Exploiting holistic approaches to model specificity in protein phosphorylation

Neuroproteomic mapping of kinases and their substrates downstream of acetylcholine: finding and implications

INTRODUCTION

Since the emergence of the cholinergic hypothesis of Alzheimer's disease (AD), acetylcholine has been viewed as a mediator of learning and memory. Donepezil improves AD-associated learning deficits and memory loss by recovering brain acetylcholine levels. However, it is associated with side effects due to global activation of acetylcholine receptors. Muscarinic acetylcholine receptor M1 (M1R), a key mediator of learning and memory, has been an alternative target. The importance of targeting a specific pathway downstream of M1R has recently been recognized. Elucidating signaling pathways beyond M1R that lead to learning and memory holds important clues for AD therapeutic strategies.

AREAS COVERED

This review first summarizes the role of acetylcholine in aversive learning, one of the outputs used for preliminary AD drug screening. It then describes the phosphoproteomic approach focused on identifying acetylcholine intracellular signaling pathways leading to aversive learning. Finally, the intracellular mechanism of donepezil and its effect on learning and memory is discussed.

EXPERT OPINION

The elucidation of signaling pathways beyond M1R by phosphoproteomic approach offers a platform for understanding the intracellular mechanism of AD drugs and for developing AD therapeutic strategies. Clarifying the molecular mechanism that links the identified acetylcholine signaling to AD pathophysiology will advance the development of AD therapeutic strategies.

Protein Phosphorylation Dynamics: Unexplored Because of Current Methodological Limitations: Dynamics of Processive Phosphorylation

The study of intrinsic phosphorylation dynamics and kinetics in the context of complex protein architecture in vivo has been challenging: Method limitations have prevented significant advances in the understanding of the highly variable turnover of phosphate groups, synergy, and cooperativity between P-sites. However, over the last decade, powerful analytical technologies have been developed to determine the full catalog of the phosphoproteome for many species. The curated databases of phospho sites found by mass spectrometry analysis and the computationally predicted sites based on the linear sequence of kinase motifs are valuable tools. They allow investigation of the complexity of phosphorylation in vivo, albeit with strong discrepancies between different methods. A series of hypothetical scenarios on combinatorial processive phosphorylation is proposed that are likely unverifiable with current methodologies. These proposed a priori postulates could be considered as possible extensions of the known schemes of the activation/inhibition signaling process in vivo.

Multiple Site-Specific Phosphorylation of IDPs Monitored by NMR

In line with their high accessibility, disordered proteins are exquisite targets of kinases. Eukaryotic organisms use the so-called intrinsically disordered proteins (IDPs) or intrinsically disordered regions of proteins (IDRs) as molecular switches carrying intracellular information tuned by reversible phosphorylation schemes. Solvent-exposed serines and threonines are abundant in IDPs, and, consistently, kinases often modify disordered regions of proteins at multiple sites. In this context, nuclear magnetic resonance (NMR) spectroscopy provides quantitative, residue-specific information that permits mapping of phosphosites and monitoring of their individual kinetics. Hence, NMR monitoring emerges as an in vitro approach, complementary to mass-spectrometry or immuno-blotting, to characterize IDP phosphorylation comprehensively. Here, we describe in detail generic protocols for carrying out NMR monitoring of IDP phosphorylation, and we provide a number of practical insights that improve handiness and reproducibility of this method.

Challenges of the Human Proteome Project: 10-Year Experience of the Russian Consortium

