Nanomechanics of Single Biomacromolecules


Single-molecule force spectroscopy has provided tremendous insights into the mechanical characteristics of biomacromolecules including proteins, nucleic acids, and sugars. This review provides the instrumentation framework for single-molecule force spectroscopy using atomic force microscopy and the experimental procedures for determining nanomechanics of biomacromolecules. The characteristic parameters determined by single-molecule force spectroscopy of proteins (unfolding forces, intrinsic unfolding/refolding rates, transition state distances, binding affinities), nucleic acids (elastic modulus, persistence length, overstretching percentages, plateau force levels), and sugars (force spectra) from the past 20 years are tabulated and their applications are discussed.

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Nanomechanics of Single Biomacromolecules
Book Title
Handbook of Nanomaterials Properties
Book DOI
Chapter DOI
Part of
  • Bharat Bhushan Send Email (1)
  • Dan Luo Send Email (2)
  • Scott R. Schricker Send Email (3)
  • Wolfgang Sigmund Send Email (4)
  • Stefan Zauscher Send Email (5)
  • Editor Affiliation
  • 1 Nanoprobe Laboratory for Bio- & Nanotechnology and Biomimetics, Ohio State University, Columbus, Ohio, USA
  • 2 Department of Biological and Environmental Engineering, Cornell University, Ithaca, New York, USA
  • 3 Division of Restorative, Prosthetic and Primary Care, The Ohio State University, College of Dentistry, Columbus, Ohio, USA
  • 4 Department of Materials Science and Engineering, University of Florida, Gainesville, Florida, USA
  • 5 Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina, USA
  • Authors
  • Qing Li Send Email (6)
  • Zackary N. Scholl Send Email (7)
  • Piotr E. Marszalek Send Email (6)
  • Author Affiliation
  • 6 Department of Mechanical Engineering and Materials Science, Center for Biologically Inspired Materials and Material Systems, and Duke University, 136 Hudson Hall/Box 90300, 27708-0287, Durham, NC, USA
  • 7 Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, 27708, USA
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