부산대학교 도서관

Atomic force microscopy (AFM) can visualize the dynamics of single biomolecules under near-physiological conditions. However, the scanning tip probes only the molecular surface with limited resolution, missing details required to fully deduce functional mechanisms from imaging alone. To overcome such drawbacks, we developed a computational framework to reconstruct 3D atomistic structures from AFM surface scans, employing simulation AFM and automatized fitting to experimental images. We provide applications to AFM images ranging from single molecular machines, protein filaments, to large-scale assemblies of 2D protein lattices, and demonstrate how the obtained full atomistic information advances the molecular understanding beyond the original topographic AFM image. We show that simulation AFM further allows for quantitative molecular feature assignment within measured AFM topographies. Implementation of the developed methods into the versatile interactive interface of the BioAFMviewer software, freely available at www.bioafmviewer.com, presents the opportunity for the broad Bio-AFM community to employ the enormous amount of existing structural and modeling data to facilitate the interpretation of resolution-limited AFM images. Author summary: Atomic force microscopy (AFM) allows to visualize the dynamics of single biomolecules during their activity. All observations are, however, restricted to regions accessible by a fairly big probing tip during scanning. Hence, AFM images only the biomolecular surface with limited spatial resolution, missing important information required for a detailed understanding of the observed phenomena. We employ simulation atomic microscopy (sAFM), computationally emulating experimental scanning, to automatically fit available biomolecular structures into experimental AFM images. This allows to obtain 3D atomistic molecular structures from experimental AFM surface scans. For applications ranging from single molecular machines, protein filaments, to assemblies of protein lattices, we demonstrate how the full atomistic information advances the molecular understanding beyond experimental images. The developed computational methods are embedded within the user-friendly BioAFMviewer interactive software interface, providing the convenient platform for the Bio-AFM community to employ simulation AFM to better understand experimental results. [ABSTRACT FROM AUTHOR]