© 2006

New Algorithms for Macromolecular Simulation

  • Benedict Leimkuhler
  • Christophe Chipot
  • Ron Elber
  • Aatto Laaksonen
  • Alan Mark
  • Tamar Schlick
  • Christoph Schütte
  • Robert Skeel

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

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Macromolecular Models: From Theories to Effective Algorithms

    1. Front Matter
      Pages 1-1
    2. Peter J. Bond, Jonathan Cuthbertson, Sundeep S. Deol, Lucy R. Forrest, Jennifer Johnston, George Patargias et al.
      Pages 3-20
    3. Marc Q. Ma, Kentaro Sugino, Yu Wang, Narain Gehani, Annie V. Beuve
      Pages 21-34
    4. Thorsten Joachims, Tamara Galor, Ron Elber
      Pages 57-69
  3. Minimization of Complex Molecular Landscapes

    1. Front Matter
      Pages 71-71
    2. David J. Wales, Joanne M. Carr, Tim James
      Pages 73-87
    3. H. A. Scheraga, A. Liwo, S. Oldziej, C. Czaplewski, J. Pillardy, J. Lee et al.
      Pages 89-100
  4. Dynamical and Stochastic-Dynamical Foundations for Macromolecular Modelling

    1. Front Matter
      Pages 101-101
    2. Scott S. Hampton, Paul Brenner, Aaron Wenger, Santanu Chatterjee, Jesús A. Izaguirre
      Pages 103-123
    3. Eric Barth, Ben Leimkuhler, Chris Sweet
      Pages 125-140
    4. Elena Akhmatskaya, Sebastian Reich
      Pages 141-153
    5. Reinier L. C. Akkermans
      Pages 155-165
    6. Wilhelm Huisinga, Bernd Schmidt
      Pages 167-182
  5. Computation of the Free Energy

    1. Front Matter
      Pages 183-183
    2. Christopher J. Woods, Michael A. King, Jonathan W. Essex
      Pages 251-259
  6. Fast Electrostatics and Enhanced Solvation Models

    1. Front Matter
      Pages 261-261

About this book


Molecular simulation is a widely used tool in biology, chemistry, physics and engineering. This book contains a collection of articles by leading researchers who are developing new methods for molecular modelling and simulation. Topics addressed here include: multiscale formulations for biomolecular modelling, such as quantum-classical methods and advanced solvation techniques; protein folding methods and schemes for sampling complex landscapes; membrane simulations; free energy calculation; and techniques for improving ergodicity. The book is meant to be useful for practitioners in the simulation community and for those new to molecular simulation who require a broad introduction to the state of the art.


Monte Carlo Potential algorithms biology biomolecular simulation chemistry enzymes genome macromolecular modeling modeling molecular modelling protein protein folding simulation

Editors and affiliations

  • Benedict Leimkuhler
    • 1
  • Christophe Chipot
    • 2
  • Ron Elber
    • 3
  • Aatto Laaksonen
    • 4
  • Alan Mark
    • 5
  • Tamar Schlick
    • 6
  • Christoph Schütte
    • 7
  • Robert Skeel
    • 8
  1. 1.Department of MathematicsUniversity of LeicesterLeicesterUK
  2. 2.Institut nancéien de chimie moléculaireUniversité Henri Poincaré - Nancy IVandoeuvre-lès-NancyFrance
  3. 3.Department of Computer ScienceCornell UniversityIthacaUSA
  4. 4.Arrhenius Laboratory Division of Physical ChemistryStockholm UniversityStockholmSweden
  5. 5.Laboratory of Biophysical ChemistryUniversity of GroningenGroningenThe Netherlands
  6. 6.Department of Chemistry, Courant Institute of Mathematical SciencesNew York UniversityNew YorkUSA
  7. 7.FB Mathematik und InformatikFreie Universität BerlinBerlinGermany
  8. 8.Department of Computer SciencePurdue UniversityWest LafayetteUSA

Bibliographic information