Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs

Deciphering the Arginine-binding preferences at the substrate-binding groove of Ser/Thr kinases by computational surface mapping

Protein kinases are key signaling enzymes that catalyze the transfer of γ-phosphate from an ATP molecule to a phospho-accepting residue in the substrate. Unraveling the molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor is important for understanding kinase specificities toward their substrates and for designing substrate-like peptidic inhibitors. We applied ANCHORSmap, a new fragment-based computational approach for mapping amino acid side chains on protein surfaces, to predict and characterize the preference of kinases toward Arginine binding. We focus on positions P−2 and P−5, commonly occupied by Arginine (Arg) in substrates of basophilic Ser/Thr kinases. The method accurately identified all the P−2/P−5 Arg binding sites previously determined by X-ray crystallography and produced Arg preferences that corresponded to those experimentally found by peptide arrays. The predicted Arg-binding positions and their associated pockets were analyzed in terms of shape, physicochemical properties, amino acid composition, and in-silico mutagenesis, providing structural rationalization for previously unexplained trends in kinase preferences toward Arg moieties. This methodology sheds light on several kinases that were described in the literature as having non-trivial preferences for Arg, and provides some surprising departures from the prevailing views regarding residues that determine kinase specificity toward Arg. In particular, we found that the preference for a P−5 Arg is not necessarily governed by the 170/230 acidic pair, as was previously assumed, but by several different pairs of acidic residues, selected from positions 133, 169, and 230 (PKA numbering). The acidic residue at position 230 serves as a pivotal element in recognizing Arg from both the P−2 and P−5 positions.

Protein kinases are key signaling enzymes and major drug targets that catalyze the transfer of phosphate group to a phospho-accepting residue in the substrate. Unraveling molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor (substrate consensus sequence, SCS) is important for understanding kinase-substrates specificities and for designing peptidic inhibitors. Current methods used to predict this set of essential residues usually rely on linking between experimentally determined SCSs to kinase sequences. As such, these methods are less sensitive when specificity is dictated by subtle or kinase-unique sequence/structural features. In this study, we took a different approach for studying kinases specificities, by applying a new fragment-based method for mapping amino acid side chains on protein surfaces. We predicted and characterized the preference of Ser/Thr kinases toward Arginine binding, using the unbound kinase structures. The method produced high quality predictions and was able to provide novel insights and interesting departures from the prevailing views regarding the specificity-determining elements governing specificity toward Arginine. This work paves the way for studying the kinase binding preferences for other amino acids, for predicting protein-peptide structures, for facilitating the design of novel inhibitors, and for re-engineering of kinase specificities.

Cyclin-specific docking motifs promote phosphorylation of yeast signaling proteins by G1/S Cdk complexes

BACKGROUND

The eukaryotic cell cycle begins with a burst of cyclin-dependent kinase (Cdk) phosphorylation. In budding yeast, several Cdk substrates are preferentially phosphorylated at the G1/S transition rather than later in the cell cycle when Cdk activity levels are high. These early Cdk substrates include signaling proteins in the pheromone response pathway. Two such proteins, Ste5 and Ste20, are phosphorylated only when Cdk is associated with the G1/S cyclins Cln1 and Cln2 and not G1, S, or M cyclins. The basis of this cyclin specificity is unknown.

RESULTS

Here we show that Ste5 and Ste20 have recognition sequences, or "docking" sites, for the G1/S cyclins. These docking sites, which are distinct from Clb5/cyclin A-binding "RXL" motifs, bind preferentially to Cln2. They strongly enhance Cln2-driven phosphorylation of each substrate in vivo and function largely independent of position and distance to the Cdk sites. We exploited this functional independence to rewire a Cdk regulatory circuit in a way that changes the target of Cdk inhibition in the pheromone response pathway. Furthermore, we uncover functionally active Cln2 docking motifs in several other Cdk substrates. The docking motifs drive cyclin-specific phosphorylation, and the cyclin preference can be switched by using a distinct motif.

CONCLUSIONS

Our findings indicate that some Cdk substrates are intrinsically capable of being phosphorylated by several different cyclin-Cdk forms, but they are inefficiently phosphorylated in vivo without a cyclin-specific docking site. Docking interactions may play a prevalent but previously unappreciated role in driving phosphorylation of select Cdk substrates preferentially at the G1/S transition.

