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The Many Faces of Structure-Based Potentials: From Protein Folding Landscapes to Structural Characterization of Complex Biomolecules

Part of the Biological and Medical Physics, Biomedical Engineering book series (BIOMEDICAL)

Abstract

Structural biology techniques, such as nuclear magnetic resonance (NMR), x-ray crystallography, and cryogenic electron microscopy (cryo-EM), have provided extraordinary insights into the details of the functional configurations of biomolecular systems. Recent advances in x-ray crystallography and cryo-EM have allowed for structural characterization of large molecular machines such as the ribosome, proteasome, and spliceosome. This deluge of structural data has been complemented by experimental techniques capable of probing dynamic information, such as Förster resonance energy transfer (FRET) and stopped flow spectrometry. While these experimental studies have provided tremendous insights into the dynamics of biomolecular systems, it is often difficult to combine the low resolution dynamical data with the high-resolution structural data into a consistent picture. Computer simulation of these biomolecular systems bridges static structural data with dynamic experiments at atomic resolution (Fig. 1).

Keywords

  • Energy Landscape
  • Free Energy Barrier
  • Free Energy Landscape
  • Native Contact
  • Biomolecular System

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Acknowledgments

JKN would like to thank Joanna Sułkowska for many helpful discussions and Paul Whitford and Ryan Hayes for a careful reading of the chapter. This work was supported by the Center for Theoretical Biological Physics sponsored by the national science foundation (NSF) (Grant PHY-0822283) and NSF Grant NSF-MCB-1051438.

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Noel, J.K., Onuchic, J.N. (2012). The Many Faces of Structure-Based Potentials: From Protein Folding Landscapes to Structural Characterization of Complex Biomolecules. In: Dokholyan, N. (eds) Computational Modeling of Biological Systems. Biological and Medical Physics, Biomedical Engineering. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-2146-7_2

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