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NMR-Based Modeling and Refinement of Protein 3D Structures

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Molecular Modeling of Proteins

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

Abstract

NMR is a well-established method to characterize the structure and dynamics of biomolecules in solution. High-quality structures can now be produced thanks to both experimental advances and computational developments that incorporate new NMR parameters and improved protocols and force fields in the structure calculation and refinement process. In this chapter, we give a short overview of the various types of NMR data that can provide structural information, and then focus on the structure calculation methodology itself. We discuss and illustrate with tutorial examples “classical” structure calculation, refinement, and structure validation approaches.

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Authors and Affiliations

  1. Department of Structural Biology, VIB Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2, B-1050, Brussels, Belgium

    Wim F. Vranken

  2. Department of Biochemistry, School of Biological Sciences, University of Leicester, Henry Wellcome Building, Lancaster Road, Leicester, LE1 9HN, UK

    Geerten W. Vuister

  3. Faculty of Science—Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands

    Alexandre M. J. J. Bonvin

Authors
  1. Wim F. Vranken
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  2. Geerten W. Vuister
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  3. Alexandre M. J. J. Bonvin
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Corresponding author

Correspondence to Alexandre M. J. J. Bonvin .

Editor information

Editors and Affiliations

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

    Andreas Kukol

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Vranken, W.F., Vuister, G.W., Bonvin, A.M.J.J. (2015). NMR-Based Modeling and Refinement of Protein 3D Structures. 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_16

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  • DOI: https://doi.org/10.1007/978-1-4939-1465-4_16

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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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