The role of protein disorder in the 14-3-3 interaction network

Disordered regions are segments of a protein that do not fold completely and thus remain flexible. These regions have key physiological roles, particularly in phospho-proteins, which are enriched in disorder-promoting residues surrounding their phosphorylation sites. 14-3-3 proteins are ordered hubs that interact with multiple and diverse intrinsically disordered phosphorylated targets. This provides 14-3-3 with the ability to participate in and to regulate multiple signalling networks. Here, I review the effect of structural disorder on the mechanism involved in 14-3-3 protein-protein interactions and how 14-3-3 impacts cell biology through disordered ligands. How 14-3-3 proteins constitute an advantageous system to identify novel classes of biological tools is discussed with a special emphasis on a particular-and innovative-use of small molecules to stabilize 14-3-3 protein complexes, useful to study gene expression, cancer signalling and neurodegenerative diseases.

Arabidopsis RTNLB1 and RTNLB2 Reticulon-like proteins regulate intracellular trafficking and activity of the FLS2 immune receptor

Receptors localized at the plasma membrane are critical for the recognition of pathogens. The molecular determinants that regulate receptor transport to the plasma membrane are poorly understood. In a screen for proteins that interact with the FLAGELIN-SENSITIVE2 (FLS2) receptor using Arabidopsis thaliana protein microarrays, we identified the reticulon-like protein RTNLB1. We showed that FLS2 interacts in vivo with both RTNLB1 and its homolog RTNLB2 and that a Ser-rich region in the N-terminal tail of RTNLB1 is critical for the interaction with FLS2. Transgenic plants that lack RTNLB1 and RTNLB2 (rtnlb1 rtnlb2) or overexpress RTNLB1 (RTNLB1ox) exhibit reduced activation of FLS2-dependent signaling and increased susceptibility to pathogens. In both rtnlb1 rtnlb2 and RTNLB1ox, FLS2 accumulation at the plasma membrane was significantly affected compared with the wild type. Transient overexpression of RTNLB1 led to FLS2 retention in the endoplasmic reticulum (ER) and affected FLS2 glycosylation but not FLS2 stability. Removal of the critical N-terminal Ser-rich region or either of the two Tyr-dependent sorting motifs from RTNLB1 causes partial reversion of the negative effects of excess RTNLB1 on FLS2 transport out of the ER and accumulation at the membrane. The results are consistent with a model whereby RTNLB1 and RTNLB2 regulate the transport of newly synthesized FLS2 to the plasma membrane.

Dynamics of Cdk1 substrate specificity during the cell cycle

Cdk specificity is determined by the intrinsic selectivity of the active site and by substrate docking sites on the cyclin subunit. There is a long-standing debate about the relative importance of these factors in the timing of Cdk1 substrate phosphorylation. We analyzed major budding yeast cyclins (the G1/S-cyclin Cln2, S-cyclin Clb5, G2/M-cyclin Clb3, and M-cyclin Clb2) and found that the activity of Cdk1 toward the consensus motif increased gradually in the sequence Cln2-Clb5-Clb3-Clb2, in parallel with cell cycle progression. Further, we identified a docking element that compensates for the weak intrinsic specificity of Cln2 toward G1-specific targets. In addition, Cln2-Cdk1 showed distinct consensus site specificity, suggesting that cyclins do not merely activate Cdk1 but also modulate its active-site specificity. Finally, we identified several Cln2-, Clb3-, and Clb2-specific Cdk1 targets. We propose that robust timing and ordering of cell cycle events depend on gradual changes in the substrate specificity of Cdk1.

Identification of specificity determining residues in peptide recognition domains using an information theoretic approach applied to large-scale binding maps

Background

Peptide Recognition Domains (PRDs) are commonly found in signaling proteins. They mediate protein-protein interactions by recognizing and binding short motifs in their ligands. Although a great deal is known about PRDs and their interactions, prediction of PRD specificities remains largely an unsolved problem.

Results

We present a novel approach to identifying these Specificity Determining Residues (SDRs). Our algorithm generalizes earlier information theoretic approaches to coevolution analysis, to become applicable to this problem. It leverages the growing wealth of binding data between PRDs and large numbers of random peptides, and searches for PRD residues that exhibit strong evolutionary covariation with some positions of the statistical profiles of bound peptides. The calculations involve only information from sequences, and thus can be applied to PRDs without crystal structures. We applied the approach to PDZ, SH3 and kinase domains, and evaluated the results using both residue proximity in co-crystal structures and verified binding specificity maps from mutagenesis studies.

