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      The Interaction of CRM1 and the Nuclear Pore Protein Tpr

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          Abstract

          While much has been devoted to the study of transport mechanisms through the nuclear pore complex (NPC), the specifics of interactions and binding between export transport receptors and the NPC periphery have remained elusive. Recent work has demonstrated a binding interaction between the exportin CRM1 and the unstructured carboxylic tail of Tpr, on the nuclear basket. Strong evidence suggests that this interaction is vital to the functions of CRM1. Using molecular dynamics simulations and a newly refined method for determining binding regions, we have identified nine candidate binding sites on CRM1 for C-Tpr. These include two adjacent to RanGTP – from which one is blocked in the absence of RanGTP – and three next to the binding region of the cargo Snurportin. We report two additional interaction sites between C-Tpr and Snurportin, suggesting a possible role for Tpr import into the nucleus. Using bioinformatics tools we have conducted conservation analysis and functional residue prediction investigations to identify which parts of the obtained binding sites are inherently more important and should be highlighted. Also, a novel measure based on the ratio of available solvent accessible surface (RASAS) is proposed for monitoring the ligand/receptor binding process.

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          Most cited references25

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          Multiple sequence alignment with the Clustal series of programs.

          R Chenna (2003)
          The Clustal series of programs are widely used in molecular biology for the multiple alignment of both nucleic acid and protein sequences and for preparing phylogenetic trees. The popularity of the programs depends on a number of factors, including not only the accuracy of the results, but also the robustness, portability and user-friendliness of the programs. New features include NEXUS and FASTA format output, printing range numbers and faster tree calculation. Although, Clustal was originally developed to run on a local computer, numerous Web servers have been set up, notably at the EBI (European Bioinformatics Institute) (http://www.ebi.ac.uk/clustalw/).
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            ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information.

            We recently developed algorithmic tools for the identification of functionally important regions in proteins of known three dimensional structure by estimating the degree of conservation of the amino-acid sites among their close sequence homologues. Projecting the conservation grades onto the molecular surface of these proteins reveals patches of highly conserved (or occasionally highly variable) residues that are often of important biological function. We present a new web server, ConSurf, which automates these algorithmic tools. ConSurf may be used for high-throughput characterization of functional regions in proteins. The ConSurf web server is available at:http://consurf.tau.ac.il. A set of examples is available at http://consurf.tau.ac.il under 'GALLERY'.
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              ProMate: a structure based prediction program to identify the location of protein-protein binding sites.

              Is the whole protein surface available for interaction with other proteins, or are specific sites pre-assigned according to their biophysical and structural character? And if so, is it possible to predict the location of the binding site from the surface properties? These questions are answered quantitatively by probing the surfaces of proteins using spheres of radius of 10 A on a database (DB) of 57 unique, non-homologous proteins involved in heteromeric, transient protein-protein interactions for which the structures of both the unbound and bound states were determined. In structural terms, we found the binding site to have a preference for beta-sheets and for relatively long non-structured chains, but not for alpha-helices. Chemically, aromatic side-chains show a clear preference for binding sites. While the hydrophobic and polar content of the interface is similar to the rest of the surface, hydrophobic and polar residues tend to cluster in interfaces. In the crystal, the binding site has more bound water molecules surrounding it, and a lower B-factor already in the unbound protein. The same biophysical properties were found to hold for the unbound and bound DBs. All the significant interface properties were combined into ProMate, an interface prediction program. This was followed by an optimization step to choose the best combination of properties, as many of them are correlated. During optimization and prediction, the tested proteins were not used for data collection, to avoid over-fitting. The prediction algorithm is fully automated, and is used to predict the location of potential binding sites on unbound proteins with known structures. The algorithm is able to successfully predict the location of the interface for about 70% of the proteins. The success rate of the predictor was equal whether applied on the unbound DB or on the disjoint bound DB. A prediction is assumed correct if over half of the predicted continuous interface patch is indeed interface. The ability to predict the location of protein-protein interfaces has far reaching implications both towards our understanding of specificity and kinetics of binding, as well as in assisting in the analysis of the proteome.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                10 April 2014
                : 9
                : 4
                : e93709
                Affiliations
                [1]Molecular Cell Biomechanics Laboratory, Departments of Bioengineering and Mechanical Engineering, University of California, Berkeley, California, United States of America
                George Washington University, United States of America
                Author notes

                Competing Interests: The authors hereby confirm that the corresponding author is a PLOS ONE Editorial Board member. This does not alter their adherence to PLOS ONE Editorial policies and criteria.

                Conceived and designed the experiments: CZ SMH RMB MRKM. Performed the experiments: CZ SMH. Analyzed the data: CZ SMH RMB MRKM. Contributed reagents/materials/analysis tools: MRKM. Wrote the paper: CZ SMH RMB MRKM.

                Article
                PONE-D-13-44281
                10.1371/journal.pone.0093709
                3983112
                24722547
                e39af6e9-939e-4b42-ac80-3e22fb662afe
                Copyright @ 2014

                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
                : 30 October 2013
                : 5 March 2014
                Page count
                Pages: 13
                Funding
                Computational grants from the XSEDE supercomputing system (TG-MCB100146), especially the Texas Advanced Computing Center (TACC) and the San Diego Supercomputer Center (SDSC) are thankfully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Biomacromolecule-Ligand Interactions
                Proteins
                Biomechanics
                Biophysics
                Biophysical Simulations
                Cell Biology
                Cellular Structures and Organelles
                Cell Membranes
                Membrane Proteins
                Transmembrane Proteins
                Cell Nucleus
                Molecular Cell Biology
                Computational Biology
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics

                Uncategorized
                Uncategorized

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