Abstract:
BACKGROUND:Recently, revealing the function of proteins with protein-protein interaction (PPI) networks is regarded as one of important issues in bioinformatics. With the development of experimental methods such as the yeast two-hybrid method, the data of protein interaction have been increasing extremely. Many databases dealing with these data comprehensively have been constructed and applied to analyzing PPI networks. However, few research on prediction interaction sites using both PPI networks and the 3D protein structures complementarily has explored. RESULTS:We propose a method of predicting interaction sites in proteins with unknown function by using both of PPI networks and protein structures. For a protein with unknown function as a target, several clusters are extracted from the neighboring proteins based on their structural similarity. Then, interaction sites are predicted by extracting similar sites from the group of a protein cluster and the target protein. Moreover, the proposed method can improve the prediction accuracy by introducing repetitive prediction process. CONCLUSIONS:The proposed method has been applied to small scale dataset, then the effectiveness of the method has been confirmed. The challenge will now be to apply the method to large-scale datasets.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Monji H,Koizumi S,Ozaki T,Ohkawa Tdoi
10.1186/1471-2105-12-S1-S39subject
Has Abstractpub_date
2011-02-15 00:00:00pages
S39issn
1471-2105pii
1471-2105-12-S1-S39journal_volume
12 Suppl 1pub_type
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