RS domains contact the pre-mRNA throughout spliceosome assembly

SR proteins are essential metazoan splicing factors that contain an RNA-binding domain and an arginine/serine-rich domain that functions to promote assembly of the spliceosome. The prevailing model over the past several years suggests that the RS domains function as protein-interaction domains. However, two new papers from Green et al. demonstrate that these RS domains directly contact the pre-mRNA within the functional spliceosome. The sequential character of these contacts suggests that RS domain interactions with RNA promote spliceosome assembly.     

Continuous compact protein domains

The coefficient of compactness was recently introduced and used to locate domains in lysozyme and ribonuclease (Zehfus and Rose: Biochemistry 25:5759-5765, 1986). Nineteen additional proteins now have been analyzed by using this measure. Complete listings of compact units and plots showing their hierarchic organization are presented for all twenty-one proteins. Large compact units correspond well to protein domains; however, many smaller compact structures of equal or better compactness are also found. Since small compact units could represent subdomains or protein-folding intermediates, their structural composition is further examined.     

Docking interactions of the JNK scaffold protein WDR62

JNK (c-Jun N-terminal kinase) is part of a MAPK (mitogen-activated protein kinase) signalling cascade. Scaffold proteins simultaneously associate with various components of the MAPK signalling pathway and play a crucial role in signal transmission and MAPK regulation. WDR62 (WD repeat domain 62) is a JNK scaffold protein. Recessive mutations within WDR62 result in severe cerebral cortical malformation. In the present study we demonstrate the association of WDR62 with endogenous and overexpressed proteins of both JNK2 and the JNK2-activating kinase MKK7 (MAPK kinase 7). Association of WDR62 with JNK2 and MKK7 occurs via direct protein-protein interactions. We mapped the docking domain of WDR62 responsible for the association with JNK. WDR62 interacts with all JNK isoforms through a D domain motif located at the C-terminus. A WDR62 mutant lacking the putative JNK-binding domain fails to activate and recruit JNK to cellular granules. Furthermore, a synthetic peptide composed of the WDR62 docking domain inhibits JNK2 activity in vitro. WDR62 association with JNK2 requires both the JNK CD and ED domains, and the binding requisite is distinct from that of the previously described JNK2 association with JIP1 (JNK-interacting protein 1). Next, we characterized the association between WDR62 and MKK7. WDR62 associates directly with the MKK7β1 isoform independently of JNK binding, but fails to interact with MKK7α1. Furthermore, MKK7β1 recruits a protein phosphatase that dephosphorylates WDR62. Interestingly, a premature termination mutation in WDR62 that results in severe brain developmental defects does not abrogate WDR62 association with either JNK or MKK7. Therefore such mutations represent a loss of WDR62 function independent of JNK signalling.     

Docking of protein molecular surfaces with evolutionary trace analysis

We have developed a new method to predict protein- protein complexes based on the shape complementarity of the molecular surfaces, along with sequence conservation obtained by evolutionary trace (ET) analysis. The docking is achieved by optimization of an object function that evaluates the degree of shape complementarity weighted by the conservation of the interacting residues. The optimization is carried out using a genetic algorithm in combination with Monte Carlo sampling. We applied this method to CAPRI targets and evaluated the performance systematically. Consequently, our method could achieve native-like predictions in several cases. In addition, we have analyzed the feasibility of the ET method for docking simulations, and found that the conservation information was useful only in a limited category of proteins (signal related proteins and enzymes).     

Diversity in protein recognition by PTB domains

Phosphotyrosine-binding (PTB) domains were originally identified as modular domains that recognize phosphorylated Asn-Pro-Xxx-p Tyr-containing proteins. Recent binding and structural studies of PTB domain complexes with target peptides have revealed a number of deviations from the previously described mode of interaction, with respect to both the sequences of possible targets and their structures within the complexes. This diversity of recognition by PTB domains extends and strengthens our general understanding of modular binding domain recognition.     

Conserved structural determinants in three-fingered protein domains

The three-dimensional structures of some components of snake venoms forming so-called 'three-fingered protein' domains (TFPDs) are similar to those of the ectodomains of activin, bone morphogenetic protein and transforming growth factor-beta receptors, and to a variety of proteins encoded by the Ly6 and Plaur genes. The analysis of sequences of diverse snake toxins, various ectodomains of the receptors that bind activin and other cytokines, and numerous gene products encoded by the Ly6 and Plaur families of genes has revealed that they differ considerably from each other. The sequences of TFPDs may consist of up to six disulfide bonds, three of which have the same highly conserved topology. These three disulfide bridges and an asparagine residue in the C-terminal part of TFPDs are essential for the TFPD-like fold. Analyses of the three-dimensional structures of diverse TFPDs have revealed that the three highly conserved disulfides impose a major stabilizing contribution to the TFPD-like fold, in both TFPDs contained in some snake venoms and ectodomains of several cellular receptors, whereas the three remaining disulfide bonds impose specific geometrical constraints in the three fingers of some TFPDs.     