Discussion

Our predictions were found to be strongly correlated with the physical proximity of residues, demonstrating the ability of our approach to detect physical interactions of the binding partners. Some high-scoring pairs were further confirmed to affect binding specificity using previous experimental results. Combining the covariation results also allowed us to predict binding profiles with higher reliability than two other methods that do not explicitly take residue covariation into account.

Conclusions

The general applicability of our approach to the three different domain families demonstrated in this paper suggests its potential in predicting binding targets and assisting the exploration of binding mechanisms.

Defining the substrate specificity determinants recognized by the active site of C-terminal Src kinase-homologous kinase (CHK) and identification of β-synuclein as a potential CHK physiological substrate

C-Terminal Src kinase-homologous kinase (CHK) exerts its tumor suppressor function by phosphorylating the C-terminal regulatory tyrosine of the Src-family kinases (SFKs). The phosphorylation suppresses their activity and oncogenic action. In addition to phosphorylating SFKs, CHK also performs non-SFK-related functions by phosphorylating other cellular protein substrates. To define these non-SFK-related functions of CHK, we used the "kinase substrate tracking and elucidation" method to search for its potential physiological substrates in rat brain cytosol. Our search revealed β-synuclein as a potential CHK substrate, and Y127 in β-synuclein as the preferential phosphorylation site. Using peptides derived from β-synuclein and positional scanning combinatorial peptide library screening, we defined the optimal substrate phosphorylation sequence recognized by the CHK active site to be E-x-[Φ/E/D]-Y-Φ-x-Φ, where Φ and x represent hydrophobic residues and any residue, respectively. Besides β-synuclein, cellular proteins containing motifs resembling this sequence are potential CHK substrates. Intriguingly, the CHK-optimal substrate phosphorylation sequence bears little resemblance to the C-terminal tail sequence of SFKs, indicating that interactions between the CHK active site and the local determinants near the C-terminal regulatory tyrosine of SFKs play only a minor role in governing specific phosphorylation of SFKs by CHK. Our results imply that recognition of SFKs by CHK is mainly governed by interactions between motifs located distally from the active site of CHK and determinants spatially separate from the C-terminal regulatory tyrosine in SFKs. Thus, besides assisting in the identification of potential CHK physiological substrates, our findings shed new light on how CHK recognizes SFKs and other protein substrates.

Predicting protein kinase specificity: Predikin update and performance in the DREAM4 challenge

Predikin is a system for making predictions about protein kinase specificity. It was declared the “best performer” in the protein kinase section of the Peptide Recognition Domain specificity prediction category of the recent DREAM4 challenge (an independent test using unpublished data). In this article we discuss some recent improvements to the Predikin web server — including a more streamlined approach to substrate-to-kinase predictions and whole-proteome predictions — and give an analysis of Predikin's performance in the DREAM4 challenge. We also evaluate these improvements using a data set of yeast kinases that have been experimentally characterised, and we discuss the usefulness of Frobenius distance in assessing the predictive power of position weight matrices.

Phosphorylation network rewiring by gene duplication

In a comprehensive analysis of phosphoregulatory evolution in yeast, the authors observe that phosphorylation sites tend to be lost after gene duplication and protein network turnover reshuffles kinase–substrate relationships over time.

Elucidating how complex regulatory networks have assembled during evolution requires a detailed understanding of the evolutionary dynamics that follow gene duplication events, including changes in post-translational modifications. We compared the phosphorylation profiles of paralogous proteins in the budding yeast Saccharomyces cerevisiae to that of a species that diverged from the budding yeast before the duplication of those genes. We found that 100 million years of post-duplication divergence are sufficient for the majority of phosphorylation sites to be lost or gained in one paralog or the other, with a strong bias toward losses. However, some losses may be partly compensated for by the evolution of other phosphosites, as paralogous proteins tend to preserve similar numbers of phosphosites over time. We also found that up to 50% of kinase–substrate relationships may have been rewired during this period. Our results suggest that after gene duplication, proteins tend to subfunctionalize at the level of post-translational regulation and that even when phosphosites are preserved, there is a turnover of the kinases that phosphorylate them.

