Interaction site prediction by structural similarity to neighboring clusters in protein-protein interaction networks.

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 Bioinformatics

journal_title

BMC bioinformatics

authors

Monji H,Koizumi S,Ozaki T,Ohkawa T

doi

10.1186/1471-2105-12-S1-S39

subject

Has Abstract

pub_date

2011-02-15 00:00:00

pages

S39

issn

1471-2105

pii

1471-2105-12-S1-S39

journal_volume

12 Suppl 1

pub_type

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