Mapping specificity determinants for protein-protein association using protein fusions and random peptide libraries

Crystal Structures of Plk1 Polo-Box Domain Bound to the Human Papillomavirus Minor Capsid Protein L2-Derived Peptide

Human papillomaviruses (HPVs) can increase the proliferation of infected cells during HPV-driven abnormalities, such as cervical cancer or benign warts. To date, more than 200 HPV genotypes have been identified, most of which are classified into three major genera: Alphapapillomavirus, Betapapillomavirus, and Gammapapillomavirus. HPV genomes commonly encode two structural (L1 and L2) and seven functional (E1, E2, E4-E7, and E8) proteins. L2, the minor structural protein of HPVs, not only serves as a viral capsid component but also interacts with various human proteins during viral infection. A recent report revealed that L2 of HPV16 recruits polo-like kinase 1 (Plk1), a master regulator of eukaryotic mitosis and cell cycle progression, for the delivery of viral DNA to mitotic chromatin during HPV16 infection. In this study, we verified the direct and potent interactions between the polo-box domain (PBD) of Plk1 and PBD-binding motif (S-S-pT-P)-containing phosphopeptides derived from L2 of HPV16/HPV18 (high-risk alphapapillomaviruses), HPV5b (low-risk betapapillomavirus), and HPV4 (low-risk gammapapillomavirus). Subsequent structural determination of the Plk1 PBD bound to the HPV18 or HPV4 L2-derived phosphopeptide demonstrated that they interact with each other in a canonical manner, in which electrostatic interactions and hydrogen bonds play key roles in sustaining the complex. Therefore, our structural and biochemical data imply that Plk1 is a broad binding target of L2 of various HPV genotypes belonging to the Alpha-, Beta-, and Gammapapillomavirus genera.

Quest for the Crypto-phosphoproteome

Protein phosphorylation is one of the most studied post-translational modifications (PTMs). Despite the remarkable advances in phosphoproteomics, a chemically less-stable subset of the phosphosites, which we call the crypto-phosphoproteome, has remained underexplored due to technological challenges. In this Viewpoint, we briefly summarize the current understanding of these elusive protein phosphorylations and identify the missing pieces for future studies.

GPS-PBS: A Deep Learning Framework to Predict Phosphorylation Sites that Specifically Interact with Phosphoprotein-Binding Domains

Protein phosphorylation is essential for regulating cellular activities by modifying substrates at specific residues, which frequently interact with proteins containing phosphoprotein-binding domains (PPBDs) to propagate the phosphorylation signaling into downstream pathways. Although massive phosphorylation sites (p-sites) have been reported, most of their interacting PPBDs are unknown. Here, we collected 4458 known PPBD-specific binding p-sites (PBSs), considerably improved our previously developed group-based prediction system (GPS) algorithm, and implemented a deep learning plus transfer learning strategy for model training. Then, we developed a new online service named GPS-PBS, which can hierarchically predict PBSs of 122 single PPBD clusters belonging to two groups and 16 families. By comparison, GPS-PBS achieved a highly competitive accuracy against other existing tools. Using GPS-PBS, we predicted 371,018 mammalian p-sites that potentially interact with at least one PPBD, and revealed that various PPBD-containing proteins (PPCPs) and protein kinases (PKs) can simultaneously regulate the same p-sites to orchestrate important pathways, such as the PI3K-Akt signaling pathway. Taken together, we anticipate GPS-PBS can be a great help for further dissecting phosphorylation signaling networks.

