Article

Structural basis for protein–protein interactions in the 14-3-3 protein family

Structural Genomics Consortium, University of Oxford, Botnar Research Centre, Oxford OX3 7LD, United Kingdom.
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 12/2006; 103(46):17237-42. DOI: 10.1073/pnas.0605779103
Source: PubMed

ABSTRACT The seven members of the human 14-3-3 protein family regulate a diverse range of cell signaling pathways by formation of protein-protein complexes with signaling proteins that contain phosphorylated Ser/Thr residues within specific sequence motifs. Previously, crystal structures of three 14-3-3 isoforms (zeta, sigma, and tau) have been reported, with structural data for two isoforms deposited in the Protein Data Bank (zeta and sigma). In this study, we provide structural detail for five 14-3-3 isoforms bound to ligands, providing structural coverage for all isoforms of a human protein family. A comparative structural analysis of the seven 14-3-3 proteins revealed specificity determinants for binding of phosphopeptides in a specific orientation, target domain interaction surfaces and flexible adaptation of 14-3-3 proteins through domain movements. Specifically, the structures of the beta isoform in its apo and peptide bound forms showed that its binding site can exhibit structural flexibility to facilitate binding of its protein and peptide partners. In addition, the complex of 14-3-3 beta with the exoenzyme S peptide displayed a secondary structural element in the 14-3-3 peptide binding groove. These results show that the 14-3-3 proteins are adaptable structures in which internal flexibility is likely to facilitate recognition and binding of their interaction partners.

Download full-text

Full-text

Available from: Jörg Günter Grossmann, Aug 23, 2015
0 Followers
 · 
131 Views
  • Source
    • "(B) illustrates the formation of possible dimers within the mammalian 14-3-3 protein family. The reported interactions are shown between different monomers by formation of heterodimers (14-3-3e/YWHAE with 14-3-3b/YWHAB, 14-3-3g/ YWHAG, 14-3-3h/YWHAH, 14-3-3z/YWHAZ, and 14-3-3t/YWHAQ) and by formation of homodimers [Yang et al., 2006]. 14-3-3s/YWHAS is found to preferentially form homodimers, whereas YWHAE is found as heterodimers in cells. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Monoamines critically modulate neurophysiological functions affected in several neuropsychiatric disorders. We therefore examined genes encoding key enzymes of catecholamine and serotonin biosynthesis (tyrosine and tryptophan hydroxylases-TH and TPH1/2) as well as their regulatory 14-3-3 proteins (encoded by YWHA-genes). Previous studies have focused mainly on the individual genes, but no analysis spanning this regulatory network has been reported. We explored interactions between these genes in Norwegian patients with adult attention deficit hyperactivity disorder (aADHD), followed by gene-complex association tests in four major neuropsychiatric conditions; childhood ADHD (cADHD), bipolar disorder, schizophrenia, and major depressive disorder. For interaction analyses, we evaluated 55 SNPs across these genes in a sample of 583 aADHD patients and 637 controls. For the gene-complex tests, we utilized the data from large-scale studies of The Psychiatric Genomics Consortium (PGC). The four major neuropsychiatric disorders were examined for association with each of the genes individually as well as in three complexes as follows: (1) TPH1 and YWHA-genes; (2) TH, TPH2 and YWHA-genes; and (3) all genes together. The results show suggestive epistasis between YWHAE and two other 14-3-3-genes - YWHAZ, YWHAQ - in aADHD (nominal P-value of 0.0005 and 0.0008, respectively). In PGC data, association between YWHAE and schizophrenia was noted (P = 1.00E-05), whereas the combination of TPH1 and YWHA-genes revealed signs of association in cADHD, schizophrenia, and bipolar disorder. In conclusion, polymorphisms in the YWHA-genes and their targets may exert a cumulative effect in ADHD and related neuropsychiatric conditions, warranting the need for further investigation of these gene-complexes. © 2015 Wiley Periodicals, Inc. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 07/2015; DOI:10.1002/ajmg.b.32339 · 3.27 Impact Factor
  • Source
    • "Several studies have shown tissue and/or cell cycle phase specific expression of 14-3-3 isoforms (Moreira et al., 2008). Structural data show little divergence in the phosphopeptide-binding pockets of the 14- 3-3 paralogs (Yang et al., 2006), and because most 14-3-3 binding motifs conform to a few consensus sequences, it seems that isoform specificity does not reside in the binding site of the 14-3-3 partners (Uhart et al., 2011). Indeed, it most likely depends on additional contacts with the partner, probably involving residues such as anchors (Rajamani et al., 2004), outside the 14-3-3 binding motifs on the 14-3-3 partners (Uhart et al., 2011; Bier et al., 2013). "
    [Show abstract] [Hide abstract]
    ABSTRACT: The understanding of networks is a common goal of an unprecedented array of traditional disciplines. One of the protein network properties most influenced by the structural contents of its nodes is the inter-connectivity. Recent studies in which structural information was included into the topological analysis of protein networks revealed that the content of intrinsic disorder in the nodes could modulate the network topology, rewire networks, and change their inter-connectivity, which is defined by its clustering coefficient. Here, we review the role of intrinsic disorder present in the partners of the highly conserved 14-3-3 protein family on its interaction networks. The 14-3-3s are phospho-serine/threonine binding proteins that have strong influence in the regulation of metabolism and signal transduction networks. Intrinsic disorder increases the clustering coefficients, namely the inter-connectivity of the nodes within each 14-3-3 paralog networks. We also review two new ideas to measure intrinsic disorder independently of the primary sequence of proteins, a thermodynamic model and a method that uses protein structures and their solvent environment. This new methods could be useful to explain unsolved questions about versatility and fixation of intrinsic disorder through evolution. The relation between the intrinsic disorder and network topologies could be an interesting model to investigate new implicitness of the graph theory into biology.
    Frontiers in Genetics 02/2014; 5:10. DOI:10.3389/fgene.2014.00010
  • Source
    • "We generated a structural model of yeast dimeric Bmh1p to locate the amino acid changes and truncation on the 3D protein structure. We used its homology with the human protein 2BR9, whose structure has been resolved by crystallography (Yang et al. 2006, see Supporting Information and Material and methods). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Different organisms have independently and recurrently evolved similar phenotypic traits at different points throughout history. This phenotypic convergence may be caused by genotypic convergence and in addition, constrained by historical contingency. To investigate how convergence may be driven by selection in a particular environment and constrained by history, we analyzed nine life-history traits and four metabolic traits during an experimental evolution of six yeast strains in four different environments. In each of the environments, the population converged towards a different multivariate phenotype. However, the evolution of most traits, including fitness components, was constrained by history. Phenotypic convergence was partly associated with the selection of mutations in genes involved in the same pathway. By further investigating the convergence in one gene, BMH1, mutated in 20% of the evolved populations, we show that both the history and the environment influenced the types of mutations (missense/nonsense), their location within the gene itself, as well as their effects on multiple traits. However, these effects could not be easily predicted from ancestors' phylogeny or past-selection. Combined, our data highlight the role of pleiotropy and epistasis in shaping a rugged fitness landscape. This article is protected by copyright. All rights reserved.
    Evolution 10/2013; 68(3). DOI:10.1111/evo.12302 · 4.66 Impact Factor
Show more