The mTOR-regulated phosphoproteome reveals a mechanism of mTORC1-mediated inhibition of growth factor signaling

The mammalian target of rapamycin (mTOR) protein kinase is a master growth promoter that nucleates two complexes, mTORC1 and mTORC2. Despite the diverse processes controlled by mTOR, few substrates are known. We defined the mTOR-regulated phosphoproteome by quantitative mass spectrometry and characterized the primary sequence motif specificity of mTOR using positional scanning peptide libraries. We found that the phosphorylation response to insulin is largely mTOR dependent and that mTOR exhibits a unique preference for proline, hydrophobic, and aromatic residues at the +1 position. The adaptor protein Grb10 was identified as an mTORC1 substrate that mediates the inhibition of phosphoinositide 3-kinase typical of cells lacking tuberous sclerosis complex 2 (TSC2), a tumor suppressor and negative regulator of mTORC1. Our work clarifies how mTORC1 inhibits growth factor signaling and opens new areas of investigation in mTOR biology.

Diverse protein kinase interactions identified by protein microarrays reveal novel connections between cellular processes

Protein kinases are key regulators of cellular processes. In spite of considerable effort, a full understanding of the pathways they participate in remains elusive. We globally investigated the proteins that interact with the majority of yeast protein kinases using protein microarrays. Eighty-five kinases were purified and used to probe yeast proteome microarrays. One-thousand-twenty-three interactions were identified, and the vast majority were novel. Coimmunoprecipitation experiments indicate that many of these interactions occurred in vivo. Many novel links of kinases to previously distinct cellular pathways were discovered. For example, the well-studied Kss1 filamentous pathway was found to bind components of diverse cellular pathways, such as those of the stress response pathway and the Ccr4-Not transcriptional/translational regulatory complex; genetic tests revealed that these different components operate in the filamentation pathway in vivo. Overall, our results indicate that kinases operate in a highly interconnected network that coordinates many activities of the proteome. Our results further demonstrate that protein microarrays uncover a diverse set of interactions not observed previously.

Phosphorylation of Mcm2 modulates Mcm2-7 activity and affects the cell's response to DNA damage

The S-phase kinase, DDK controls DNA replication through phosphorylation of the replicative helicase, Mcm2–7. We show that phosphorylation of Mcm2 at S164 and S170 is not essential for viability. However, the relevance of Mcm2 phosphorylation is demonstrated by the sensitivity of a strain containing alanine at these positions (mcm2_AA) to methyl methanesulfonate (MMS) and caffeine. Consistent with a role for Mcm2 phosphorylation in response to DNA damage, the mcm2_AA strain accumulates more RPA foci than wild type. An allele with the phosphomimetic mutations S164E and S170E (mcm2_EE) suppresses the MMS and caffeine sensitivity caused by deficiencies in DDK function. In vitro, phosphorylation of Mcm2 or Mcm2_EE reduces the helicase activity of Mcm2–7 while increasing DNA binding. The reduced helicase activity likely results from the increased DNA binding since relaxing DNA binding with salt restores helicase activity. The finding that the ATP site mutant mcm2_K549R has higher DNA binding and less ATPase than mcm2_EE, but like mcm2_AA results in drug sensitivity, supports a model whereby a specific range of Mcm2–7 activity is required in response to MMS and caffeine. We propose that phosphorylation of Mcm2 fine-tunes the activity of Mcm2–7, which in turn modulates DNA replication in response to DNA damage.

A quantitative literature-curated gold standard for kinase-substrate pairs

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.

Quantitative mass spectrometry analysis reveals similar substrate consensus motif for human Mps1 kinase and Plk1

BACKGROUND

Members of the Mps1 kinase family play an essential and evolutionarily conserved role in the spindle assembly checkpoint (SAC), a surveillance mechanism that ensures accurate chromosome segregation during mitosis. Human Mps1 (hMps1) is highly phosphorylated during mitosis and many phosphorylation sites have been identified. However, the upstream kinases responsible for these phosphorylations are not presently known.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we identify 29 in vivo phosphorylation sites in hMps1. While in vivo analyses indicate that Aurora B and hMps1 activity are required for mitotic hyper-phosphorylation of hMps1, in vitro kinase assays show that Cdk1, MAPK, Plk1 and hMps1 itself can directly phosphorylate hMps1. Although Aurora B poorly phosphorylates hMps1 in vitro, it positively regulates the localization of Mps1 to kinetochores in vivo. Most importantly, quantitative mass spectrometry analysis demonstrates that at least 12 sites within hMps1 can be attributed to autophosphorylation. Remarkably, these hMps1 autophosphorylation sites closely resemble the consensus motif of Plk1, demonstrating that these two mitotic kinases share a similar substrate consensus.

