ArticleScientific reports2022
Calculating the force-dependent unbinding rate of biological macromolecular bonds from force-ramp optical trapping assays.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Long-range electrostatic interactions significantly modulate the affinity of dynein for microtubules.Biophysical journal · 2022Article
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Abstract
The non-covalent biological bonds that constitute protein-protein or protein-ligand interactions play crucial roles in many cellular functions, including mitosis, motility, and cell-cell adhesion. The effect of external force ([Formula: see text]) on the unbinding rate ([Formula: see text]) of macromolecular interactions is a crucial parameter to understanding the mechanisms behind these functions. Optical tweezer-based single-molecule force spectroscopy is frequently used to obtain quantitative force-dependent dissociation data on slip, catch, and ideal bonds. However, analyses of this data using dissociation time or dissociation force histograms often quantitatively compare bonds without fully characterizing their underlying biophysical properties. Additionally, the results of histogram-based analyses can depend on the rate at which force was applied during the experiment and the experiment's sensitivity. Here, we present an analytically derived cumulative distribution function-like approach to analyzing force-dependent dissociation force spectroscopy data. We demonstrate the benefits and limitations of the technique using stochastic simulations of various bond types. We show that it can be used to obtain the detachment rate and force sensitivity of biological macromolecular bonds from force spectroscopy experiments by explicitly accounting for loading rate and noisy data. We also discuss the implications of our results on using optical tweezers to collect force-dependent dissociation data.
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