Review
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?
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* Corresponding authors: Abraham I Louw braam.louw@bioagric.up.ac.za - Eric Maréchal eric.marechal@cea.fr
1 Department of Biochemistry and African Centre for Gene Technologies, Faculty of Natural and Agricultural Sciences, University of Pretoria, 0002, Pretoria, South Africa
2 UMR 5163 CNRS-Université Joseph Fourier, Laboratoire Adaptation et Pathogénie des Microorganismes, Institut Jean Roget, 38700, La Tronche, France
3 Bioinformatics and Computational Biology Unit, Faculty of Natural and Agricultural Sciences, University of Pretoria, 0002, Pretoria, South Africa
4 UMR 5168 CNRS-CEA-INRA-Université Joseph Fourier, Département Réponse et Dynamique Cellulaires; CEA Grenoble, 17 rue des Martyrs, 38054, Grenoble Cedex 09, France
5 Laboratoire de Physique Corpusculaire de Clermont-Ferrand, CNRS-IN2P3, Campus des Cézeaux, 63177 Aubière Cedex, France
6 Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53754 Sankt Augustin, Germany
7 Département d'Ecophysiologie Végétale et de Microbiologie; CEA Cadarache, 13108 Saint Paul-lez-Durance, France
8 UMR 5539 CNRS-Université Montpellier II, Place Eugène Bataillon, 34095 Montpellier cedex 05, France
9 Laboratoire de Biologie, Informatique et Mathématiques; Département Réponse et Dynamique Cellulaires; CEA Grenoble, 17 rue des Martyrs, F-38054, Grenoble cedex 09, France
Malaria Journal 2006, 5:110 doi:10.1186/1475-2875-5-110
Published: 17 November 2006Abstract
The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.