This manuscript collects all the efforts of the Russian Consortium, bottlenecks revealed in the course of the C-HPP realization, and ways of their overcoming. One of the main bottlenecks in the C-HPP is the insufficient sensitivity of proteomic technologies, hampering the detection of low- and ultralow-copy number proteins forming the "dark part" of the human proteome. In the frame of MP-Challenge, to increase proteome coverage we suggest an experimental workflow based on a combination of shotgun technology and selected reaction monitoring with two-dimensional alkaline fractionation. Further, to detect proteins that cannot be identified by such technologies, nanotechnologies such as combined atomic force microscopy with molecular fishing and/or nanowire detection may be useful. These technologies provide a powerful tool for single molecule analysis, by analogy with nanopore sequencing during genome analysis. To systematically analyze the functional features of some proteins (CP50 Challenge), we created a mathematical model that predicts the number of proteins differing in amino acid sequence: proteoforms. According to our data, we should expect about 100 000 different proteoforms in the liver tissue and a little more in the HepG2 cell line. The variety of proteins forming the whole human proteome significantly exceeds these results due to post-translational modifications (PTMs). As PTMs determine the functional specificity of the protein, we propose using a combination of gene-centric transcriptome-proteomic analysis with preliminary fractionation by two-dimensional electrophoresis to identify chemically modified proteoforms. Despite the complexity of the proposed solutions, such integrative approaches could be fruitful for MP50 and CP50 Challenges in the framework of the C-HPP.

Large-scale Discovery of Substrates of the Human Kinome

Kinase networks are important for cellular signal transduction. Despite tremendous efforts to uncover these signaling pathways, huge numbers of uncharacterized phosphosites still remain in the human proteome. Because of the transient nature of kinase-substrate interactions in vivo, it is almost impossible to identify direct substrates. Here, we present a strategy for the rapid, accurate and high-throughput discovery of in vitro kinase substrates using quantitative proteomics. Using 385 purified kinases (354 wild-type protein kinases, 21 mutants and 10 lipid kinases), we identified a total of 175,574 potential direct kinase substrates. In addition, we identified novel kinase groups, such as one group containing 30 threonine-directed kinases and another containing 15 serine/threonine/tyrosine kinases. Surprisingly, we observed that the diversity of substrates for tyrosine kinases was much higher than that for serine-threonine kinases.

Kinome-wide identification of phosphorylation networks in eukaryotic proteomes

Motivation

Signaling and metabolic pathways are finely regulated by a network of protein phosphorylation events. Unraveling the nature of this intricate network, composed of kinases, target proteins and their interactions, is therefore of crucial importance. Although thousands of kinase-specific phosphorylations (KsP) have been annotated in model organisms their kinase-target network is far from being complete, with less studied organisms lagging behind.

Results

In this work, we achieved an automated and accurate identification of kinase domains, inferring the residues that most likely contribute to peptide specificity. We integrated this information with the target peptides of known human KsP to predict kinase-specific interactions in other eukaryotes through a deep neural network, outperforming similar methods. We analyzed the differential conservation of kinase specificity among eukaryotes revealing the high conservation of the specificity of tyrosine kinases. With this approach we discovered 1590 novel KsP of potential clinical relevance in the human proteome.

Availability and implementation

http://akid.bio.uniroma2.it.

Supplementary information

Supplementary data are available at Bioinformatics online.

[Application of molecular descriptors for recognition of phosphorylation sites in amino acid sequences]

Recognition of the phosphorylation sites in proteins is required for reconstruction of regulatory processes in living systems. This task is complicated because the phosphorylation motifs in amino acid sequences are considerably degenerated. To improve the prediction efficacy researchers often use additional descriptors, which should reflect physicochemical features of site-surrounding regions. We have evaluated the reasonability of this approach by applying molecular descriptors (MNA) for structural presentation of the peptide segments. Comparative testing was performed using the prognostic method PASS and two input data types: sets of the MNA descriptors represented peptides as chemical structures and amino acid sequences written using a one-letter code. Training sets were classified in accordance with the established types of the enzymes (protein kinases), modifying corresponding phosphorylation sites. The accuracy estimates obtained by prognosis validation for various classes of substrates were significantly different with both the letters and molecular descriptors. In case of the letter description, the prognosis accuracy demonstrated less dependence on the length of peptides in the training set, while in the case of structural descriptors the accuracy level was determined by the peptide size and descriptor characteristics (MNA levels). The maximal prognosis accuracy related to various kinase families was achieved at different sizes of molecular fragments covered by the MNA descriptors of corresponding levels. This obviously reflected structural differences in surroundings of phosphorylation sites modified by various protein kinases. The use of molecular descriptors provided the prognostic results comparable with the results obtained using traditional letter representation. The prognosis accuracy demonstrated less dependence on the method describing site-surrounding peptides at higher accuracy rates. Applying the MNA descriptors it is possible to achieve better accuracy in the cases when the letter description cannot provide acceptable accuracy.