CONCLUSIONS/SIGNIFICANCE

hMps1 kinase is regulated by Aurora B kinase and its autophosphorylation. Analysis on hMps1 autophosphorylation sites demonstrates that hMps1 has a substrate preference similar to Plk1 kinase.

Transcriptional regulation via TF-modifying enzymes: an integrative model-based analysis

Transcription factor activity is largely regulated through post-translational modification. Here, we report the first integrative model of transcription that includes both interactions between transcription factors and promoters, and between transcription factors and modifying enzymes. Simulations indicate that our method is robust against noise. We validated our tool on a well-studied stress response network in yeast and on a STAT1-mediated regulatory network in human B cells. Our work represents a significant step toward a comprehensive model of gene transcription.

Biological signalling activity measurements using mass spectrometry

MS (mass spectrometry) techniques are rapidly evolving to high levels of performance and robustness. This is allowing the application of these methods to the interrogation of signalling networks with unprecedented depth and accuracy. In the present review we discuss how MS-based multiplex quantification of kinase activities and phosphoproteomics provide complementary means to assess biological signalling activity. In addition, we discuss how a wider application of these analytical concepts to quantify kinase signalling will result in a more comprehensive understanding of normal and disease biology at the system level.

Measuring the evolutionary rewiring of biological networks

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or "rewire", at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of "commonplace" networks such as family trees, co-authorships and linux-kernel function dependencies.

Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast

The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery-and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.

Regulation of yeast Yak1 kinase by PKA and autophosphorylation-dependent 14-3-3 binding

Yak1 is a member of an evolutionarily conserved family of Ser/Thr protein kinases known as dual-specificity Tyr phosphorylation-regulated kinases (DYRKs). Yak1 was originally identified as a growth antagonist, which functions downstream of Ras/PKA signalling pathway. It has been known that Yak1 is phosphorylated by PKA in vitro and is translocated to the nucleus upon nutrient deprivation. However, the regulatory mechanisms for Yak1 activity and localization are largely unknown. In the present study, we investigated the role of PKA and Bmh1, a yeast 14-3-3 protein, in regulation of Yak1. We demonstrate that PKA-dependent phosphorylation of Yak1 on Ser295 and two minor sites inhibits nuclear localization of Yak1. We also show that intramolecular autophosphorylation on at least four Ser/Thr residues in the non-catalytic N-terminal domain is required for full kinase activity of Yak1. The most potent autophosphorylation site, Thr335, plays an essential role for Bmh1 binding in collaboration with a yet unidentified second binding site in the N-terminal domain. Bmh1 binding decreases the catalytic activity of Yak1 without affecting its subcellular localization. Since the binding of 14-3-3 proteins to Yak1 coincides with PKA activity, such regulatory mechanisms might allow cytoplasmic retention of an inactive form of Yak1 under high glucose conditions.

Moving from transcriptional to phospho-evolution: generalizing regulatory evolution?

Much of biological diversity is thought to arise from changes in regulatory networks. Although the role of transcriptional regulation has been well established, the contribution to evolution of changes at other levels of regulation has yet to be addressed. Using examples from the literature and recent studies on the evolution of protein phosphorylation, we argue that protein regulatory networks also play a prime role in generating diversity within and between species. Because there are several analogies between the regulation of protein functions by kinases and the regulation of gene expression by transcription factors, the principles that guide transcriptional regulatory evolution can also be explored in kinase-substrate networks. These comparisons will allow us to generalize existing models of evolution across the complex layers of the cell's regulatory links.

Structural bases of PAS domain-regulated kinase (PASK) activation in the absence of activation loop phosphorylation

Per-Arnt-Sim (PAS) domain-containing protein kinase (PASK) is an evolutionary conserved protein kinase that coordinates cellular metabolism with metabolic demand in yeast and mammals. The molecular mechanisms underlying PASK regulation, however, remain unknown. Herein, we describe a crystal structure of the kinase domain of human PASK, which provides insights into the regulatory mechanisms governing catalysis. We show that the kinase domain adopts an active conformation and has catalytic activity in vivo and in vitro in the absence of activation loop phosphorylation. Using site-directed mutagenesis and structural comparison with active and inactive kinases, we identified several key structural features in PASK that enable activation loop phosphorylation-independent activity. Finally, we used combinatorial peptide library screening to determine that PASK prefers basic residues at the P-3 and P-5 positions in substrate peptides. Our results describe the key features of the PASK structure and how those features are important for PASK activity and substrate selection.

