Glycosyltransferase prediction in Mycobacterium tuberculosis genome by threading

Varování

Publikace nespadá pod Pedagogickou fakultu, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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WIMMEROVÁ Michaela BETTLER Emmanuel IMBERTY Anne

Rok publikování 2002
Druh Článek ve sborníku
Konference 3rd International Symposium on Glycosyltransferases
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
Obor Biochemie
Klíčová slova glycosyltransferase; mycobacterium tuberculosis; threading
Popis Mycobacterium tuberculosis is a intracellular pathogen of the alveolar macrophages in lung resistant to most common antibiotics and chemotherapeutic agents. This resistance is related to its unusual and well-organized cell wall that contains the unique structures of branched and complex polysaccharides and glycolipids. The main cell wall constituents are known but there is only little information about the key enzymes in their biosynthesis, glycosyltransferases (GT). The genome of M. tuberculosis contains 3,951 protein-coding sequences. Putative function annotation of some of them was predicted using a combination of sequence alignment and motif comparison. Using this approach, only a small number of putative GTs was identified. Recently, only nine crystal structures of GTs have been solved. There is very low sequence similarity among them and they belong to different family groups. On the other hand, solving of their crystal structures demonstrated that they adopt only two basic 3D-folds We focused on 3D-topology identification of potential GTs in Mycobacterium spp. and applied the fold recognition method to the complete amino acid sequences encoded by M. tuberculosis (http://genolist.pasteur.fr/). The ProCeryon program based on calculation of mean force potentials was used for 3D-topology predictions with input parameters optimised on existing structures of GTs. The quality of final 122,481 models was evaluated by pseudo-energy calculation of residue-residue and/or residue-solvent interactions. Promising sequences that were predicted to adopt a GT fold by our approach were submitted to other bioinformatics analysis for further characterization.
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