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. The Catalytic Domain of Eukaryotic Protein KinasesTypically, eukaryotic protein kinases are composed of nonconserved regulatory domains and a conserved catalytic core of~250 amino acid residues that binds and anchors substrates and is responsible for catalysis (1). The catalytic domain consists of two lobes called N and C (also known as small and large lobes, respectively), named for their N-or C-terminal position, respectively, within the domain. The N-lobe consists of five-stranded, anti-parallel b sheets that are an essential part of the adenosine triphosphate (ATP) binding site, whereas the C-lobe is mostly helical (Fig. 1A). The active-site cleft, which contains the ATP binding site, lies between the two lobes (2). In an activated kinase, the lobes converge to form a deep cleft where the adenine ring of ATP binds such that the g-phosphate is positioned at the outer edge where the transfer of the phosphoryl group occurs, whereas the adenosine moiety is buried in a hydrophobic region of the pocket (Fig. 1B). Adjacent to the ATP binding pocket is a shallow crevice called the substrate binding site (SBS) that anchors the substrate and correctly positions the phosphorylatable residue (2).Catalysis is mediated by opening and closing of this active-site cleft. Substrates are anchored and p...

Linear consensus motifs are short contiguous sequences of residues within a protein that can form recognition modules for protein interaction or catalytic modification. Protein kinase specificity and the matching of kinases to substrates have been mostly defined by phosphorylation sites that occur in linear consensus motifs. However, phosphorylation can also occur within sequences that do not match known linear consensus motifs recognized by kinases and within flexible loops. We report the identification of Thr(253) in α-tubulin as a site that is phosphorylated by protein kinase C βI (PKCβI). Thr(253) is not part of a linear PKC consensus motif. Instead, Thr(253) occurs within a region on the surface of α-tubulin that resembles a PKC phosphorylation site consensus motif formed by basic residues in different parts of the protein, which come together in the folded protein to form the recognition motif for PKCβI. Mutations of these basic residues decreased substrate phosphorylation, confirming the presence of this "structurally formed" consensus motif and its importance for the protein kinase-substrate interaction. Analysis of previously reported protein kinase A (PKA) and PKC substrates identified sites within structurally formed consensus motifs in many substrates of these two kinase families. Thus, the concept of consensus phosphorylation site motif needs to be expanded to include sites within these structurally formed consensus motifs.

Studies show that neuropeptide-receptor systems in the basolateral amygdala (BLA) play an important role in the pathology of anxiety and other mood disorders. Since GPR171, a recently deorphanized receptor for the abundant neuropeptide BigLEN, is expressed in the BLA, we investigated its role in fear and anxiety-like behaviors. To carry out these studies we identified small molecule ligands using a homology model of GPR171 to virtually screen a library of compounds. One of the hits, MS0021570_1, was identified as a GPR171 antagonist based on its ability to block (i) BigLEN-mediated activation of GPR171 in heterologous cells, (ii) BigLEN-mediated hyperpolarization of BLA pyramidal neurons, and (iii) feeding induced by DREADD-mediated activation of BigLEN containing AgRP neurons in the arcuate nucleus. The role of GPR171 in anxiety-like behavior or fear conditioning was evaluated following systemic or intra-BLA administration of MS0021570_1, as well as following lentiviral-mediated knockdown of GPR171 in the BLA. We find that systemic administration of MS0021570_1 attenuates anxiety-like behavior while intra-BLA administration or knockdown of GPR171 in the BLA reduces anxiety-like behavior and fear conditioning. These results indicate that the BigLEN-GPR171 system plays an important role in these behaviors and could be a novel target to develop therapeutics to treat psychiatric disorders.

Taken together, our results reveal the existence of an intracellular selection process in macrophages that favors TcII, but not TcI, when infection occurs with vector-derived mixed TcI/TcII strains.

Protein kinase C (PKC) plays a regulatory role in key pathways in cancer. However, since phosphorylation is a step for classical PKC (cPKC) maturation and does not correlate with activation, there is a lack of tools to detect active PKC in tissue samples. Here, a structure-based rational approach was used to select a peptide to generate an antibody that distinguishes active from inactive cPKC. A peptide conserved in all cPKCs, C2Cat, was chosen since modeling studies based on a crystal structure of PKCβ showed that it is localized at the interface between the C2 and catalytic domains of cPKCs in an inactive kinase. Anti-C2Cat recognizes active cPKCs at least two-fold better than inactive kinase in ELISA and immunoprecipitation assays, and detects the temporal dynamics of cPKC activation upon receptor or phorbol stimulation. Furthermore, the antibody is able to detect active PKC in human tissue. Higher levels of active cPKC were observed in the more aggressive triple negative breast cancer tumors as compared to the less aggressive estrogen receptor positive tumors. Thus, this antibody represents a reliable, hitherto unavailable and a valuable tool to study PKC activation in cells and tissues. Similar structure-based rational design strategies can be broadly applied to obtain active-state specific antibodies for other signal transduction molecules.