An integrated methodology for data processing in dynamic force spectroscopy of ligand–receptor binding

Dynamic force spectroscopy (DFS), using atomic force microscopy (AFM), is a powerful tool to study ligand–receptor binding. The interaction mode of two binding partners is investigated by exploring stochastic behaviors of bond rupture events. However, to define a rupture event from force–distance measurements is not conclusive or unique in literature. To reveal the influence of event identification methods, we have developed an efficient protocol to manage tremendous amount of data by implementing different choices of peak selection from the force–distance curve. This data processing software simplifies routinely experimental procedures such as cantilever spring constant and force–distance curve calibrations, statistical treatments of data, and analysis distributions of rupture events. In the present work, we took available experimental data from a complex between a chelate metal compound and a monoclonal antibody as a study system.