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 (F) on the unbinding rate (k_off(F)) 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.

中文翻译：

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从力斜坡光学捕获分析计算生物大分子键的力依赖解结合率

构成蛋白质-蛋白质或蛋白质-配体相互作用的非共价生物键在许多细胞功能中起着至关重要的作用，包括有丝分裂、运动和细胞-细胞粘附。外力 ( F ) 对解结合率 ( k _off ( F ) 的影响)) 大分子相互作用是理解这些功能背后机制的关键参数。基于光镊的单分子力谱经常用于获得关于滑动、捕获和理想键的定量依赖于力的解离数据。然而，使用解离时间或解离力直方图对这些数据的分析通常会定量比较键，而不完全表征其潜在的生物物理特性。此外，基于直方图的分析结果可能取决于实验过程中施加力的速率和实验的灵敏度。在这里，我们提出了一种分析导出的累积分布函数类方法来分析与力相关的解离力谱数据。我们使用各种键类型的随机模拟来证明该技术的优点和局限性。我们表明，通过明确考虑加载速率和噪声数据，它可用于从力谱实验中获得生物大分子键的脱离率和力敏感性。我们还讨论了我们的结果对使用光镊收集依赖于力的解离数据的影响。