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      The Structure and Regulation of Human Muscle α-Actinin

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          Summary

          The spectrin superfamily of proteins plays key roles in assembling the actin cytoskeleton in various cell types, crosslinks actin filaments, and acts as scaffolds for the assembly of large protein complexes involved in structural integrity and mechanosensation, as well as cell signaling. α-actinins in particular are the major actin crosslinkers in muscle Z-disks, focal adhesions, and actin stress fibers. We report a complete high-resolution structure of the 200 kDa α-actinin-2 dimer from striated muscle and explore its functional implications on the biochemical and cellular level. The structure provides insight into the phosphoinositide-based mechanism controlling its interaction with sarcomeric proteins such as titin, lays a foundation for studying the impact of pathogenic mutations at molecular resolution, and is likely to be broadly relevant for the regulation of spectrin-like proteins.

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          Highlights

          • Structure of human α-actinin-2 in an autoinhibited closed conformation

          • Facilitation of PIP2-induced allosteric modulation for opening and titin binding

          • Essentiality of structural flexibility for crosslinking antiparallel F-actin

          • Relevance for the intramolecular pseudoligand regulation mechanism of the spectrin family

          Abstract

          The structure of human α-actinin, the major component of the basic contractile units of muscles, reveals a unique phosphoinositide-based mechanism of its regulation, as well as assembly.

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          Most cited references81

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          Linking crystallographic model and data quality.

          In macromolecular x-ray crystallography, refinement R values measure the agreement between observed and calculated data. Analogously, R(merge) values reporting on the agreement between multiple measurements of a given reflection are used to assess data quality. Here, we show that despite their widespread use, R(merge) values are poorly suited for determining the high-resolution limit and that current standard protocols discard much useful data. We introduce a statistic that estimates the correlation of an observed data set with the underlying (not measurable) true signal; this quantity, CC*, provides a single statistically valid guide for deciding which data are useful. CC* also can be used to assess model and data quality on the same scale, and this reveals when data quality is limiting model improvement.
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            Why molecules move along a temperature gradient.

            Molecules drift along temperature gradients, an effect called thermophoresis, the Soret effect, or thermodiffusion. In liquids, its theoretical foundation is the subject of a long-standing debate. By using an all-optical microfluidic fluorescence method, we present experimental results for DNA and polystyrene beads over a large range of particle sizes, salt concentrations, and temperatures. The data support a unifying theory based on solvation entropy. Stated in simple terms, the Soret coefficient is given by the negative solvation entropy, divided by kT. The theory predicts the thermodiffusion of polystyrene beads and DNA without any free parameters. We assume a local thermodynamic equilibrium of the solvent molecules around the molecule. This assumption is fulfilled for moderate temperature gradients below a fluctuation criterion. For both DNA and polystyrene beads, thermophoretic motion changes sign at lower temperatures. This thermophilicity toward lower temperatures is attributed to an increasing positive entropy of hydration, whereas the generally dominating thermophobicity is explained by the negative entropy of ionic shielding. The understanding of thermodiffusion sets the stage for detailed probing of solvation properties of colloids and biomolecules. For example, we successfully determine the effective charge of DNA and beads over a size range that is not accessible with electrophoresis.
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              Global rigid body modeling of macromolecular complexes against small-angle scattering data.

              New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented. Depending on the complexity of the object, different approaches are employed for the global search of the optimum configuration of subunits fitting the experimental data. An exhaustive grid search is used for hetero- and homodimeric particles and for symmetric oligomers formed by identical subunits. For the assemblies or multidomain proteins containing more then one subunit/domain per asymmetric unit, heuristic algorithms based on simulated annealing are used. Fast computational algorithms based on spherical harmonics representation of scattering amplitudes are employed. The methods allow one to construct interconnected models without steric clashes, to account for the particle symmetry and to incorporate information from other methods, on distances between specific residues or nucleotides. For multidomain proteins, addition of missing linkers between the domains is possible. Simultaneous fitting of multiple scattering patterns from subcomplexes or deletion mutants is incorporated. The efficiency of the methods is illustrated by their application to complexes of different types in several simulated and practical examples. Limitations and possible ambiguity of rigid body modeling are discussed and simplified docking criteria are provided to rank multiple models. The methods described are implemented in publicly available computer programs running on major hardware platforms.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                04 December 2014
                04 December 2014
                : 159
                : 6
                : 1447-1460
                Affiliations
                [1 ]Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5, 1030 Vienna, Austria
                [2 ]British Heart Foundation Centre of Research Excellence, Randall Division for Cell and Molecular Biophysics and Cardiovascular Division, King’s College London, London SE1 1UL, UK
                [3 ]European Molecular Biology Laboratory, Deutsches Elektronen-Synchrotron, Notkestrasse 85, 22603 Hamburg, Germany
                [4 ]Department of Biotechnology, Norwegian University of Science and Technology, Sem Sælands vei 6/8, 7491 Trondheim, Norway
                [5 ]Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
                [6 ]Division of Biochemistry, Department of Chemistry, University of Natural Resources and Life Sciences, Muthgasse 18, 1190 Vienna, Austria
                [7 ]Department of Biochemistry, Faculty of Chemistry and Chemical Technology, University of Ljubljana, Aškerčeva 5, 1000 Ljubljana, Slovenia
                [8 ]M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997, Russia
                [9 ]Fachbereich Physik, Freie Universität Berlin, Arnimallee 14, 14195 Berlin, Germany
                Author notes
                []Corresponding author mathias.gautel@ 123456kcl.ac.uk
                [∗∗ ]Corresponding author kristina.djinovic@ 123456univie.ac.at
                [10]

                Co-first author

                Article
                S0092-8674(14)01428-7
                10.1016/j.cell.2014.10.056
                4259493
                25433700
                02847fc1-767e-40a6-89e2-352042f133fc
                © 2014 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

                History
                : 7 May 2014
                : 1 October 2014
                : 24 October 2014
                Categories
                Article

                Cell biology
                Cell biology

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