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      The dynamic dimer structure of the chaperone Trigger Factor

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          Abstract

          The chaperone Trigger Factor (TF) from Escherichia coli forms a dimer at cellular concentrations. While the monomer structure of TF is well known, the spatial arrangement of this dimeric chaperone storage form has remained unclear. Here, we determine its structure by a combination of high-resolution NMR spectroscopy and biophysical methods. TF forms a symmetric head-to-tail dimer, where the ribosome binding domain is in contact with the substrate binding domain, while the peptidyl-prolyl isomerase domain contributes only slightly to the dimer affinity. The dimer structure is highly dynamic, with the two ribosome binding domains populating a conformational ensemble in the center. These dynamics result from intermolecular in trans interactions of the TF client-binding site with the ribosome binding domain, which is conformationally frustrated in the absence of the ribosome. The avidity in the dimer structure explains how the dimeric state of TF can be monomerized also by weakly interacting clients.

          Abstract

          The bacterial chaperone Trigger Factor (TF) is a dynamic protein and its dimer structure is unknown. Here the authors present a protocol combining NMR, computational and biophysical methods for the structural characterization of large dynamic protein complexes and show that TF forms a symmetric head-to-tail dimer.

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          Molecular chaperones in protein folding and proteostasis.

          Most proteins must fold into defined three-dimensional structures to gain functional activity. But in the cellular environment, newly synthesized proteins are at great risk of aberrant folding and aggregation, potentially forming toxic species. To avoid these dangers, cells invest in a complex network of molecular chaperones, which use ingenious mechanisms to prevent aggregation and promote efficient folding. Because protein molecules are highly dynamic, constant chaperone surveillance is required to ensure protein homeostasis (proteostasis). Recent advances suggest that an age-related decline in proteostasis capacity allows the manifestation of various protein-aggregation diseases, including Alzheimer's disease and Parkinson's disease. Interventions in these and numerous other pathological states may spring from a detailed understanding of the pathways underlying proteome maintenance.
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            Version 1.2 of the Crystallography and NMR system.

            Version 1.2 of the software system, termed Crystallography and NMR system (CNS), for crystallographic and NMR structure determination has been released. Since its first release, the goals of CNS have been (i) to create a flexible computational framework for exploration of new approaches to structure determination, (ii) to provide tools for structure solution of difficult or large structures, (iii) to develop models for analyzing structural and dynamical properties of macromolecules and (iv) to integrate all sources of information into all stages of the structure determination process. Version 1.2 includes an improved model for the treatment of disordered solvent for crystallographic refinement that employs a combined grid search and least-squares optimization of the bulk solvent model parameters. The method is more robust than previous implementations, especially at lower resolution, generally resulting in lower R values. Other advances include the ability to apply thermal factor sharpening to electron density maps. Consistent with the modular design of CNS, these additions and changes were implemented in the high-level computing language of CNS.
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              A series of PDB-related databanks for everyday needs

              We present a series of databanks (http://swift.cmbi.ru.nl/gv/facilities/) that hold information that is computationally derived from Protein Data Bank (PDB) entries and that might augment macromolecular structure studies. These derived databanks run parallel to the PDB, i.e. they have one entry per PDB entry. Several of the well-established databanks such as HSSP, PDBREPORT and PDB_REDO have been updated and/or improved. The software that creates the DSSP databank, for example, has been rewritten to better cope with π-helices. A large number of databanks have been added to aid computational structural biology; some examples are lists of residues that make crystal contacts, lists of contacting residues using a series of contact definitions or lists of residue accessibilities. PDB files are not the optimal presentation of the underlying data for many studies. We therefore made a series of databanks that hold PDB files in an easier to use or more consistent representation. The BDB databank holds X-ray PDB files with consistently represented B-factors. We also added several visualization tools to aid the users of our databanks.
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                Author and article information

                Contributors
                sebastian.hiller@unibas.ch
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                8 December 2017
                8 December 2017
                2017
                : 8
                : 1992
                Affiliations
                [1 ]ISNI 0000 0004 1937 0642, GRID grid.6612.3, Biozentrum, , University of Basel, ; Klingelbergstrasse 70, 4056 Basel, Switzerland
                [2 ]ISNI 0000 0000 9919 9582, GRID grid.8761.8, Present Address: Department of Chemistry and Molecular Biology, Wallenberg Centre of Molecular and Translational Medicine, , University of Gothenburg, ; 405 30 Göteborg, Sweden
                Author information
                http://orcid.org/0000-0002-3135-7964
                http://orcid.org/0000-0002-6709-4684
                Article
                2196
                10.1038/s41467-017-02196-7
                5722895
                29222465
                8f773c7d-7b13-4db3-b095-b5d6af0986eb
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 May 2017
                : 12 November 2017
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