BioAFMviewer software for simulation atomic force microscopy of molecular structures and conformational dynamics

Abstract

Atomic force microscopy (AFM) and high-speed scanning have significantly advanced real time observation of biomolecular dynamics, with applications ranging from single molecules to the cellular level. To facilitate the interpretation of resolution-limited imaging, post-experimental computational analysis plays an increasingly important role to understand AFM measurements. Data-driven simulation of AFM, computationally emulating experimental scanning, and automatized fitting has recently elevated the understanding of measured AFM topographies by inferring the underlying full 3D atomistic structures. Providing an interactive user-friendly interface for simulation AFM, the BioAFMviewer software has become an established tool within the Bio-AFM community, with a plethora of applications demonstrating how the obtained full atomistic information advances molecular understanding beyond topographic imaging. This graphical review illustrates the BioAFMviewer capacities and further emphasizes the importance of simulation AFM to complement experimental observations.

Fig. 1

Simulation AFM emulates experimental scanning to compute a surface topographic image of a biomolecular structure which can be compared to measured AFM images. The computation is based on non-elastic collisions of a rigid conical tip with a Van-der-Waals sphere atomic model of the molecular structure placed on a solid surface, calculating a height value for each cell along the scanning grid. In the simulated AFM topographic image, heights are illustrated by a color gradient. Central to the BioAFMviewer software is an integrated molecular viewer visualizing the loaded PDB structure in any 3D orientation and synchronized computation and visualization of the corresponding simulation AFM image (Live Simulation AFM). The spatial resolution of scanning, tip-shape parameters, and the visual representation can be conveniently adjusted.

Fig. 2

Automatized fitting to infer atomistic structures from resolution-limited experimental imaging. For a given PDB structure, simulation AFM can compute surface topographies of any possible molecular orientation, generating a library of simulated AFM images. The BioAFMviewer fitting module identifies the molecular structure whose simulated image matches best with an experimental target AFM image, quantified by an optimal image similarity score. A two-layered search strategy consisting of global unbiased sampling and refined iterative search ensures efficient automatized fitting taking typically only a few minutes on a laptop computer. Therefore, simulation AFM and automatized fitting within the BioAFMviewer allow to identify the atomistic structure behind measured resolution-limited AFM topographies.

Fig. 3

Applications to experimental AFM images. Automatized fitting was applied to obtain the 3D atomistic structures from experimental topographies ranging from single proteins and filaments to assemblies of 2D protein lattices. For the protein machines ClpB and rotor-less F1-ATPase the arrangement of functional domains can be disambiguated, and, even their nucleotide state can be inferred from HS-AFM topographies. Fitting an atomic model consisting of 24 actin subunits to a HS-AFM image of an actin filament demonstrates efficient fitting even for large proteins and allows to infer filament polarity. Application to HS-AFM imaging of lattices formed by protein channels in lipid bilayers allows to better understand their ligand-dependent activation mechanism. The atomic reconstruction from experimental imaging channels in their resting state versus activated state arrangement reveals differences of functional importance. While in their resting state configuration transmembrane domains of adjacent channels can form tight contact interfaces resulting in a quasi-static symmetric lattice, domains motions are much less restricted for channels in the ligand-induced activated state having a less ordered arrangement with larger separation of neighboring channels. Such information could not be deduced from AFM topographies since any transmembrane domain motions cannot be detected by the scanning tip. The ClpB HS-AFM image is adopted from (Uchihashi et al., 2018) and that of F1-ATPase is from (Ando et al., 2014).

Fig. 4

Topography Analysis Tools. A variety of tools allow quantitative topography analysis to validate experimental observations by employing simulation AFM and automatized fitting. Several applications where simulated topographies obtained after fitting are compared with measured images demonstrate a remarkable agreement. In case of the actin filament the spatial separation between individual monomers as well as the half-helical pitch of the periodic arrangement compare well. For the ClpB and rotor-less F1-ATPase protein machines height profiles show a well agreement of relative surface heights in simulated and HS-AFM images. Such applications demonstrate that by more detailed analysis, simulation AFM allows validation of experimental observations and quantitative feature assignment with measured topographies. A noteworthy observation is that absolute heights determined in simulated AFM topographies are systematically larger compared to measured topographies. This is due to the approximation of non-elastic tip-scanning with a rigid atomic model of the biomolecular structure, whereas experimental tip-scanning probes a deformable structure and is also invasive. Nonetheless, the agreement of relative heights of the scanned protein topographies is remarkable.

Fig. 5

Simulation AFM experiments. Available static structures can be employed in multi-scale molecular modelling to explore non-equilibrium functional conformational dynamics in proteins, thus providing high-resolution molecular movies of their operation cycles. In the BioAFMviewer simulation AFM of such molecular movies can be performed to produce computational AFM experiments. The top row shows consecutive snapshots from a molecular movie of a transmembrane transporter, visualizing conformational motions of the opening-closing transition which underlies the operation cycle. The molecular movie was obtained employing elastic-network based Brownian dynamics simulations (Oranella et al., 2016). The bottom row displays the corresponding topographic images of the simulated experiment in the same perspective.