Rigid-body fitting to atomic force microscopy images for inferring probe shape and biomolecular structure

Abstract

Atomic force microscopy (AFM) can visualize functional biomolecules near the physiological condition, but the observed data are limited to the surface height of specimens. Since the AFM images highly depend on the probe tip shape, for successful inference of molecular structures from the measurement, the knowledge of the probe shape is required, but is often missing. Here, we developed a method of the rigid-body fitting to AFM images, which simultaneously finds the shape of the probe tip and the placement of the molecular structure via an exhaustive search. First, we examined four similarity scores via twin-experiments for four test proteins, finding that the cosine similarity score generally worked best, whereas the pixel-RMSD and the correlation coefficient were also useful. We then applied the method to two experimental high-speed-AFM images inferring the probe shape and the molecular placement. The results suggest that the appropriate similarity score can differ between target systems. For an actin filament image, the cosine similarity apparently worked best. For an image of the flagellar protein FlhAC, we found the correlation coefficient gave better results. This difference may partly be attributed to the flexibility in the target molecule, ignored in the rigid-body fitting. The inferred tip shape and placement results can be further refined by other methods, such as the flexible fitting molecular dynamics simulations. The developed software is publicly available.

Simulation atomic force microscopy for atomic reconstruction of biomolecular structures from resolution-limited experimental images

“…We note that the Global Search method is similar to that recently reported for the rigid-body fitting to HS-AFM data [ 19 ]. In that regard, our independent work distinguishes itself by the convenient implementation into the user-friendly BioAFMviewer software interface (see Discussion ).…”

“…Parameters characterizing the tip shape should play a role in the optimization process of finding the best match between simulation and experimental AFM image. Recent studies of structural fitting to AFM images showed that optimal parameters can be determined only within a margin of uncertainty [ 19 , 24 ], which is due to the limited resolution of the imaging method. Within the BioAFMviewer interface the user can easily modify the tip-shape and observe the immediate effect on the computed AFM image, and, as we have shown previously, simulation AFM images which remarkably well reproduce experimental AFM images can thus be obtained [ 16 ].…”

“…For the much faster Quick Fit algorithm, however, we allow to perform independent runs, each time with a different combination of probe radius and cone angle varied around the preset tip shape. In this report we will not elaborate on the effect of the tip-shape on fitting, as this was systematically explored previously [ 19 , 24 ].…”

“…The simulated scanning method computationally emulates scanning of the molecular structure to produce pseudo AFM images. It has been employed in several studies to interpret experimental AFM images of proteins [8,[17][18][19][20][21][22], and in molecular simulations of flexible fitting biomolecular structures to experimental images [23] or to deduce information on the AFM tip shape [24].…”

Simulation atomic force microscopy to predict correlated conformational dynamics in proteins from topographic imaging

“…4 ), the experimental realization is highly challenging. On the other side, computational approaches including molecular modelling and simulations are inreasingly used to assist in understanding biomolecular high-speed AFM measurements [5][6][7][8] .…”