FGF401, A First-In-Class Highly Selective and Potent FGFR4 Inhibitor for the Treatment of FGF19-Driven Hepatocellular Cancer.

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and it is the third leading cause of cancer-related deaths worldwide. Recently, aberrant signaling through the FGF19/FGFR4 axis has been implicated in HCC. Here, we describe the development of FGF401, a highly potent and selective, first in class, reversible-covalent small-molecule inhibitor of the kinase activity of FGFR4. FGF401 is exquisitely selective for FGFR4 versus the other FGFR paralogues FGFR1, FGFR2, FGFR3, and all other kinases in the kinome. FGF401 has excellent drug-like properties showing a robust pharmacokinetic/pharmacodynamics/efficacy relationship, driven by a fraction of time above the phospho-FGFR4 IC90 value. FGF401 has remarkable antitumor activity in mice bearing HCC tumor xenografts and patient-derived xenograft models that are positive for FGF19, FGFR4, and KLB. FGF401 is the first FGFR4 inhibitor to enter clinical trials, and a phase I/II study is currently ongoing in HCC and other solid malignancies.

Structural biology contributions to the discovery of drugs to treat chronic myelogenous leukaemia.

Chronic myelogenous leukaemia (CML) results from the Bcr-Abl oncoprotein, which has a constitutively activated Abl tyrosine kinase domain. Although most chronic phase CML patients treated with imatinib as first-line therapy maintain excellent durable responses, patients who have progressed to advanced-stage CML frequently fail to respond or lose their response to therapy owing to the emergence of drug-resistant mutants of the protein. More than 40 such point mutations have been observed in imatinib-resistant patients. The crystal structures of wild-type and mutant Abl kinase in complex with imatinib and other small-molecule Abl inhibitors were determined, with the aim of understanding the molecular basis of resistance and to aid in the design and optimization of inhibitors active against the resistance mutants. These results are presented in a way which illustrates the approaches used to generate multiple structures, the type of information that can be gained and the way that this information is used to support drug discovery.