Proline rich motifs as drug targets in immune mediated disorders

The current version of the human immunome network consists of nearly 1400 interactions involving approximately 600 proteins. Intermolecular interactions mediated by proline-rich motifs (PRMs) are observed in many facets of the immune response. The proline-rich regions are known to preferentially adopt a polyproline type II helical conformation, an extended structure that facilitates transient intermolecular interactions such as signal transduction, antigen recognition, cell-cell communication and cytoskeletal organization. The propensity of both the side chain and the backbone carbonyls of the polyproline type II helix to participate in the interface interaction makes it an excellent recognition motif. An advantage of such distinct chemical features is that the interactions can be discriminatory even in the absence of high affinities. Indeed, the immune response is mediated by well-orchestrated low-affinity short-duration intermolecular interactions. The proline-rich regions are predominantly localized in the solvent-exposed regions such as the loops, intrinsically disordered regions, or between domains that constitute the intermolecular interface. Peptide mimics of the PRM have been suggested as potential antagonists of intermolecular interactions. In this paper, we discuss novel PRM-mediated interactions in the human immunome that potentially serve as attractive targets for immunomodulation and drug development for inflammatory and autoimmune pathologies.

Proteomic screening method for phosphopeptide motif binding proteins using peptide libraries

Phosphopeptide binding domains mediate the directed and localized assembly of protein complexes essential to intracellular kinase signaling. To identify phosphopeptide binding proteins, we developed a proteomic screening method using immobilized partially degenerate phosphopeptide mixtures combined with SILAC and microcapillary LC-MS/MS. The method was used to identify proteins that specifically bound to phosphorylated peptide library affinity matrices, including pTyr, and the motifs pSer/pThr-Pro, pSer/pThr-X-X-X-pSer/pThr, pSer/pThr-Glu/Asp, or pSer/pThr-pSer/pThr in degenerate sequence contexts. Heavy and light SILAC lysates were applied to columns containing these phosphorylated and nonphosphorylated (control) peptide libraries respectively, and bound proteins were eluted, combined, digested, and analyzed by LC-MS/MS using a hybrid quadrupole-TOF mass spectrometer. Heavy/light peptide ion ratios were calculated, and peptides that yielded ratios greater than ∼3:1 were considered as being from potential phosphopeptide binding proteins since this ratio represents the lowest ratio from a known positive control. Many of those identified were known phosphopeptide-binding proteins, including the SH2 domain containing p85 subunit of PI3K bound to pTyr, 14-3-3 bound to pSer/pThr-Asp/Glu, polo-box domain containing PLK1 and Pin1 bound to pSer/pThr-Pro, and pyruvate kinase M2 binding to pTyr. Approximately half of the hits identified by the peptide library screens were novel. Protein domain enrichment analysis revealed that most pTyr hits contain SH2 domains, as expected, and to a lesser extent SH3, C1, STAT, Tyr phosphatase, Pkinase, C2, and PH domains; however, pSer/pThr motifs did not reveal enriched domains across hits.

Partitioning of minimotifs based on function with improved prediction accuracy

Background

Minimotifs are short contiguous peptide sequences in proteins that are known to have a function in at least one other protein. One of the principal limitations in minimotif prediction is that false positives limit the usefulness of this approach. As a step toward resolving this problem we have built, implemented, and tested a new data-driven algorithm that reduces false-positive predictions.

Methodology/Principal Findings

Certain domains and minimotifs are known to be strongly associated with a known cellular process or molecular function. Therefore, we hypothesized that by restricting minimotif predictions to those where the minimotif containing protein and target protein have a related cellular or molecular function, the prediction is more likely to be accurate. This filter was implemented in Minimotif Miner using function annotations from the Gene Ontology. We have also combined two filters that are based on entirely different principles and this combined filter has a better predictability than the individual components.

Conclusions/Significance

Testing these functional filters on known and random minimotifs has revealed that they are capable of separating true motifs from false positives. In particular, for the cellular function filter, the percentage of known minimotifs that are not removed by the filter is ∼4.6 times that of random minimotifs. For the molecular function filter this ratio is ∼2.9. These results, together with the comparison with the published frequency score filter, strongly suggest that the new filters differentiate true motifs from random background with good confidence. A combination of the function filters and the frequency score filter performs better than these two individual filters.

