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Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information

  1. Author:
    Tuncbag, Nurcan
    Keskin, Ozlem
    Nussinov, Ruth
    Gursoy, Attila

  2. Author Address

    Graduate School of Informatics, Department of Health Informatics, Middle East Technical University, 06800, Ankara, Turkey., Chemical and Biological Engineering, College of Engineering, Koc University, 34450, Istanbul, Turkey. okeskin@ku.edu.tr., Center for Computational Biology and Bioinformatics, Koc University, Rumelifeneri Yolu Sariyer, 34450, Istanbul, Turkey. okeskin@ku.edu.tr., Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory, National Cancer Institute, Frederick, MD, 21702, USA., Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Sackler Institute of Molecular Medicine, Tel Aviv University, Tel Aviv, 69978, Israel., Center for Computational Biology and Bioinformatics, Koc University, Rumelifeneri Yolu Sariyer, 34450, Istanbul, Turkey. agursoy@ku.edu.tr., Computer Engineering, College of Engineering, Koc University, 34450, Istanbul, Turkey. agursoy@ku.edu.tr.,
    1. Year: 2017
    2. Epub Date: 02 Feb 2017
  2. Journal: Methods in molecular biology (Clifton, N.J.)
    1. 1558
    2. Pages: 255-270
  4. Type of Article: Article
  5. ISSN: 978-1-4939-6781-0
  1. Abstract:

    Structural details of protein interactions are invaluable to the understanding of cellular processes. However, the identification of interactions at atomic resolution is a continuing challenge in the systems biology era. Although the number of structurally resolved complexes in the Protein Databank increases exponentially, the complexes only cover a small portion of the known structural interactome. In this chapter, we review the PRISM system that is a protein-protein interaction (PPI) prediction tool-its rationale, principles, and applications. We further discuss its extensions to discover the effect of single residue mutations, to model large protein assemblies, to improve its performance by exploiting conformational protein ensembles, and to reconstruct large PPI networks or pathway maps.

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External Sources

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  2. DOI: 10.1007/978-1-4939-6783-4_12
  3. PMID: 28150242
  4. View record in Web of Science®
  5. WOS: 000430676400013

Library Notes

  1. Fiscal Year: FY2016-2017

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