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Na+/Ca2+ selectivity in the bacterial voltage-gated sodium channel NavAb

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Ion channel, Ion selectivity, Molecular dynamics, Sodium channel, Action potential, Bacterial channel, Calcium channel, Simulation

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      Abstract

      The recent publication of a number of high resolution bacterial voltage-gated sodium channel structures has opened the door for the mechanisms employed by these channels to distinguish between ions to be elucidated. The way these channels select between Na + and K + has been investigated in computational studies, but the selectivity for Na + over Ca 2+ has not yet been studied in this way. Here we use molecular dynamics simulations to calculate the energetics of Na + and Ca 2+ transport through the channel. Single ion profiles show that Ca 2+ experiences a large barrier midway through the selectivity filter that is not seen by Na + . This barrier is caused by the need for Ca 2+ to partly dehydrate to pass through this region and the lack of compensating interactions with the protein. Multi-ion profiles show that ions can pass each other in the channel, which is why the presence of Ca 2+ does not block Na + conduction despite binding more strongly in the pore.

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      Most cited references 56

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      Scalable molecular dynamics with NAMD.

      NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu. (c) 2005 Wiley Periodicals, Inc.
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        All-atom empirical potential for molecular modeling and dynamics studies of proteins.

        New protein parameters are reported for the all-atom empirical energy function in the CHARMM program. The parameter evaluation was based on a self-consistent approach designed to achieve a balance between the internal (bonding) and interaction (nonbonding) terms of the force field and among the solvent-solvent, solvent-solute, and solute-solute interactions. Optimization of the internal parameters used experimental gas-phase geometries, vibrational spectra, and torsional energy surfaces supplemented with ab initio results. The peptide backbone bonding parameters were optimized with respect to data for N-methylacetamide and the alanine dipeptide. The interaction parameters, particularly the atomic charges, were determined by fitting ab initio interaction energies and geometries of complexes between water and model compounds that represented the backbone and the various side chains. In addition, dipole moments, experimental heats and free energies of vaporization, solvation and sublimation, molecular volumes, and crystal pressures and structures were used in the optimization. The resulting protein parameters were tested by applying them to noncyclic tripeptide crystals, cyclic peptide crystals, and the proteins crambin, bovine pancreatic trypsin inhibitor, and carbonmonoxy myoglobin in vacuo and in crystals. A detailed analysis of the relationship between the alanine dipeptide potential energy surface and calculated protein φ, χ angles was made and used in optimizing the peptide group torsional parameters. The results demonstrate that use of ab initio structural and energetic data by themselves are not sufficient to obtain an adequate backbone representation for peptides and proteins in solution and in crystals. Extensive comparisons between molecular dynamics simulations and experimental data for polypeptides and proteins were performed for both structural and dynamic properties. Energy minimization and dynamics simulations for crystals demonstrate that the latter are needed to obtain meaningful comparisons with experimental crystal structures. The presented parameters, in combination with the previously published CHARMM all-atom parameters for nucleic acids and lipids, provide a consistent set for condensed-phase simulations of a wide variety of molecules of biological interest.
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          THE weighted histogram analysis method for free-energy calculations on biomolecules. I. The method

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            Author and article information

            Affiliations
            Research School of Biology , The Australian National University, Acton, Australia
            Contributors
            Journal
            Peerj
            Peerj
            PeerJ
            PeerJ
            PeerJ
            PeerJ Inc. (San Francisco, USA )
            2167-8359
            12 February 2013
            2013
            : 1
            23638350
            3629057
            16
            10.7717/peerj.16
            (Editor)
            © 2013 Corry

            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.

            Product
            Funding
            Funded by: Pawsey Centre Project
            Funded by: Merit Allocation Scheme of the NCI
            This work was supported by computer time from the Pawsey Centre Project in Western Australia and through an award under the Merit Allocation Scheme of the NCI facility at the ANU. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Biophysics
            Computational Biology

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