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      Coherent Conformational Degrees of Freedom as a Structural Basis for Allosteric Communication

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      1 , 2 , 1 , *
      PLoS Computational Biology
      Public Library of Science

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          Abstract

          Conformational changes in allosteric regulation can to a large extent be described as motion along one or a few coherent degrees of freedom. The states involved are inherent to the protein, in the sense that they are visited by the protein also in the absence of effector ligands. Previously, we developed the measure binding leverage to find sites where ligand binding can shift the conformational equilibrium of a protein. Binding leverage is calculated for a set of motion vectors representing independent conformational degrees of freedom. In this paper, to analyze allosteric communication between binding sites, we introduce the concept of leverage coupling, based on the assumption that only pairs of sites that couple to the same conformational degrees of freedom can be allosterically connected. We demonstrate how leverage coupling can be used to analyze allosteric communication in a range of enzymes (regulated by both ligand binding and post-translational modifications) and huge molecular machines such as chaperones. Leverage coupling can be calculated for any protein structure to analyze both biological and latent catalytic and regulatory sites.

          Author Summary

          What are the molecular mechanisms of allosteric communication in proteins? We base our analysis on the hypothesis that a folded protein has a number of conformational degrees of freedom, which describe fluctuations around the native conformation and switching from/to functional states. Transitions between the protein states involved in function and its regulation are based on coherent conformational degrees of freedom. Motion of one part of a protein along such a degree of freedom, implies a correlated motion in other parts of the protein. By determining which binding sites are simultaneously affected by the same motion we find sites that are allosterically coupled, i.e. where binding at one site can cause a change in ligand-affinity at another. Leverage coupling, the quantity introduced to measure this type of connection, reflects allosteric communication between different binding sites. We show how it can be used to understand allostery in enzymes of different sizes as well as in large protein complexes such as chaperones. Analysis of leverage coupling provides guidance in targeting native and latent regulatory sites.

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          Most cited references34

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          The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data.

          The Catalytic Site Atlas (CSA) provides catalytic residue annotation for enzymes in the Protein Data Bank. It is available online at http://www.ebi.ac.uk/thornton-srv/databases/CSA. The database consists of two types of annotated site: an original hand-annotated set containing information extracted from the primary literature, using defined criteria to assign catalytic residues, and an additional homologous set, containing annotations inferred by PSI-BLAST and sequence alignment to one of the original set. The CSA can be queried via Swiss-Prot identifier and EC number, as well as by PDB code. CSA Version 1.0 contains 177 original hand- annotated entries and 2608 homologous entries, and covers approximately 30% of all EC numbers found in PDB. The CSA will be updated on a monthly basis to include homologous sites found in new PDBs, and new hand-annotated enzymes as and when their annotation is completed.
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            Coarse-grained normal mode analysis in structural biology.

            The realization that experimentally observed functional motions of proteins can be predicted by coarse-grained normal mode analysis has renewed interest in applications to structural biology. Notable applications include the prediction of biologically relevant motions of proteins and supramolecular structures driven by their structure-encoded collective dynamics; the refinement of low-resolution structures, including those determined by cryo-electron microscopy; and the identification of conserved dynamic patterns and mechanically key regions within protein families. Additionally, hybrid methods that couple atomic simulations with deformations derived from coarse-grained normal mode analysis are able to sample collective motions beyond the range of conventional molecular dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.
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              Usefulness and limitations of normal mode analysis in modeling dynamics of biomolecular complexes.

              Various types of large-amplitude molecular deformation are ubiquitously involved in the functions of biological macromolecules, especially supramolecular complexes. They can be very effectively analyzed by normal mode analysis with well-established procedures. However, despite its enormous success in numerous applications, certain issues related to the applications of normal mode analysis require further discussion. In this review, the author addresses some common issues so as to raise the awareness of the usefulness and limitations of the method in the general community of structural biology.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                December 2011
                December 2011
                8 December 2011
                : 7
                : 12
                : e1002301
                Affiliations
                [1 ]Computational Biology Unit/Uni Research, University of Bergen, Bergen, Norway
                [2 ]Department of Informatics, University of Bergen, Bergen, Norway
                Stanford University, United States of America
                Author notes

                Performed the experiments: SM. Analyzed the data: SM INB. Wrote the paper: SM INB. Conceived the experiments: INB. Designed the experiments: SM INB. Designed the software used in analysis: SM.

                Article
                PCOMPBIOL-D-11-01227
                10.1371/journal.pcbi.1002301
                3234217
                22174669
                bdd29284-0784-4913-84b2-18400ae709b4
                Mitternacht, Berezovsky. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 18 August 2011
                : 29 October 2011
                Page count
                Pages: 12
                Categories
                Research Article
                Biology
                Computational Biology
                Biological Data Management
                Biophysic Al Simulations
                Theoretical Biology
                Physics
                Biophysics
                Protein Chemistry

                Quantitative & Systems biology
                Quantitative & Systems biology

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