Utilizing peptide SPOT arrays to identify protein interactions

SPOT arrays consist of synthesized peptides 12- to 18-amino acids long, with overlapping sequences that cover the entire sequence of a protein, covalently linked to a solid support. This unit describes how to construct peptide SPOT arrays, biotinylate recombinant proteins, and conduct overlay assays to identify binding interactions. In addition, directions describing how to analyze results to determine single amino acid binding contributions are included. The two techniques in this unit describe how to scan protein sequences to find binding motifs and how to conduct site-directed mutagenesis studies.

Domains mediate protein-protein interactions and nucleate protein assemblies

Cell physiology is governed by an intricate mesh of physical and functional links among proteins, nucleic acids and other metabolites. The recent information flood coming from large-scale genomic and proteomic approaches allows us to foresee the possibility of compiling an exhaustive list of the molecules present within a cell, enriched with quantitative information on concentration and cellular localization. Moreover, several high-throughput experimental and computational techniques have been devised to map all the protein interactions occurring in a living cell. So far, such maps have been drawn as graphs where nodes represent proteins and edges represent interactions. However, this representation does not take into account the intrinsically modular nature of proteins and thus fails in providing an effective description of the determinants of binding. Since proteins are composed of domains that often confer on proteins their binding capabilities, a more informative description of the interaction network would detail, for each pair of interacting proteins in the network, which domains mediate the binding. Understanding how protein domains combine to mediate protein interactions would allow one to add important features to the protein interaction network, making it possible to discriminate between simultaneously occurring and mutually exclusive interactions. This objective can be achieved by experimentally characterizing domain recognition specificity or by analyzing the frequency of co-occurring domains in proteins that do interact. Such approaches allow gaining insights on the topology of complexes with unknown three-dimensional structure, thus opening the prospect of adopting a more rational strategy in developing drugs designed to selectively target specific protein interactions.

Structure-templated predictions of novel protein interactions from sequence information

The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.

Many functions performed within a living cell are mediated by specific interactions between proteins. Precise geometric and chemical matches between segments of the protein structures facilitate those interactions. Such binding surfaces are often evolutionarily conserved elements of protein structures known as conserved domains that recognize specific binding elements on the interacting proteins. Binding domains and their corresponding interacting profiles constitute basic interacting modules that are replicated in multiple protein pairs, where they mediate similar interactions. Although many conserved domains are identified, only a handful have known, well-characterized binding elements. This paper describes a computational method that aims to elucidate the binding specificity of many domains. The utility of the derived binding specificity is demonstrated by predicting new interactions between yeast proteins. The predictions are based solely on sequence information by identifying the conserved domains and their corresponding binding sequences. A number of the predicted interactions were confirmed experimentally, demonstrating the feasibility of this approach.

Using peptide arrays to define nuclear carrier binding sites on nucleoporins

In the peptide SPOT array technique, an array of different peptides are synthesized on, and covalently linked to, cellulose membranes. In one usage of this technique, these peptides are screened in an overlay assay to determine which short sequence(s) contains a binding site for an interacting protein. By preparing overlapping peptides that cover the entire sequence of a protein, all of the binding domains on the protein for a second protein can be identified. We have utilized the peptide SPOT array technique to identify the short amino acid sequences within nuclear pore complex proteins (also known as nucleoporins or Nups) that bind the nuclear carrier importin-beta. Crystallization studies by others have indicated that nuclear carriers such as importin-beta bind to phenylalanine-glycine (FG) repeats present in numerous copies in the sequences of a family of nucleoporins. Consistent with this, we found that most (but not all) of the Nup binding sites for importin-beta identified by this technique contain Fx, FG, FxFG, FxFx, or GLFG sequences, although not all such sequences bound importin-beta. Peptide SPOT array substitution studies confirmed a crucial role for the phenylalanine in FG repeats and identified a lysine residue flanking some repeats that is crucial for importin-beta binding to those repeats. In addition to these expected binding sequences for importin-beta, we found multiple instances of a peptide lacking a canonical FG repeat that strongly bound importin-beta, indicating that additional Nup sequences may form binding sites for importin-beta.

