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      CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic Protein Structures

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          Abstract

          Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

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          Most cited references45

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          Crystal structure and mechanism of a calcium-gated potassium channel.

          Ion channels exhibit two essential biophysical properties; that is, selective ion conduction, and the ability to gate-open in response to an appropriate stimulus. Two general categories of ion channel gating are defined by the initiating stimulus: ligand binding (neurotransmitter- or second-messenger-gated channels) or membrane voltage (voltage-gated channels). Here we present the structural basis of ligand gating in a K(+) channel that opens in response to intracellular Ca(2+). We have cloned, expressed, analysed electrical properties, and determined the crystal structure of a K(+) channel (MthK) from Methanobacterium thermoautotrophicum in the Ca(2+)-bound, opened state. Eight RCK domains (regulators of K(+) conductance) form a gating ring at the intracellular membrane surface. The gating ring uses the free energy of Ca(2+) binding in a simple manner to perform mechanical work to open the pore.
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            Principles of selective ion transport in channels and pumps.

            The transport of ions across the membranes of cells and organelles is a prerequisite for many of life's processes. Transport often involves very precise selectivity for specific ions. Recently, atomic-resolution structures have been determined for channels or pumps that are selective for sodium, potassium, calcium, and chloride: four of the most abundant ions in biology. From these structures we can begin to understand the principles of selective ion transport in terms of the architecture and detailed chemistry of the ion conduction pathways.
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              3V: cavity, channel and cleft volume calculator and extractor

              As larger macromolecular structures become available, there is a growing need to understand their ‘internal’ volumes—such as deep clefts, channels and cavities—as these often play critical roles in their function. The 3V web server can automatically extract and comprehensively analyze all the internal volumes from input RNA and protein structures. It rapidly finds internal volumes by taking the difference between two rolling-probe solvent-excluded surfaces, one with as large as possible a probe radius and the other with a solvent radius (typically 1.5 Å for water). The outputs are volumetric representations, both as images and downloadable files, which can be used for further analysis. The 3V server and source code are available from http://3vee.molmovdb.org.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                October 2012
                October 2012
                18 October 2012
                : 8
                : 10
                : e1002708
                Affiliations
                [1 ]Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic
                [2 ]Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Brno, Czech Republic
                [3 ]International Centre for Clinical Research, St. Anne's University Hospital Brno, Brno, Czech Republic
                UCSD, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: EC AP PB OS JB BK AG VS MK PM LB JS JD. Performed the experiments: EC AP PB JB AG MK LB. Analyzed the data: EC AP JB JD. Wrote the paper: EC AP JB LB JD. Contributed the software code: AP PB OS BK VS PM JS. Edited the manuscript: PB OS BK AG VS MK PM JS. Prepared manual and examples: EC AP JB VS.

                Article
                PCOMPBIOL-D-12-00584
                10.1371/journal.pcbi.1002708
                3475669
                23093919
                fe285d01-4116-4ed2-8160-839b67603579
                Copyright @ 2012

                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
                : 4 April 2012
                : 1 August 2012
                Page count
                Pages: 12
                Funding
                This work was supported by the European Regional Development Fund (CZ.1.05/2.1.00/01.0001 and CZ.1.05/1.1.00/02.0123), the Grant Agency of the Czech Republic (P202/10/1435 and P503/12/0572) and the Grant Agency of the Czech Academy of Sciences (IAA401630901). MetaCentrum provided access to computing facilities, supported by the Ministry of Education of the Czech Republic (LM2010005). The work of AG was supported by SoMoPro programme No. SIGA762 funded by the European Community within the 7th FP under grant agreement No. 229603, and cofinanced by the South Moravian Region. The work of AP was supported by Brno Ph.D. Talent Scholarship provided by Brno City Municipality. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Computational Biology
                Theoretical Biology
                Chemistry
                Theoretical Chemistry
                Physics
                Biophysics

                Quantitative & Systems biology
                Quantitative & Systems biology

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