Objectif
Since the completion of the human and other organisms' genome sequence, many new druggable targets are expected to be identified by structural genomics with the expectation of developing new therapeutics. One of the bottlenecks of this drug discovery process is the difficulties encountered to understand the function of these new proteins. So far, much emphasis has been given to bioinformatics: the genomes are annotated using sequence analysis or structural modelling. However, these methods are not always applicable or relevant.
This proposal suggests to investigate methods derived from chemoinformatics. Specifically, chemogenomics implies that the function of a protein can be derived from the structure of the sets of ligands that bind to it. By comparing the pair-wise similarity of these sets of compounds to random distributions, statistical models can be used to compute scores between pairs of sets. These scores are then used to build chemical relationship maps, i.e. ontology of the ligands. These maps could be used alternatively or complementarily to other classifications to annotate the genomes.
Champ scientifique
- medical and health sciencesbasic medicinepharmacology and pharmacydrug discovery
- natural sciencescomputer and information sciencesknowledge engineeringontology
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- natural sciencesmathematicsapplied mathematicsstatistics and probability
- natural sciencesbiological sciencesgeneticsgenomes
Mots‑clés
Appel à propositions
FP6-2005-MOBILITY-6
Voir d’autres projets de cet appel