"Bits" and pieces

Many protein-protein interactions involved in signal transduction occur through the interaction of modular protein domains in one molecule with short linear sequences of amino acids ("motifs") in another. Although protein domains are recognized by a variety of computational tools, bioinformatic approaches alone have not been successful in identifying the short sequence motifs to which domains bind. A new approach, applying motif-determining algorithms to smaller subproteomic collections of proteins that are already known to associate with each other in high-throughput protein-protein interaction screens, now appears to be capable of capturing a reasonably large number of low-affinity core motif sequences. Application of this approach to the genomes of yeast, fruit flies, nematodes, and humans has doubled the number of known or suspected protein-protein interaction motifs.

The affinity concept in bioseparation: Evolving paradigms and expanding range of applications

The meaning of the word affinity in the context of protein separation has undergone evolutionary changes over the years. The exploitation of molecular recognition phenomenon is no longer limited to affinity chromatography modes. Affinity based separations today include precipitation, membrane based purification and two-phase/three-phase extractions. Apart from the affinity ligands, which have biological relationship (in vivo) with the target protein, a variety of other ligands are now used in the affinity based separations. These include dyes, chelated metal ions, peptides obtained by phage display technology, combinatorial synthesis, ribosome display methods and by systematic evolution of ligands by exponential enrichment (SELEX). Molecular modeling techniques have also facilitated the designing of biomimetic ligands. Fusion proteins obtained by recombinatorial methods have emerged as a powerful approach in bioseparation. Overexpression in E. coli often result in inactive and insoluble inclusion bodies. A number of interesting approaches are used for simultaneous refolding and purification in such cases. Proteomics also needs affinity chromatography to reduce the complexity of the system before analysis by electrophoresis and mass spectrometry are made. At industrial level, validation, biosafety and process hygiene are also important aspects. This overview looks at these evolving paradigms and various strategies which utilize affinity phenomenon for protein separations.

Targeting polo-like kinase 1 for cancer therapy

Human polo-like kinase 1 (PLK1) is essential during mitosis and in the maintenance of genomic stability. PLK1 is overexpressed in human tumours and has prognostic potential in cancer, indicating its involvement in carcinogenesis and its potential as a therapeutic target. The use of different PLK1 inhibitors has increased our knowledge of mitotic regulation and allowed us to assess their ability to suppress tumour growth in vivo. We address the structural features of the kinase domain and the unique polo-box domain of PLK1 that are most suited for drug development and discuss our current understanding of the therapeutic potential of PLK1.

MDC1 directly binds phosphorylated histone H2AX to regulate cellular responses to DNA double-strand breaks

Histone variant H2AX phosphorylation in response to DNA damage is the major signal for recruitment of DNA-damage-response proteins to regions of damaged chromatin. Loss of H2AX causes radiosensitivity, genome instability, and DNA double-strand-break repair defects, yet the mechanisms underlying these phenotypes remain obscure. Here, we demonstrate that mammalian MDC1/NFBD1 directly binds to phospho-H2AX (gammaH2AX) by specifically interacting with the phosphoepitope at the gammaH2AX carboxyl terminus. Moreover, through a combination of biochemical, cell-biological, and X-ray crystallographic approaches, we reveal the molecular details of the MDC1/NFBD1-gammaH2AX complex. These data provide compelling evidence that the MDC1/NFBD1 BRCT repeat domain is the major mediator of gammaH2AX recognition following DNA damage. We further show that MDC1/NFBD1-gammaH2AX complex formation regulates H2AX phosphorylation and is required for normal radioresistance and efficient accumulation of DNA-damage-response proteins on damaged chromatin. Thus, binding of MDC1/NFBD1 to gammaH2AX plays a central role in the mammalian response to DNA damage.

Peptide phage display for probing GST-protein interactions

Phage display is a powerful strategy for identifying protein-peptide interactions. Glutathione transferases (GSTs) play prominent roles in the cellular protection against oxidative stress by catalyzing detoxication reactions. In addition, GSTs seem to act in signaling pathways by means of interaction with other macromolecules such as protein kinases. This chapter describes how the technique of peptide phage display can be used to identify possible partners in GST-protein complexes.

Methods to reveal domain networks

The development and application of high-throughput technology to study protein interactions has led to the construction of complex interaction maps, the correct interpretation of which is crucial to the identification of targets for drug development. Here we propose that a more informative description of protein interaction networks can be achieved by considering explicitly the modular nature of proteins. In this representation, proteins are drawn as covalently linked modular domains binding to their target sites in partner proteins. Families of conserved modules that bind to relatively short peptides mediate a large fraction of the non-covalent interactions linking different proteins in the network. As these interactions are often involved in the propagation of signal transduction, determining the recognition specificity of each domain family member is an essential step toward a functional description of the global interactome.

Polo-like kinase 1 creates the tension-sensing 3F3/2 phosphoepitope and modulates the association of spindle-checkpoint proteins at kinetochores

BACKGROUND

In mitosis, a mechanochemical system recognizes tension that is generated by bipolar microtubule attachment to sister kinetochores. This is translated into multiple outputs including the stabilization of microtubule attachments, changes in kinetochore protein dynamics, and the silencing of the spindle checkpoint. How kinetochores sense tension and translate this into various signals represent critical unanswered questions. The kinetochores of chromosomes not under tension are specifically phosphorylated at an epitope recognized by the 3F3/2 monoclonal antibody. Determining the kinase that generates the 3F3/2 phosphoepitope at kinetochores should reveal an important component of this system that regulates mitotic progression.

RESULTS

We demonstrate that Polo-like kinase 1 (Plk1) creates the 3F3/2 phosphoepitope on mitotic kinetochores. In a permeabilized in vitro cell system, the depletion of Xenopus Plk1 from M phase extract leads to the loss of 3F3/2 kinase activity. Purified recombinant Plk1 is sufficient to generate the 3F3/2 phosphoepitope in this system. Using siRNA, we show that the reduction of Plk1 protein levels significantly diminishes 3F3/2 phosphoepitope expression at kinetochores. The consensus phosphorylation sites of Plk1 show strong similarity to the 3F3/2 phosphoepitope sequence determined by phosphopeptide mapping. The inhibition of Plk1 by siRNA alters the normal kinetochore association of Mad2, Cenp-E, Hec1/Ndc80, Spc24, and Cdc20 and induces a spindle-checkpoint-mediated mitotic arrest.

CONCLUSIONS

Plk1 generates the 3F3/2 phosphoepitope at kinetochores that are not under tension and contributes to the normal kinetochore association of several key proteins important in checkpoint signaling. Mechanical tension regulates Plk1 accumulation at kinetochores and possibly its kinase activity.

The use of in vitro peptide-library screens in the analysis of phosphoserine/threonine-binding domain structure and function

Phosphoserine/threonine-binding domains integrate intracellular signal transduction events by forming multiprotein complexes with substrates of protein serine/threonine kinases. These phosphorylation-dependent molecular recognition events are responsible for coordinating the precise temporal and spatial response of cells to a wide range of stimuli, particularly those involved in cell cycle control and the response to DNA damage. The known families of phosphoserine/threonine-binding modules include 14-3-3 proteins, WW domains, FHA domains, WD40 repeats, and the Polo-box domains of Polo-like kinases. Peptide-library experiments reveal the optimal sequence motifs recognized by these domains, and facilitate high-resolution structural studies elucidating the mechanisms of phospho-dependent binding and the molecular basis for domain function within intricate signaling networks. Information emerging from these studies is critical for the design of novel experimental and therapeutic tools aimed at altering signal transduction cascades in normal and diseased cells.

