Institut de Biologie StructuraleGrenoble / France

Contact person(s) related to this article / PELLEQUER Jean-Luc

Structural Bioinformatics

Structural bioinformatics is tools and methods allowing the prediction, characterization, and analysis of sequences and structures of macromolecules.

Adepth : A method to compute the depth of atoms in proteins.

Chen S.-w.W. and Pellequer J.-L. (2013) Adepth : new representation and its implications for atomic depths of macromolecules. Nucl. Acids Res. 41 : W412-W416.

Go to the Adepth website.

We applied the signed distance function (SDF) for representing the depths of atoms in a macromolecule. The calculations of SDF values were performed on grid points in a rectangular box that accommodates the macromolecule. The depth for an atom inside the molecule was then obtained as a result of tri-linear interpolation of SDF values at the nearest grid points surrounding the atom. Theoretical concept and computational development performed by Wendy Chen.

Adepth allows you to :

  • 1) Calculate accurately the depth of any atom within a macromolecular structure
  • 2) Provide an extrusion (skin) of a macromolecular structure
  • 3) Generate of pseudo-2D convolution map, highlighting the effect of AFM tips on single molecules

BridgeD : Prediction of the optimal insertion site of a disulfide bridge in a protein.

Pellequer J.-L. and Chen S.-w.W. (2006) Multi-template approach to modeling engineered disulfide bonds. Proteins 65 : 192-202.

Go to the BridgeD website.

There are three major reasons why the insertion of disulfide bridges into a protein is important :

  • To stabilize proteins against thermal denaturation - an approach often used in industrial biotechnology.
  • To study the internal dynamics of a protein by blocking an open / closed or active / inactive state, this approach has made it possible to study several molecular mechanisms such as the movement of transmembrane helices in response to a stimulus.
  • To link two domains or two proteins to one another, an approach often used to stabilize variable antibody fragments and for our projects on coagulation factors.
    Theoretical concept and computational development performed by Wendy Chen.

Destripe : A method to eliminate stripe noise from AFM images.

Chen S.-w.W. and Pellequer J.L. (2011) DeStripe : frequency-based algorithm for removing stripe noises from AFM images. BMC Struct. Biol. 11 : 7.

Go to the DeStripe website.

We have developed a stripe noise reduction protocol, called DeStripe, for single biomolecule images obtained by AFM that are contaminated by heavy and thin bands of vertical noise. To detect and restore noisy pixel, the program adopts a "divide and conquer" strategy by dividing the Fourier spectrum of the image into a central region and a peripheral region. The method is also applicable to other noisy images with high density bands such as those acquired by scanning electron microscopy. The noise reduction effect introduced by DeStripe allows for better visualization of objects without introducing additional artifacts into the restored image. Theoretical concept and development performed by Wendy Chen.

Example of image processing :

Raw image__________________Denoised image____________Noise image

Bepitope : Software for predicting B-cell epitopes

Bepitope is a computer tool for predicting the antigenic sites of a protein. Odorico M. and Pellequer J.-L. (2003) BEPITOPE : predicting the location of continuous epitopes and patterns in proteins. J. Mol. Recognit. 16 : 20-22. A modern version of the original PREDITOP tool : Pellequer J-L and Westhof E (1993) PREDITOP : a program for antigenicity predictions. J. Mol. Graph. 11 : 204-210.

An antigenic site is the region of a protein that is / will be recognized by an antibody molecule. The goal of Bepitope is to identify the antigenic sites of a protein that will tend to adopt the same cognate 3D structure once synthesized as a peptide.
Experimentally, once the region is identified, the peptide will be synthesized and then injected into the host to produce antibodies. Thanks to the phenomenon of the cross-reaction, the antibody recognizing the peptide will have the possibility of recognizing the parent protein from which the peptide is derived.
This is a big challenge in protein engineering because it is rare that a protein fragment, once synthesized as a peptide, adopts the same local 3D structure as that present in the structure of the entire protein. Nevertheless, it has been shown that peptides in solution often adopt a beta-strand structure.
The idea behind Bepitope’s Pellequer method is therefore to identify the regions in beta turn of a protein thus increasing the chances of cross reactions between an antipeptide antibody and the native parent protein.

The new online version of Bepitope is here >>>>>>>>>>>>> :

A tutorial will be provided soon.