Sequence-based prediction of protein domains

Guessing the boundaries of structural domains has been an important and challenging problem in experimental and computational structural biology. Predictions were based on intuition, biochemical properties, statistics, sequence homology and other aspects of predicted protein structure. Here, we introduced CHOPnet, a de novo method that predicts structural domains in the absence of homology to known domains. Our method was based on neural networks and relied exclusively on information available for all proteins. Evaluating sustained performance through rigorous cross-validation on proteins of known structure, we correctly predicted the number of domains in 69% of all proteins. For 50% of the two-domain proteins the centre of the predicted boundary was closer than 20 residues to the boundary assigned from three-dimensional (3D) structures; this was about eight percentage points better than predictions by ‘equal split’. Our results appeared to compare favourably with those from previously published methods. CHOPnet may be useful to restrict the experimental testing of different fragments for structure determination in the context of structural genomics.     

Detecting coevolution in and among protein domains

Correlated changes of nucleic or amino acids have provided strong information about the structures and interactions of molecules. Despite the rich literature in coevolutionary sequence analysis, previous methods often have to trade off between generality, simplicity, phylogenetic information, and specific knowledge about interactions. Furthermore, despite the evidence of coevolution in selected protein families, a comprehensive screening of coevolution among all protein domains is still lacking. We propose an augmented continuous-time Markov process model for sequence coevolution. The model can handle different types of interactions, incorporate phylogenetic information and sequence substitution, has only one extra free parameter, and requires no knowledge about interaction rules. We employ this model to large-scale screenings on the entire protein domain database (Pfam). Strikingly, with 0.1 trillion tests executed, the majority of the inferred coevolving protein domains are functionally related, and the coevolving amino acid residues are spatially coupled. Moreover, many of the coevolving positions are located at functionally important sites of proteins/protein complexes, such as the subunit linkers of superoxide dismutase, the tRNA binding sites of ribosomes, the DNA binding region of RNA polymerase, and the active and ligand binding sites of various enzymes. The results suggest sequence coevolution manifests structural and functional constraints of proteins. The intricate relations between sequence coevolution and various selective constraints are worth pursuing at a deeper level.     

Evolutionary transitions in protein fold space

With the number of known protein folds potentially approaching completion, the problems associated with their systematic classification are evaluated. It is argued that it will be difficult, if not impossible, to find a general metric based on pairwise comparison that will provide a satisfactory classification. It is suggested that some progress may be made through comparison against a library of idealised 'template' folds, but a proper solution can only be attained if this includes a model of the underlying evolutionary processes. These processes are considered with examples of some unexpected relationships among folds, including circular permutations. The problem is finally set in the wider context of the genetic environment, introducing complications relating to introns, gene fixation and population size.     

Docking and scoring protein complexes: CAPRI 3rd Edition

The performance of methods for predicting protein-protein interactions at the atomic scale is assessed by evaluating blind predictions performed during 2005-2007 as part of Rounds 6-12 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). These Rounds also included a new scoring experiment, where a larger set of models contributed by the predictors was made available to groups developing scoring functions. These groups scored the uploaded set and submitted their own best models for assessment. The structures of nine protein complexes including one homodimer were used as targets. These targets represent biologically relevant interactions involved in gene expression, signal transduction, RNA, or protein processing and membrane maintenance. For all the targets except one, predictions started from the experimentally determined structures of the free (unbound) components or from models derived by homology, making it mandatory for docking methods to model the conformational changes that often accompany association. In total, 63 groups and eight automatic servers, a substantial increase from previous years, submitted docking predictions, of which 1994 were evaluated here. Fifteen groups submitted 305 models for five targets in the scoring experiment. Assessment of the predictions reveals that 31 different groups produced models of acceptable and medium accuracy-but only one high accuracy submission-for all the targets, except the homodimer. In the latter, none of the docking procedures reproduced the large conformational adjustment required for correct assembly, underscoring yet again that handling protein flexibility remains a major challenge. In the scoring experiment, a large fraction of the groups attained the set goal of singling out the correct association modes from incorrect solutions in the limited ensembles of contributed models. But in general they seemed unable to identify the best models, indicating that current scoring methods are probably not sensitive enough. With the increased focus on protein assemblies, in particular by structural genomics efforts, the growing community of CAPRI predictors is engaged more actively than ever in the development of better scoring functions and means of modeling conformational flexibility, which hold promise for much progress in the future.     

