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New Algorithms for Macromolecular Simulation pp 263–295Cite as

Implicit Solvent Electrostatics in Biomolecular Simulation

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Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 49))

Abstract

We give an overview of how implicit solvent models are currently used in protein simulations. The emphasis is on numerical algorithms and approximations: since even folded proteins sample many distinct configurations, it is of considerable importance to be both accurate and efficient in estimating the energetic consequences of this dynamical behavior. Particular attention is paid to calculations of pH-dependent behavior, as a paradigm for the analysis of electrostatic interactions in complex systems.

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Authors and Affiliations

  1. Dept. of Biochemistry and Molecular Biophysics, Washington University, St. Louis, MO, 63110, USA

    Nathan A. Baker

  2. Dept. of Molecular Biotechnology, St. Jude Childrens Research Hospital, Memphis, TN, 38105, USA

    Donald Bashford

  3. Dept. of Molecular Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA

    David A. Case

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  1. Nathan A. Baker
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  2. Donald Bashford
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  3. David A. Case
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Leicester, University Road, Leicester, LE1 7RH, UK

    Benedict Leimkuhler

  2. Institut nancéien de chimie moléculaire, Université Henri Poincaré - Nancy I, B.P. 239, 54506, Vandoeuvre-lès-Nancy, France

    Christophe Chipot

  3. Department of Computer Science, Cornell University, 4130 Upson Hall, Ithaca, NY, 14853-7501, USA

    Ron Elber

  4. Arrhenius Laboratory Division of Physical Chemistry, Stockholm University, 106 91, Stockholm, Sweden

    Aatto Laaksonen

  5. Laboratory of Biophysical Chemistry, University of Groningen, Nijenborgh 4, 9747 AG, Groningen, The Netherlands

    Alan Mark

  6. Department of Chemistry, Courant Institute of Mathematical Sciences, New York University, Mercer Street 251, New York, NY, 10012, USA

    Tamar Schlick

  7. FB Mathematik und Informatik, Freie Universität Berlin, Arnimallee 2-6, 14195, Berlin, Germany

    Christoph Schütte

  8. Department of Computer Science, Purdue University, N. University Street 250, West Lafayette, IN, 47907-2066, USA

    Robert Skeel

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Baker, N.A., Bashford, D., Case, D.A. (2006). Implicit Solvent Electrostatics in Biomolecular Simulation. In: Leimkuhler, B., et al. New Algorithms for Macromolecular Simulation. Lecture Notes in Computational Science and Engineering, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31618-3_15

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  • DOI: https://doi.org/10.1007/3-540-31618-3_15

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