Flexible Fitting to Infer Atomistic-Precision Models of Large-Amplitude Conformational Dynamics in Biomolecules from High-Speed Atomic Force Microscopy Imaging.

ABSTRACT: High-speed atomic force microscopy (HS-AFM) experiments allow direct observation of biomolecular dynamics at the single-molecule level, acquiring a large amount of topographic imaging data that visualizes changes in the molecular surface during functional activity over an extended period of time. Since images have no atomistic resolution, a major challenge has been to develop post-experimental computational methods to infer atomistic information from measurements. The recently developed NMFF-AFM flexible fitting method provides a computationally efficient approach promising to infer atomistic-precision models of conformational dynamics from resolution-limited AFM imaging data. We report the software integration of this method into the well-established BioAFMviewer platform and demonstrate its first applications to experimental HS-AFM imaging data. To facilitate applications, we developed a direct workflow from raw experimental AFM data to the visualization and analysis of fitting results. The presented applications to experimental data of a single protein domain, a protein complex, and a megadalton-sized protein filament demonstrate the versatility of NMFF-AFM modeling to reproduce large-amplitude conformational motions of biomolecular dynamics from HS-AFM imaging. As a first step toward automated large-scale analysis of AFM imaging data, we furthermore demonstrate reconstruction of an atomistic molecular movie of protein dynamics, involving large-amplitude conformational transitions, from a measured HS-AFM movie sequence. Implementation of flexible fitting within the stand-alone user-friendly interactive BioAFMviewer software provides the opportunity for a broad range of applications to facilitate the understanding of resolution-limited HS-AFM measurements.

SUBMITTER: Amyot R 

PROVIDER: S-EPMC12490010 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature