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Protein complex prediction via verifying and reconstructing the topology of domain-domain interactions

DOI: 10.1186/1471-2105-11-350

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Here, we introduce a combinatorial approach for prediction of protein complexes focusing not only on determining member proteins in complexes but also on the DDI/PPI organization of the complexes. Our method analyzes complex candidates predicted by the existing methods. It searches for optimal combinations of domain-domain interactions in the candidates based on an assumption that the proteins in a candidate can form a true protein complex if each of the domains is used by a single protein interaction. This optimization problem was mathematically formulated and solved using binary integer linear programming. By using publicly available sets of yeast protein-protein interactions and domain-domain interactions, we succeeded in extracting protein complex candidates with an accuracy that is twice the average accuracy of the existing methods, MCL, MCODE, or clustering coefficient. Although the configuring parameters for each algorithm resulted in slightly improved precisions, our method always showed better precision for most values of the parameters.Our combinatorial approach can provide better accuracy for prediction of protein complexes and also enables to identify both direct PPIs and DDIs that mediate them in complexes.Recently developed high-throughput methods such as yeast two-hybrid or mass spectrometry to obtain protein-protein interactions (PPIs) have provided a global view of the interaction network [1-5]. As a PPI network grows, it becomes increasingly important to detect functional modules for understanding cellular organization and its dynamics [6]. Protein complexes are clusters of multiple proteins, and they often play a crucial part in basal cellular mechanism. Therefore, computational methods to predict protein complexes are becoming important.There are four steps in characterizing a protein complex [7]. The first step is to identify its member proteins. The second step is to determine its topology by identifying pairs of proteins which have direct inte

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