We provide a stand-alone software, the BioAFMviewer, which transforms biomolecular structures into the graphical representation corresponding to the outcome of atomic force microscopy (AFM) experiments. The AFM graphics is obtained by performing simulated scanning over the molecular structure encoded in the corresponding PDB file. A versatile molecular viewer integrates the visualization of PDB structures and control over their orientation, while synchronized simulated scanning with variable spatial resolution and tip-shape geometry produces the corresponding AFM graphics. We demonstrate the applicability of the BioAFMviewer by comparing simulated AFM graphics to high-speed AFM observations of proteins. The software can furthermore process molecular movies of conformational motions, e.g. those obtained from servers which model functional transitions within a protein, and produce the corresponding simulated AFM movie. The BioAFMviewer software provides the platform to employ the plethora of structural and dynamical data of proteins in order to help in the interpretation of biomolecular AFM experiments.
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.
We provide the BioAFMviewer-Toolbox, an extension of our previously developed software platform for simulated AFM scanning of biomolecular structures and dy- namics. The focus was on developing a toolbox of methods which employ simulated AFM scanning combined with quantitative analysis to facilitate the interpretation of resolution-limited AFM images. The key advancement is the automatized fitting of biomolecular structures to experimental AFM images, which allows to reconstruct 3D atomistic structures from AFM surface scans. Moreover, several methods for detailed analysis and comparison of surface topographies in simulated and experimental AFM images are provided. We demonstrate the applicability of the developed tools in the interpretation of high-speed AFM observations of proteins. The toolbox is implemented into the versatile interactive interface of the BioAFMviewer, which is a free software package available at www.bioafmviewer.com.
Atomic force microscopy (AFM) and high-speed AFM allow direct observation of biomolecular structures and their functional dynamics. Based on scanning the molecular surface of a sample deposited on a supporting substrate by a probing tip, topographic images of its dynamic shape are obtained. Critical to successful AFM observations is a balance between immobilization of the sample while avoiding too strong perturbations of its functional conformational dynamics. Since the sample placement on the supporting substrate cannot be directly controlled in experiments, the relative orientation is a priori unknown, and, due to limitations in the spatial resolution of images, difficult to infer from a posteriori analysis. We present a method to predict the macromolecular placement of samples based on electrostatic interactions with the AFM substrate and demonstrate applications to HS-AFM observations of the Cas9 endonuclease, an aptamer-protein complex, and the ClpB molecular chaperone. The model also allows predictions of imaging stability under tip-scanning. We implemented the developed method within the freely available BioAFMviewer software package. Therefore, predictions based on available structural data can be made even prior to an actual experiment.
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