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Tackling Sampling Challenges in Biomolecular Simulations

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Molecular Modeling of Proteins

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1215))

Abstract

Molecular dynamics (MD) simulations are a powerful tool to give an atomistic insight into the structure and dynamics of proteins. However, the time scales accessible in standard simulations, which often do not match those in which interesting biological processes occur, limit their predictive capabilities. Many advanced sampling techniques have been proposed over the years to overcome this limitation. This chapter focuses on metadynamics, a method based on the introduction of a time-dependent bias potential to accelerate sampling and recover equilibrium properties of a few descriptors that are able to capture the complexity of a process at a coarse-grained level. The theory of metadynamics and its combination with other popular sampling techniques such as the replica exchange method is briefly presented. Practical applications of these techniques to the study of the Trp-Cage miniprotein folding are also illustrated. The examples contain a guide for performing these calculations with PLUMED, a plugin to perform enhanced sampling simulations in combination with many popular MD codes.

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Acknowledgements

AB thanks the Swiss National Science Foundation for financial support under the Ambizione grant PZ00P2_136856. J. P. acknowledges the support of NSF award CMMI-1032368. The simulations of Trp-Cage miniprotein were made possible in part by the National Science Foundation through TeraGrid resources provided by NICS. These simulations were also facilitated through the use of computational, storage, and networking infrastructure provided by the Hyak supercomputer system, supported in part by the University of Washington eScience Institute.

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Authors and Affiliations

  1. Laboratory of Statistical Biophysics, School of Basic Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland

    Alessandro Barducci

  2. Department of Chemical Engineering, University of Washington, Seattle, WA, USA

    Jim Pfaendtner

  3. Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK

    Massimiliano Bonomi

Authors
  1. Alessandro Barducci
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  2. Jim Pfaendtner
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  3. Massimiliano Bonomi
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Corresponding author

Correspondence to Massimiliano Bonomi .

Editor information

Editors and Affiliations

  1. University of Hertfordshire, Hatfield, Hertfordshire, United Kingdom

    Andreas Kukol

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Barducci, A., Pfaendtner, J., Bonomi, M. (2015). Tackling Sampling Challenges in Biomolecular Simulations. In: Kukol, A. (eds) Molecular Modeling of Proteins. Methods in Molecular Biology, vol 1215. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1465-4_8

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  • DOI: https://doi.org/10.1007/978-1-4939-1465-4_8

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1464-7

  • Online ISBN: 978-1-4939-1465-4

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