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Identifying drug-target proteins based on network features

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Abstract

Proteins rarely function in isolation inside and outside cells, but operate as part of a highly interconnected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action in terms of informatics. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interaction network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins in the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been demonstrated to be drug-target proteins in the literature.

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Authors and Affiliations

  1. School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China

    MingZhu Zhu, Lei Gao, Xia Li & ZhiCheng Liu

  2. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China

    Xia Li

Authors
  1. MingZhu Zhu
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  2. Lei Gao
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  3. Xia Li
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  4. ZhiCheng Liu
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Corresponding authors

Correspondence to Xia Li or ZhiCheng Liu.

Additional information

Supported by National Natural Science Foundation of China (Grant No. 30370798, 30571034 and 30570424), National High-Tech Research and Development Program of China (Grant No. 2007AA02Z329), National Basic Research Program of China (Grant No. 2008CB517302), Natural Science Foundation of Heilongjiang Province, China (Grant No. ZJG0501, 1055HG009, GB03C602-4 and BMFH060044), New Century Hundred-Thousand-Ten Thousand Talents Project of Beijing City, Scientific Research Common Program of Beijing Municipal Commission of Education (KM200610025011).

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Zhu, M., Gao, L., Li, X. et al. Identifying drug-target proteins based on network features. SCI CHINA SER C 52, 398–404 (2009). https://doi.org/10.1007/s11427-009-0055-y

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