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Metadynamics to Enhance Sampling in Biomolecular Simulations

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Biomolecular Simulations

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2022))

Abstract

Molecular dynamics is a powerful simulation method to provide detailed atomic-scale insight into a range of biological processes including protein folding, biochemical reactions, ligand binding, and many others. Over the last several decades, enhanced sampling methods have been developed to address the large separation in time scales between a molecular dynamics simulation (usually microseconds or shorter) and the time scales of biological processes (often orders of magnitude longer). This chapter specifically focuses on the metadynamics family of methods, which achieves enhanced sampling through the introduction of a history-dependent bias potential that is based on one or more slow degrees of freedom, called collective variables. We introduce the method and its recent variants related to biomolecular studies and then discuss frontier areas of the method. A large part of this chapter is devoted to helping new users of the method understand how to choose metadynamics parameters properly and apply the method to their system of interest.

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Acknowledgement

The author gratefully acknowledges the help of Kayla Sprenger and Sarah Alamdari in providing detailed feedback on a draft of this chapter.

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Authors and Affiliations

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

    Jim Pfaendtner

  2. Pacific Northwest National Laboratory, Richland, WA, USA

    Jim Pfaendtner

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  1. Jim Pfaendtner
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Correspondence to Jim Pfaendtner .

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Editors and Affiliations

  1. Structural Bioinformatics Unit, Institut Pasteur, CNRS UMR 3528, Paris, France

    Massimiliano Bonomi

  2. Dipartimento di Bioscienze, Università degli Studi di Milano, Milano, Italy

    Carlo Camilloni

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Pfaendtner, J. (2019). Metadynamics to Enhance Sampling in Biomolecular Simulations. In: Bonomi, M., Camilloni, C. (eds) Biomolecular Simulations. Methods in Molecular Biology, vol 2022. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9608-7_8

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  • DOI: https://doi.org/10.1007/978-1-4939-9608-7_8

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