autophosphorylation site. Specifically, for the 3'-phosphoinositide-dependent protein kinase 1 (PDK1), two phospho-residues p-PDK1(Ser410) and p-PDK1(Thr513) are modulated by small-molecule PDK1 inhibitors, and their degree of dephosphorylation correlates with inhibitor potency. We note that classical, ATP-competitive PDK1 inhibitors do not modulate PDK1 T-loop phosphorylation (p-PDK1(Ser241)), highlighting the value of an unbiased approach to identify drug target-regulated phosphorylation sites as these are complementary to pathway PD biomarkers. Finally, we extend our analysis to another protein Ser/Thr kinase, highlighting a broader utility of our approach for identification of kinase drug-target engagement biomarkers.

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