Revisiting protein kinase–substrate interactions: Toward therapeutic development

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Science Signaling  22 Mar 2016:
Vol. 9, Issue 420, pp. re3
DOI: 10.1126/scisignal.aad4016


Protein phosphorylation is a common posttranslational modification and is involved in many physiological and pathophysiological processes. Among other diseases, the deregulation of protein kinase activities can lead to cellular transformation and cancer. Thus, kinases are good drug targets. Understanding how kinases interact with their substrates may elucidate processes that lead to disease, as well as aid in the development of better, more specific kinase inhibitors with improved clinical success. In this Review, which contains 4 figures, 2 tables, and 129 references, we summarize the advances in understanding how kinases physically interact with their substrates and discuss the technologies to detect kinase substrates.


Despite the efforts of pharmaceutical companies to develop specific kinase modulators, few drugs targeting kinases have been completely successful in the clinic. This is primarily due to the conserved nature of kinases, especially in the catalytic domains. Consequently, many currently available inhibitors lack sufficient selectivity for effective clinical application. Kinases phosphorylate their substrates to modulate their activity. One of the important steps in the catalytic reaction of protein phosphorylation is the correct positioning of the target residue within the catalytic site. This positioning is mediated by several regions in the substrate binding site, which is typically a shallow crevice that has critical subpockets that anchor and orient the substrate. The structural characterization of this protein-protein interaction can aid in the elucidation of the roles of distinct kinases in different cellular processes, the identification of substrates, and the development of specific inhibitors. Because the region of the substrate that is recognized by the kinase can be part of a linear consensus motif or a nonlinear motif, advances in technology beyond simple linear sequence scanning for consensus motifs were needed. Cost-effective bioinformatics tools are already frequently used to predict kinase-substrate interactions for linear consensus motifs, and new tools based on the structural data of these interactions improve the accuracy of these predictions and enable the identification of phosphorylation sites within nonlinear motifs. In this Review, we revisit kinase-substrate interactions and discuss the various approaches that can be used to identify them and analyze their binding structures for targeted drug development.

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