A Fast Solution for Automated Single-Molecule Force Spectroscopy Data Collection and Processing

Abstract

AbstractForce spectroscopy is a sophisticated technology for studying the physical chemistry of polymers at the single-molecule level. Its implication in biomolecules, e.g., proteins, DNA or RNA, yielded tremendous information on their structures, folding, and functions. In a routine procedure, an experimenter pulls the molecule of interest to generate the force-extension (FE) curve using technologies that include atomic force microscopy (AFM), magnetic force spectroscopy (MFS), optical tweezer and acoustic force spectroscopy (AFS), then extract parameters characteristic to the polymer. The latter step requires fitting the FE curve with mathematical models. Although several models have been widely applied for over 20 years, the fitting of the experimental data was not as straightforward. This step can be time-consuming, prone to mistakes, and sometimes cause debate. To lower the technical barriers for users and to reduce the time consumption and errors involved in force spectroscopy data processing, we optimized the fitting procedure for three classical worm-like chain (WLC) models into an automated software package named Single Molecule Force Spectroscopy Toolkit (SMFST). Our MATLAB-based software with a graphical user interface demonstrated robust fitting for three models in a wide range of forces and provided convenient tools for batch data processing to meet future requirements of high-throughput data collection.