Computational prediction and experimental verification of new MAP kinase docking sites and substrates including Gli transcription factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new 'D-site' class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates.

Yeast proteomics and protein microarrays

Our understanding of biological processes as well as human diseases has improved greatly thanks to studies on model organisms such as yeast. The power of scientific approaches with yeast lies in its relatively simple genome, its facile classical and molecular genetics, as well as the evolutionary conservation of many basic biological mechanisms. However, even in this simple model organism, systems biology studies, especially proteomic studies had been an intimidating task. During the past decade, powerful high-throughput technologies in proteomic research have been developed for yeast including protein microarray technology. The protein microarray technology allows the interrogation of protein–protein, protein–DNA, protein–small molecule interaction networks as well as post-translational modification networks in a large-scale, high-throughput manner. With this technology, many groundbreaking findings have been established in studies with the budding yeast Saccharomyces cerevisiae, most of which could have been unachievable with traditional approaches. Discovery of these networks has profound impact on explicating biological processes with a proteomic point of view, which may lead to a better understanding of normal biological phenomena as well as various human diseases.

Characterization of substrates that have a differential effect on Saccharomyces cerevisiae protein kinase A holoenzyme activation

The specificity in phosphorylation by kinases is determined by the molecular recognition of the peptide target sequence. In Saccharomyces cerevisiae, the protein kinase A (PKA) specificity determinants are less studied than in mammalian PKA. The catalytic turnover numbers of the catalytic subunits isoforms Tpk1 and Tpk2 were determined, and both enzymes are shown to have the same value of 3 s(-1). We analyze the substrate behavior and sequence determinants around the phosphorylation site of three protein substrates, Pyk1, Pyk2, and Nth1. Nth1 protein is a better substrate than Pyk1 protein, and both are phosphorylated by either Tpk1 or Tpk2. Both enzymes also have the same selectivity toward the protein substrates and the peptides derived from them. The three substrates contain one or more Arg-Arg-X-Ser consensus motif, but not all of them are phosphorylated. The determinants for specificity were studied using the peptide arrays. Acidic residues in the position P+1 or in the N-terminal flank are deleterious, and positive residues present beyond P-2 and P-3 favor the catalytic reaction. A bulky hydrophobic residue in position P+1 is not critical. The best substrate has in position P+4 an acidic residue, equivalent to the one in the inhibitory sequence of Bcy1, the yeast regulatory subunit of PKA. The substrate effect in the holoenzyme activation was analyzed, and we demonstrate that peptides and protein substrates sensitized the holoenzyme to activation by cAMP in different degrees, depending on their sequences. The results also suggest that protein substrates are better co-activators than peptide substrates.

Analysis of serine-threonine kinase specificity using arrayed positional scanning peptide libraries

Protein kinases vary substantially in their consensus phosphorylation motifs, the residues that are either preferred or deselected by the kinase at specific positions surrounding the phosphorylation site. The protocol described here is used to rapidly determine phosphorylation motifs for serine-threonine kinases. The procedure involves screening an arrayed combinatorial peptide library consisting of 198 biotinylated substrates. Peptides are phosphorylated by the kinase of interest in the presence of radiolabeled ATP and then captured on streptavidin membrane. The membrane is subsequently washed, dried, and exposed to a phosphor screen to visualize and quantify incorporation of radiolabel into the peptides. The phosphorylation motif is thereby derived from the relative extent of phosphorylation of each peptide in the array.

MOTIPS: automated motif analysis for predicting targets of modular protein domains

Background

Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy.

Results

We developed an efficient search algorithm to scan the target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder. The integration is performed using naïve Bayes and a training set of validated experiments.

Conclusions

By integrating a variety of biologically relevant features to predict domain targets, we demonstrated a notably improved prediction of modular protein domain targets. Combined with emerging high-resolution data of domain specificities, we believe that our approach can assist in the reconstruction of many signaling pathways.