BRCT repeats as phosphopeptide-binding modules involved in protein targeting

We used a proteomic approach to identify phosphopeptide-binding modules mediating signal transduction events in the DNA damage response pathway. Using a library of partially degenerate phosphopeptides, we identified tandem BRCT (BRCA1 carboxyl-terminal) domains in PTIP (Pax transactivation domain-interacting protein) and in BRCA1 as phosphoserine- or phosphothreonine-specific binding modules that recognize substrates phosphorylated by the kinases ATM (ataxia telangiectasia-mutated) and ATR (ataxia telangiectasia- and RAD3-related) in response to gamma-irradiation. PTIP tandem BRCT domains are responsible for phosphorylation-dependent protein localization into 53BP1- and phospho-H2AX (gamma-H2AX)-containing nuclear foci, a marker of DNA damage. These findings provide a molecular basis for BRCT domain function in the DNA damage response and may help to explain why the BRCA1 BRCT domain mutation Met1775 --> Arg, which fails to bind phosphopeptides, predisposes women to breast and ovarian cancer.

The molecular basis for phosphodependent substrate targeting and regulation of Plks by the Polo-box domain

Polo-like kinases (Plks) perform crucial functions in cell-cycle progression and multiple stages of mitosis. Plks are characterized by a C-terminal noncatalytic region containing two tandem Polo boxes, termed the Polo-box domain (PBD), which has recently been implicated in phosphodependent substrate targeting. We show that the PBDs of human, Xenopus, and yeast Plks all recognize similar phosphoserine/threonine-containing motifs. The 1.9 A X-ray structure of a human Plk1 PBD-phosphopeptide complex shows that the Polo boxes each comprise beta6alpha structures that associate to form a 12-stranded beta sandwich domain. The phosphopeptide binds along a conserved, positively charged cleft located at the edge of the Polo-box interface. Mutations that specifically disrupt phosphodependent interactions abolish cell-cycle-dependent localization and provide compelling phenotypic evidence that PBD-phospholigand binding is necessary for proper mitotic progression. In addition, phosphopeptide binding to the PBD stimulates kinase activity in full-length Plk1, suggesting a conformational switching mechanism for Plk regulation and a dual functionality for the PBD.

Scansite 2.0: Proteome-wide prediction of cell signaling interactions using short sequence motifs

Scansite identifies short protein sequence motifs that are recognized by modular signaling domains, phosphorylated by protein Ser/Thr- or Tyr-kinases or mediate specific interactions with protein or phospholipid ligands. Each sequence motif is represented as a position-specific scoring matrix (PSSM) based on results from oriented peptide library and phage display experiments. Predicted domain-motif interactions from Scansite can be sequentially combined, allowing segments of biological pathways to be constructed in silico. The current release of Scansite, version 2.0, includes 62 motifs characterizing the binding and/or substrate specificities of many families of Ser/Thr- or Tyr-kinases, SH2, SH3, PDZ, 14-3-3 and PTB domains, together with signature motifs for PtdIns(3,4,5)P(3)-specific PH domains. Scansite 2.0 contains significant improvements to its original interface, including a number of new generalized user features and significantly enhanced performance. Searches of all SWISS-PROT, TrEMBL, Genpept and Ensembl protein database entries are now possible with run times reduced by approximately 60% when compared with Scansite version 1.0. Scansite 2.0 allows restricted searching of species-specific proteins, as well as isoelectric point and molecular weight sorting to facilitate comparison of predictions with results from two-dimensional gel electrophoresis experiments. Support for user-defined motifs has been increased, allowing easier input of user-defined matrices and permitting user-defined motifs to be combined with pre-compiled Scansite motifs for dual motif searching. In addition, a new series of Sequence Match programs for non-quantitative user-defined motifs has been implemented. Scansite is available via the World Wide Web at http://scansite.mit.edu.

