Deciphering the energy landscape of the interaction uranyl-DCP with antibodies using dynamic force spectroscopy

DeStripe: frequency-based algorithm for removing stripe noises from AFM images

Background

Atomic force microscopy (AFM) is a relatively recently developed technique that shows a promising impact in the field of structural biology and biophysics. It has been used to image the molecular surface of membrane proteins at a lateral resolution of one nanometer or less. An immediate obstacle of characterizing surface features in AFM images is stripe noise. To better interpret structures at a sub-domain level, pre-processing of AFM images for removing stripe noises is necessary. Noise removal can be performed in either spatial or frequency domain. However, denoising processing in the frequency domain is a better solution for preserving edge sharpness.

Results

We have developed a denoising protocol, called DeStripe, for AFM bio-molecular images that are contaminated with heavy and fine stripes. This program adopts a divide-and-conquer approach by dividing the Fourier spectrum of the image into central and off-center regions for noisy pixels detection and intensity restoration; it is also applicable to other images interfered with high-density stripes such as those acquired by the scanning electron microscope. The denoising effect brought by DeStripe provides better visualization for image objects without introducing additional artifacts into the restored image.

Conclusions

The DeStripe denoising effect on AFM images is illustrated in the present work. It allows extracting extended information from the topographic measurements and implicitly enhances the molecular features in the image. All the presented images were processed by DeStripe with the raw image as the only input without any requirement for other prior information. A web service, http://biodev.cea.fr/destripe, is available for running DeStripe.

Predicting the disruption by UO2(2+) of a protein-ligand interaction

The uranyl cation (UO(2) (2+)) can be suspected to interfere with the binding of essential metal cations to proteins, underlying some mechanisms of toxicity. A dedicated computational screen was used to identify UO(2) (2+) binding sites within a set of nonredundant protein structures. The list of potential targets was compared to data from a small molecules interaction database to pinpoint specific examples where UO(2) (2+) should be able to bind in the vicinity of an essential cation, and would be likely to affect the function of the corresponding protein. The C-reactive protein appeared as an interesting hit since its structure involves critical calcium ions in the binding of phosphorylcholine. Biochemical experiments confirmed the predicted binding site for UO(2) (2+) and it was demonstrated by surface plasmon resonance assays that UO(2) (2+) binding to CRP prevents the calcium-mediated binding of phosphorylcholine. Strikingly, the apparent affinity of UO(2) (2+) for native CRP was almost 100-fold higher than that of Ca(2+). This result exemplifies in the case of CRP the capability of our computational tool to predict effective binding sites for UO(2) (2+) in proteins and is a first evidence of calcium substitution by the uranyl cation in a native protein.