Title

Functional annotation strategy for protein structures

Authors

Olivia Doppelt^{1, 2}, Fabrice Moriaud², Aurélie Bornot¹ & Alexandre G. de Brevern^1*

Affiliation

¹ Equipe de Bioinformatique Génomique et Moléculaire (EBGM), INSERM UMR-S 726, Université Denis Diderot - Paris 7, case 7113, 2, place Jussieu, 75251 Paris, France; ² MEDIT SA, 2 rue du Belvédère, 91120, Palaiseau, France

Email

alexandre.debrevern@ebgm.jussieu.fr

Phone

(33) 1 44 27 77 31;

Fax

(33) 1 43 26 38 30; * Corresponding author

Article Type

Views & Challenges

Date

received January 26, 2007; revised March 14, 2006; accepted March 14, 2006; published online March 15, 2007

Abstract

Whole-genome sequencing projects are a major source of unknown function proteins. However, as predicting protein function from sequence remains a difficult task, research groups recently started to use 3D protein structures and structural models to bypass it. MED-SuMo compares protein surfaces analyzing the composition and spatial distribution of specific chemical groups (hydrogen bond donor, acceptor, positive, negative, aromatic, hydrophobic, guanidinium, hydroxyl, acyl and glycine). It is able to recognize proteins that have similar binding sites and thus, may perform similar functions. We present here a fine example which points out the interest of MED-SuMo approach for functional structural annotation.

Keywords

annotation; function; protein structures; prediction

Citation

Edited by

B. Offmann

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.