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SPPS: A Sequence-Based Method for Predicting Probability of Protein-Protein Interaction Partners

Author

Listed:
  • Xinyi Liu
  • Bin Liu
  • Zhimin Huang
  • Ting Shi
  • Yingyi Chen
  • Jian Zhang

Abstract

Background: The molecular network sustained by different types of interactions among proteins is widely manifested as the fundamental driving force of cellular operations. Many biological functions are determined by the crosstalk between proteins rather than by the characteristics of their individual components. Thus, the searches for protein partners in global networks are imperative when attempting to address the principles of biology. Results: We have developed a web-based tool “Sequence-based Protein Partners Search” (SPPS) to explore interacting partners of proteins, by searching over a large repertoire of proteins across many species. SPPS provides a database containing more than 60,000 protein sequences with annotations and a protein-partner search engine in two modes (Single Query and Multiple Query). Two interacting proteins of human FBXO6 protein have been found using the service in the study. In addition, users can refine potential protein partner hits by using annotations and possible interactive network in the SPPS web server. Conclusions: SPPS provides a new type of tool to facilitate the identification of direct or indirect protein partners which may guide scientists on the investigation of new signaling pathways. The SPPS server is available to the public at http://mdl.shsmu.edu.cn/SPPS/.

Suggested Citation

  • Xinyi Liu & Bin Liu & Zhimin Huang & Ting Shi & Yingyi Chen & Jian Zhang, 2012. "SPPS: A Sequence-Based Method for Predicting Probability of Protein-Protein Interaction Partners," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-6, January.
    • Handle: RePEc:plo:pone00:0030938
    DOI: 10.1371/journal.pone.0030938
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    References listed on IDEAS

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    1. Guilherme T Valente & Marcio L Acencio & Cesar Martins & Ney Lemke, 2013. "The Development of a Universal In Silico Predictor of Protein-Protein Interactions," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-11, May.

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