Docking protein Gab2 positively regulates glycoprotein VI-mediated platelet activation

Gab2, a recently identified docking protein, contains a pleckstrin homology domain and potential binding sites for SH2 and SH3 domain-containing proteins. Gab2 has been shown to support growth, differentiation, and function in a number of haematopoietic cells, although its role in platelets remains to be determined. Here we report that cross-linking of the collagen receptor GPVI by the snake venom toxin convulxin stimulates tyrosine phosphorylation of Gab2. Furthermore, platelet aggregation induced by submaximal concentrations of convulxin is attenuated in the absence of Gab2, although recovery is seen with higher concentrations of the toxin. Consistent with this, tyrosine phosphorylation of Fc receptor gamma-chain, Syk, Btk, and phospholipase Cgamma2 by convulxin is reduced in the absence of Gab2. In comparison, the G protein-coupled receptor agonist, thrombin, does not induce phosphorylation of Gab2 and aggregation is unaltered in the absence of the toxin. These findings provide evidence for a functional role of Gab2 in supporting platelet activation by GPVI.     

Protein fold recognition and dynamics in the space of contact maps

We introduce an energy function for contact maps of proteins. In addition to the standard term, that takes into account pair-wise interactions between amino acids, our potential contains a new hydrophobic energy term. Parameters of the energy function were obtained from a statistical analysis of the contact maps of known structures. The quality of our energy function was tested extensively in a variety of ways. In particular, fold recognition experiments revealed that for a fixed sequence the native map is identified correctly in an overwhelming majority of the cases tested. We succeeded in identifying the structure of some proteins that are known to pose difficulties for such tests (BPTI, spectrin, and cro-protein). In addition, many known pairs of homologous structures were correctly identified, even when the two sequences had relatively low sequence homology. We also introduced a dynamic Monte Carlo procedure in the space of contact maps, taking topological and polymeric constraints into account by restrictive dynamic rules. Various aspects of protein dynamics, including high-temperature melting and refolding, were simulated. Perspectives of application of the energy function and the method for structure checking and fold prediction are discussed. Proteins 26:391–410 © 1996 Wiley-Liss, Inc.     

Reading protein modifications with interaction domains

Proteins are controlled by a vast and dynamic array of post-translational modifications, many of which create binding sites for specific protein-interaction domains. We propose that these domains, working together, read the state of the proteome and therefore couple post-translational modifications to cellular organization. We also identify common strategies through which modification-dependent interactions synergize to regulate cell behaviour.     

Capturing protein tails by CAP-Gly domains

Cytoskeleton-associated protein-glycine-rich (CAP-Gly) domains are protein-interaction modules implicated in important cellular processes and in hereditary human diseases. A prominent function of CAP-Gly domains is to bind to C-terminal EEY/F-COO(-) sequence motifs present in alpha-tubulin and in some microtubule-associated protein tails; however, CAP-Gly domains also interact with other structural elements including end-binding homology domains, zinc-finger motifs and proline-rich sequences. Recent findings unravelled the link between tubulin tyrosination and CAP-Gly-protein recruitment to microtubules. They further provided a molecular basis for understanding the role of CAP-Gly domains in controlling dynamic cellular processes including the tracking and regulation of microtubule ends. It is becoming increasingly clear that CAP-Gly domains are also involved in coordinating complex and diverse aspects of cell architecture and signalling.     

Clustering of protein domains in the human genome

We present a systematic study of the clustering of genes within the human genome based on homology inferred from both sequence and structural similarity. The 3D-Genomics automated proteome annotation pipeline () was utilised to infer homology for each protein domain in the genome, for the 26 superfamilies most highly represented in the Structural Classification Of Proteins (SCOP) database. This approach enabled us to identify homologues that could not be detected by sequence-based methods alone. For each superfamily, we investigated the distribution, both within and among chromosomes, of genes encoding at least one domain within the superfamily. The results indicate a diversity of clustering behaviours: some superfamilies showed no evidence of any clustering, and others displayed significant clustering either within or among chromosomes, or both. Removal of tandem repeats reduced the levels of clustering observed, but some superfamilies still displayed highly significant clustering. Thus, our study suggests that either the process of gene duplication, or the evolution of the resulting clusters, differs between structural superfamilies.