97
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Flexible nets: disorder and induced fit in the associations of p53 and 14-3-3 with their partners

      research-article
      1 , 1 , 1 , 1 , 1 , 2 , 1 ,
      BMC Genomics
      BioMed Central
      The 2007 International Conference on Bioinformatics & Computational Biology (BIOCOMP'07)
      25–28 June 2007

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Proteins are involved in many interactions with other proteins leading to networks that regulate and control a wide variety of physiological processes. Some of these proteins, called hub proteins or hubs, bind to many different protein partners. Protein intrinsic disorder, via diversity arising from structural plasticity or flexibility, provide a means for hubs to associate with many partners (Dunker AK, Cortese MS, Romero P, Iakoucheva LM, Uversky VN: Flexible Nets: The roles of intrinsic disorder in protein interaction networks. FEBS J 2005, 272:5129-5148).

          Results

          Here we present a detailed examination of two divergent examples: 1) p53, which uses different disordered regions to bind to different partners and which also has several individual disordered regions that each bind to multiple partners, and 2) 14-3-3, which is a structured protein that associates with many different intrinsically disordered partners. For both examples, three-dimensional structures of multiple complexes reveal that the flexibility and plasticity of intrinsically disordered protein regions as well as induced-fit changes in the structured regions are both important for binding diversity.

          Conclusions

          These data support the conjecture that hub proteins often utilize intrinsic disorder to bind to multiple partners and provide detailed information about induced fit in structured regions.

          Related collections

          Most cited references132

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Error and attack tolerance of complex networks

          Many complex systems, such as communication networks, display a surprising degree of robustness: while key components regularly malfunction, local failures rarely lead to the loss of the global information-carrying ability of the network. The stability of these complex systems is often attributed to the redundant wiring of the functional web defined by the systems' components. In this paper we demonstrate that error tolerance is not shared by all redundant systems, but it is displayed only by a class of inhomogeneously wired networks, called scale-free networks. We find that scale-free networks, describing a number of systems, such as the World Wide Web, Internet, social networks or a cell, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected by even unrealistically high failure rates. However, error tolerance comes at a high price: these networks are extremely vulnerable to attacks, i.e. to the selection and removal of a few nodes that play the most important role in assuring the network's connectivity.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae.

            Two large-scale yeast two-hybrid screens were undertaken to identify protein-protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A comprehensive two-hybrid analysis to explore the yeast protein interactome.

              Protein-protein interactions play crucial roles in the execution of various biological functions. Accordingly, their comprehensive description would contribute considerably to the functional interpretation of fully sequenced genomes, which are flooded with novel genes of unpredictable functions. We previously developed a system to examine two-hybrid interactions in all possible combinations between the approximately 6,000 proteins of the budding yeast Saccharomyces cerevisiae. Here we have completed the comprehensive analysis using this system to identify 4,549 two-hybrid interactions among 3,278 proteins. Unexpectedly, these data do not largely overlap with those obtained by the other project [Uetz, P., et al. (2000) Nature (London) 403, 623-627] and hence have substantially expanded our knowledge on the protein interaction space or interactome of the yeast. Cumulative connection of these binary interactions generates a single huge network linking the vast majority of the proteins. Bioinformatics-aided selection of biologically relevant interactions highlights various intriguing subnetworks. They include, for instance, the one that had successfully foreseen the involvement of a novel protein in spindle pole body function as well as the one that may uncover a hitherto unidentified multiprotein complex potentially participating in the process of vesicular transport. Our data would thus significantly expand and improve the protein interaction map for the exploration of genome functions that eventually leads to thorough understanding of the cell as a molecular system.
                Bookmark

                Author and article information

                Conference
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2008
                20 March 2008
                : 9
                : Suppl 1
                : S1
                Affiliations
                [1 ]Center for Computational Biology and Bioinformatics, Indiana University Schools of Medicine and Informatics, 410 W. 10 th Street, Indianapolis, IN 46202, USA
                [2 ]Institute for Biological Instrumentation, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia
                Article
                1471-2164-9-S1-S1
                10.1186/1471-2164-9-S1-S1
                2386051
                18366598
                9c12d000-3f8f-435a-863d-a39a2a011ef2
                Copyright © 2008 Oldfield et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                The 2007 International Conference on Bioinformatics & Computational Biology (BIOCOMP'07)
                Las Vegas, NV, USA
                25–28 June 2007
                History
                Categories
                Research

                Genetics
                Genetics

                Comments

                Comment on this article