Analysis of optical tweezers single-molecule force spectroscopy based on a signal-enhanced denoising model

Optical Tweezers-based Single-Molecule Force Spectroscopy enables nanoscale investigation of biological molecules but is plagued by noise that interferes with Force-Distance Curves (FDCs). This study presents an automated analysis method comprising a Sliding Slice Denoiser (SSD) and an FDC Analysis Module. The SSD employs adaptive segmentation and a neural network integrated with Inception blocks and Self-Attention modules for denoising, then reconstructs high signal‑to‑noise ratios (SNR) FDCs. The module performs folding event quantification, site localization, and Worm-Like Chain fitting to extract biophysical parameters. Tests on single-fold Deoxyribonucleic Acid (DNA) hairpins show improved SNR, with the distance signal increasing from 21.8 dB to 53.6 dB and the force signal from 30.9 dB to 53.2 dB. Mean Absolute Errors of fold site are low, at approximately 0.097 pN for force and 0.73 nm for distance, with Coefficient of Determination exceeding 0.97. For 1 to 6 folds simulated FDCs, the overall fold count prediction accuracy reaches 99%.