Modeling Protein Interacting Groups by Quasi-Bicliques: Complexity, Algorithm, and Application

• Published in: IEEE/ACM transactions on computational biology and bioinformatics Vol. 7; no. 2; pp. 354 - 364
• Main Authors: Liu, Xiaowen, Li, Jinyan, Wang, Lusheng
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2010; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Amino Acid Motifs; Amino Acid Sequence; Availability; Bioinformatics; Biological system modeling; Cells (biology); Computational Biology - methods; Computer science; Heuristic algorithms; interaction sites; Mass spectroscopy; Models, Chemical; Molecular Sequence Data; Polynomials; Protein engineering; Protein Interaction Mapping - methods; Protein Structure, Tertiary; Protein-protein interactions; Proteins - chemistry; quasi-bicliques; Sequences; NP-hardness; Quasi-bicliques; Protein interaction sites; PPI networks; Protein interacting groups; Algorithms
• ISSN: 1545-5963; 1557-9964
• DOI: 10.1109/TCBB.2008.61

Protein-protein interactions (PPIs) are one of the most important mechanisms in cellular processes. To model protein interaction sites, recent studies have suggested to find interacting protein group pairs from large PPI networks at the first step and then to search conserved motifs within the protein groups to form interacting motif pairs. To consider the noise effect and the incompleteness of biological data, we propose to use quasi-bicliquesior finding interacting protein group pairs. We investigate two new problems that arise from finding interacting protein group pairs: the maximum vertex quasi-biclique problem and the maximum balanced quasi-biclique problem. We prove that both problems are NP-hard. This is a surprising result as the widely known maximum vertex biclique problem is polynomial time solvable [1]. We then propose a heuristic algorithm that uses the greedy method to find the quasi-bicliques from PPI networks. Our experiment results on real data show that this algorithm has a better performance than a benchmark algorithm for identifying highly matched BLOCKS and PRINTS motifs. We also report results of two case studies on interacting motif pairs that map well with two interacting domain pairs in iPfam. Availability: The software and supplementary information are available at http://www.cs.cityu.edu.hk/~lwang/software/ppi/index.html.