Structural pattern matching of nonribosomal peptides

S Caboche, M Pupin, V Leclère, P Jacques… - BMC structural …, 2009 - Springer
S Caboche, M Pupin, V Leclère, P Jacques, G Kucherov
BMC structural biology, 2009Springer
Abstract Background Nonribosomal peptides (NRPs), bioactive secondary metabolites
produced by many microorganisms, show a broad range of important biological activities (eg
antibiotics, immunosuppressants, antitumor agents). NRPs are mainly composed of amino
acids but their primary structure is not always linear and can contain cycles or branchings.
Furthermore, there are several hundred different monomers that can be incorporated into
NRPs. The N ORINE database, the first resource entirely dedicated to NRPs, currently stores …
Background
Nonribosomal peptides (NRPs), bioactive secondary metabolites produced by many microorganisms, show a broad range of important biological activities (e.g. antibiotics, immunosuppressants, antitumor agents). NRPs are mainly composed of amino acids but their primary structure is not always linear and can contain cycles or branchings. Furthermore, there are several hundred different monomers that can be incorporated into NRPs. The NORINE database, the first resource entirely dedicated to NRPs, currently stores more than 700 NRPs annotated with their monomeric peptide structure encoded by undirected labeled graphs. This opens a way to a systematic analysis of structural patterns occurring in NRPs. Such studies can investigate the functional role of some monomeric chains, or analyse NRPs that have been computationally predicted from the synthetase protein sequence. A basic operation in such analyses is the search for a given structural pattern in the database.
Results
We developed an efficient method that allows for a quick search for a structural pattern in the NORINE database. The method identifies all peptides containing a pattern substructure of a given size. This amounts to solving a variant of the maximum common subgraph problem on pattern and peptide graphs, which is done by computing cliques in an appropriate compatibility graph.
Conclusion
The method has been incorporated into the NORINE database, available at http://bioinfo.lifl.fr/norine . Less than one second is needed to search for a pattern in the entire database.
Springer
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