Simulation atomic force microscopy for atomic reconstruction of biomolecular structures from resolution-limited experimental images.
Romain AmyotArin MarchesiClemens M FranzIgnacio CasusoHolger FlechsigPublished in: PLoS computational biology (2022)
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.
Keyphrases
- atomic force microscopy
- single molecule
- high speed
- deep learning
- high resolution
- convolutional neural network
- living cells
- healthcare
- optical coherence tomography
- primary care
- molecular dynamics simulations
- computed tomography
- mental health
- magnetic resonance imaging
- machine learning
- artificial intelligence
- electronic health record
- mass spectrometry
- protein protein
- virtual reality
- binding protein
- contrast enhanced
- electron microscopy