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Proteins. 2012 Jul;80(7):1736-43. doi: 10.1002/prot.24066. Epub 2012 Apr 13.

Protein-protein interaction network-based detection of functionally similar proteins within species.

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MOA Key Laboratory of Animal Biotechnology of National Ministry of Agriculture, Institute of Veterinary Immunology, Division of Veterinary Microbiology & Virology, Department of Preventive Veterinary Medicine, College of Veterinary Medicine, and Investigation Group of Molecular Virology, Immunology, Oncology & Systems Biology, Center for Bioinformatics, Northwest A & F University, Yangling 712100, Xi'an City, Shaanxi Province, People's Republic of China.


Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent.

[Indexed for MEDLINE]

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