Proteomic screen finds pSer/pThr-binding domain localizing Plk1 to mitotic substrates

We have developed a proteomic approach for identifying phosphopeptide binding domains that modulate kinase-dependent signaling pathways. An immobilized library of partially degenerate phosphopeptides biased toward a particular protein kinase phosphorylation motif is used to isolate phospho-binding domains that bind to proteins phosphorylated by that kinase. Applying this approach to cyclin-dependent kinases (Cdks), we identified the polo-box domain (PBD) of the mitotic kinase polo-like kinase 1 (Plk1) as a specific phosphoserine (pSer) or phosphothreonine (pThr) binding domain and determined its optimal binding motif. This motif is present in known Plk1 substrates such as Cdc25, and an optimal phosphopeptide containing the motif disrupted PBD-substrate binding and localization of the PBD to centrosomes. This finding reveals how Plk1 can localize to specific sites within cells in response to Cdk phosphorylation at those sites and provides a structural mechanism for targeting the Plk1 kinase domain to its substrates.

Identification of the tuberous sclerosis complex-2 tumor suppressor gene product tuberin as a target of the phosphoinositide 3-kinase/akt pathway

The S/T-protein kinases activated by phosphoinositide 3-kinase (PI3K) regulate a myriad of cellular processes. Here, we show that an approach using a combination of biochemistry and bioinformatics can identify substrates of these kinases. This approach identifies the tuberous sclerosis complex-2 gene product, tuberin, as a potential target of Akt/PKB. We demonstrate that, upon activation of PI3K, tuberin is phosphorylated on consensus recognition sites for PI3K-dependent S/T kinases. Moreover, Akt/PKB can phosphorylate tuberin in vitro and in vivo. We also show that S939 and T1462 of tuberin are PI3K-regulated phosphorylation sites and that T1462 is constitutively phosphorylated in PTEN(-/-) tumor-derived cell lines. Finally, we find that a tuberin mutant lacking the major PI3K-dependent phosphorylation sites can block the activation of S6K1, suggesting a means by which the PI3K-Akt pathway regulates S6K1 activity.

Structural and functional versatility of the FHA domain in DNA-damage signaling by the tumor suppressor kinase Chk2

The Chk2 Ser/Thr kinase plays crucial, evolutionarily conserved roles in cellular responses to DNA damage. Identification of two pro-oncogenic mutations within the Chk2 FHA domain has highlighted its importance for Chk2 function in checkpoint activation. The X-ray structure of the Chk2 FHA domain in complex with an in vitro selected phosphopeptide motif reveals the determinants of binding specificity and shows that both mutations are remote from the peptide binding site. We show that the Chk2 FHA domain mediates ATM-dependent Chk2 phosphorylation and targeting of Chk2 to in vivo binding partners such as BRCA1 through either or both of two structurally distinct mechanisms. Although phospho-dependent binding is important for Chk2 activity, previously uncharacterized phospho-independent FHA domain interactions appear to be the primary target of oncogenic lesions.

Phosphotyrosine-binding domains in signal transduction

Protein phosphorylation provides molecular control of complex physiological events within cells. In many cases, phosphorylation on specific amino acids directly controls the assembly of multi-protein complexes by recruiting phospho-specific binding modules. Here, the function, structure, and cell biology of phosphotyrosine-binding domains is discussed.

A motif-based profile scanning approach for genome-wide prediction of signaling pathways

The rapid increase in genomic information requires new techniques to infer protein function and predict protein-protein interactions. Bioinformatics identifies modular signaling domains within protein sequences with a high degree of accuracy. In contrast, little success has been achieved in predicting short linear sequence motifs within proteins targeted by these domains to form complex signaling networks. Here we describe a peptide library-based searching algorithm, accessible over the World Wide Web, that identifies sequence motifs likely to bind to specific protein domains such as 14-3-3, SH2, and SH3 domains, or likely to be phosphorylated by specific protein kinases such as Src and AKT. Predictions from database searches for proteins containing motifs matching two different domains in a common signaling pathway provides a much higher success rate. This technology facilitates prediction of cell signaling networks within proteomes, and could aid in the identification of drug targets for the treatment of human diseases.