Figure 4.

Malaria chemogenomics: organization and treatment of genomic, post-genomic and chemical information for the prediction and characterization of target and drug candidates. Genomic data from Plasmodium and other species (a), i.e. protein sequences, should be organized based on sequence similarity (b). This projection should allow the high throughput reconstruction of molecular phylogenies both at the intraspecific (connecting paralogs and alleles) and interspecific (connecting homologues among which orthologs) levels following statistically accurate methods e.g. the TULIP method. Another substantial side of the biological space is designed by representing the knowledge of the biological processes, using stable ontologies e.g. the GO, and dynamic graph representation, e.g. PlasmoCyc (c). Versatile tools should allow the integration of genomic data, biological process representations and global functional profiles obtained with diverse X-omic approaches (4). These tools should comply with the large diversity of technologies and mining methods. The collection of information on the biological response to drugs is one of the doors to connect the biological space with the chemical space, following the "reverse chemical genetic" way, i.e. "from known drugs to biological response" (toxicity, mode of action). The other door to connect the chemical space and the biological space follows the "direct chemical genetic" way, i.e. "from known biological target to drug candidates". In addition to malaria protein structures obtained from crystals, the automated structural annotation of the malaria proteome should be initiated with quality scores (e). Based on protein structure information, virtual docking campaigns such as the WISDOM challenges can be achieved using the power of computer grids. The in silico organization of the small molecules stored in chemolibraries (f) follows similar principles, in particular the determination of three-dimensional structures of small molecules (g) and a clustering of small molecular structures based on drug properties and descriptors (h). Sharing and mining of chemogenomic information, completed with knowledge harvested in unstructured scientific literature, would benefit of the advances in knowledge space design and deployment on knowledge grids.