Abstract
Protein kinases are versatile molecule switches that govern functional processes in signal transduction networks and regulate fundamental biological processes of cell cycle and organism development. The continuous growth of biological information and a remarkable breath of structural, genetic, and pharmacological studies on protein kinase genes have significantly advanced our knowledge of the kinase activation, drug binding and allosteric mechanisms underlying kinase regulation and interactions in signaling cascades.. Structural and biochemical studies of the genetic and molecular determinants of protein kinases binding with inhibitors have been the cornerstone of drug discovery efforts in clinical oncology leading to proliferation of effective anticancer therapies. Recent advances in understanding allosteric regulation of protein kinases have fueled unprecedented efforts aiming in the discovery of targeted and allosteric kinase inhibitors that can combat cancer mutants and are at the forefront of the precision medicine initiative in oncology. Despite diversity of regulatory scenarios underlying kinase functions, dimerization-driven activation is a common mechanism of allosteric regulation that is shared by many protein kinase families, most notably ErbB and BRAF kinases that play a central role in growth factor signaling and human disease. In this review, we focused on structural, biochemical and computational studies of the ErbB and BRAF kinases and discuss how diversity of the structural landscape for these kinase genes and dimerization- dependent mechanisms of their regulation can be leveraged in the design and discovery of kinase inhibitors and allosteric modulators of kinase activation. The lessons from this analysis could inform discovery of specific targeted therapies and robust drug combinations for cancer treatment.
Keywords: ErbB kinases, BRAF kinases, dimerization-induced kinase activation, BRAF paradoxical activation, allosteric regulation, allosteric kinase inhibitors, computational modeling of protein kinases, multiscale simulations, kinase residue interaction networks.