Title

POINT: a database for the prediction of protein-protein interactions based on the orthologous interactome

Document Type

Article

Abstract

One possible path towards understanding the biological function of a target protein is through the discovery of how it interfaces within protein-protein interaction networks. The goal of this study was to create a virtual protein-protein interaction model using the concepts of orthologous conservation (or interologs) to elucidate the interacting networks of a particular target protein. POINT (the prediction of interactome database) is a functional database for the prediction of the human protein-protein interactome based on available orthologous interactome datasets. POINT integrates several publicly accessible databases, with emphasis placed on the extraction of a large quantity of mouse, fruit fly, worm and yeast protein-protein interactions datasets from the Database of Interacting Proteins (DIP), followed by conversion of them into a predicted human interactome. In addition, protein-protein interactions require both temporal synchronicity and precise spatial proximity. POINT therefore also incorporates correlated mRNA expression clusters obtained from cell cycle microarray databases and subcellular localization from Gene Ontology to further pinpoint the likelihood of biological relevance of each predicted interacting sets of protein partners.

Medical Subject Headings

Animals; Database Management Systems; Databases, Protein; Drosophila Proteins (chemistry, metabolism); Evolution, Molecular; Humans; Information Storage and Retrieval (methods); Internet; Mice; Protein Interaction Mapping (methods); Proteome (chemistry, metabolism); Saccharomyces cerevisiae Proteins (chemistry, metabolism); Sequence Alignment (methods); Sequence Analysis, Protein (methods); Signal Transduction (physiology); User-Computer Interface

Publication Date

11-22-2004

Publication Title

Bioinformatics (Oxford, England)

ISSN

1367-4803

Volume

20

Issue

17

First Page

3273

Last Page

6

PubMed ID

15217821

Digital Object Identifier (DOI)

10.1093/bioinformatics/bth366

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