de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Impressum Kontakt Einloggen
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Detection of protein catalytic residues at high precision using local network properties

MPG-Autoren

Slama,  Patrick
Max Planck Society;

Filippis,  Ioannis
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50406

Lappe,  Michael
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

1471-2105-9-517.pdf
(beliebiger Volltext), 1020KB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Slama, P., Filippis, I., & Lappe, M. (2008). Detection of protein catalytic residues at high precision using local network properties. BMC Bioinformatics, 9, 517-517. doi:10.1186/1471-2105-9-517.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-7E8F-D
Zusammenfassung
BACKGROUND: Identifying the active site of an enzyme is a crucial step in functional studies. While protein sequences and structures can be experimentally characterized, determining which residues build up an active site is not a straightforward process. In the present study a new method for the detection of protein active sites is introduced. This method uses local network descriptors derived from protein three-dimensional structures to determine whether a residue is part of an active site. It thus does not involve any sequence alignment or structure similarity to other proteins. A scoring function is elaborated over a set of more than 220 proteins having different structures and functions, in order to detect protein catalytic sites with a high precision, i.e. with a minimal rate of false positives. RESULTS: The scoring function was based on the counts of first-neighbours on side-chain contacts, third-neighbours and residue type. Precision of the detection using this function was 28.1%, which represents a more than three-fold increase compared to combining closeness centrality with residue surface accessibility, a function which was proposed in recent years. The performance of the scoring function was also analysed into detail over a smaller set of eight proteins. For the detection of 'functional' residues, which were involved either directly in catalytic activity or in the binding of substrates, precision reached a value of 72.7% on this second set. These results suggested that our scoring function was effective at detecting not only catalytic residues, but also any residue that is part of the functional site of a protein. CONCLUSION: As having been validated on the majority of known structural families, this method should prove useful for the detection of active sites in any protein with unknown function, and for direct application to the design of site-directed mutagenesis experiments.