Lawrence Livermore National Laboratory



LLNL BES Program Highlight


Scientific Achievement

A unified model of bond strength across multiple timescales.

Significance and Impact

This is the first-ever demonstration that the equilibrium free energy can be determined by single molecule force spectroscopy.

Research Details

  • Model describes a seamless transition between near-equilibrium and far-form-equilibrium rupture regimes
  • We verified the model predictions in BD simulations and in an experiment
  • Data from 10 different experimental system show the transition predicted by the model; all data fall on the same natural linear trend predicted by the model
Photo of Alex Noy

Alex Noy

noy1@llnl.gov  

Principal Investigator for the Extraction of Equilibrium Energy and Kinetic Parameters from Single Molecule Force Spectroscopy Data

Dynamic strength data for 10 different biological bonds fitted by the model

R.W. Friddle, A. Noy, J.J. De Yoreo, Interpreting the widespread nonlinear force spectra of intermolecular bonds, Proc. Nat'l. Acad. Sci. U.S.A. 109, 13573-13578 (2012).

Research Summary

Single molecule force spectroscopy always was an attractive method for probing intermolecular bonds, but getting real quantitative information has been difficult. The situation improved with development of dynamic force spectroscopy by E. Evans. Force spectroscopy has always been an important characterization technique for this project; therefore, our team put in an effort to make the technique more quantitative. First we demonstrated the existence of a near-equilibrium regime for probing the bond strength, which allowed direct determination o the bond free energy. Finally, we have developed a model that (a) connected near-equilibrium regime with the far-from-equilibrium regime typical for dynamic force spectroscopy measurements; and (b) showed that it is possible to extract all relevant kinetic and thermodynamic bond parameters from a single force spectroscopy measurement. Finally, we verified the model in an experiment. We also showed that the model fits the literature data from 10 different systems, and the data from all 10 systems fall onto a single linear trendline predicted by the model.