Counteracting Protein Kinase Activity in the Heart: The Multiple Roles of Protein Phosphatases

Decades of cardiovascular research have shown that variable and flexible levels of protein phosphorylation are necessary to maintain cardiac function. A delicate balance between phosphorylated and dephosphorylated states of proteins is guaranteed by a complex interplay of protein kinases (PKs) and phosphatases. Serine/threonine phosphatases, in particular members of the protein phosphatase (PP) family govern dephosphorylation of the majority of these cardiac proteins. Recent findings have however shown that PPs do not only dephosphorylate previously phosphorylated proteins as a passive control mechanism but are capable to actively control PK activity via different direct and indirect signaling pathways. These control mechanisms can take place on (epi-)genetic, (post-)transcriptional, and (post-)translational levels. In addition PPs themselves are targets of a plethora of proteinaceous interaction partner regulating their endogenous activity, thus adding another level of complexity and feedback control toward this system. Finally, novel approaches are underway to achieve spatiotemporal pharmacologic control of PPs which in turn can be used to fine-tune misleaded PK activity in heart disease. Taken together, this review comprehensively summarizes the major aspects of PP-mediated PK regulation and discusses the subsequent consequences of deregulated PP activity for cardiovascular diseases in depth.

Kinase-interacting substrate screening is a novel method to identify kinase substrates

Protein kinases play pivotal roles in numerous cellular functions; however, the specific substrates of each protein kinase have not been fully elucidated. We have developed a novel method called kinase-interacting substrate screening (KISS). Using this method, 356 phosphorylation sites of 140 proteins were identified as candidate substrates for Rho-associated kinase (Rho-kinase/ROCK2), including known substrates. The KISS method was also applied to additional kinases, including PKA, MAPK1, CDK5, CaMK1, PAK7, PKN, LYN, and FYN, and a lot of candidate substrates and their phosphorylation sites were determined, most of which have not been reported previously. Among the candidate substrates for Rho-kinase, several functional clusters were identified, including the polarity-associated proteins, such as Scrib. We found that Scrib plays a crucial role in the regulation of subcellular contractility by assembling into a ternary complex with Rho-kinase and Shroom2 in a phosphorylation-dependent manner. We propose that the KISS method is a comprehensive and useful substrate screen for various kinases.

Predicting CK2 beta-dependent substrates using linear patterns

CK2 is a constitutively active Ser/Thr protein kinase deregulated in cancer and other pathologies, responsible for about the 20% of the human phosphoproteome. The holoenzyme is a complex composed of two catalytic (α or α´) and two regulatory (β) subunits, with individual subunits also coexisting in the cell. In the holoenzyme, CK2β is a substrate-dependent modulator of kinase activity. Therefore, a comprehensive characterization of CK2 cellular function should firstly address which substrates are phosphorylated exclusively when CK2β is present (class-III or beta-dependent substrates). However, current experimental constrains limit this classification to a few substrates. Here, we took advantage of motif-based prediction and designed four linear patterns for predicting class-III behavior in sets of experimentally determined CK2 substrates. Integrating high-throughput substrate prediction, functional classification and network analysis, our results suggest that beta-dependent phosphorylation might exert particular regulatory roles in viral infection and biological processes/pathways like apoptosis, DNA repair and RNA metabolism. It also pointed, that human beta-dependent substrates are mainly nuclear, a few of them shuttling between nuclear and cytoplasmic compartments.

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The designed linear patterns assist CK2 beta-dependent substrates prediction.

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A high-throughput prediction of CK2 beta-dependent substrates was performed in several organisms including human, mouse and rat.

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The functional classification indicated a role of CK2 beta-dependent regulation in viral infection, apoptosis, DNA repair and RNA metabolism.

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The functional classification indicated that human CK2 beta-dependent substrates are mainly nuclear with a number of them also found in cytoplasm.