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    Prediction of Biomolecular Complexes

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    Type
    Book Chapter
    Authors
    Vangone, Anna
    Oliva, Romina cc
    Cavallo, Luigi cc
    Bonvin, Alexandre M.J.J. cc
    KAUST Department
    Chemical Science Program
    KAUST Catalysis Center (KCC)
    Physical Science and Engineering (PSE) Division
    Date
    2017-04-13
    Online Publication Date
    2017-04-13
    Print Publication Date
    2017
    Permanent link to this record
    http://hdl.handle.net/10754/623894
    
    Metadata
    Show full item record
    Abstract
    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.
    Citation
    Vangone A, Oliva R, Cavallo L, Bonvin AMJJ (2017) Prediction of Biomolecular Complexes. From Protein Structure to Function with Bioinformatics: 265–292. Available: http://dx.doi.org/10.1007/978-94-024-1069-3_8.
    Sponsors
    AV was supported by Marie Skłodowska-Curie Individual Fellowship H2020 MSCA-IF-2015 [BAP-659025]. RO was supported by Regione Campania [LR5-AF2008].
    Publisher
    Springer Nature
    Journal
    From Protein Structure to Function with Bioinformatics
    DOI
    10.1007/978-94-024-1069-3_8
    Additional Links
    http://link.springer.com/chapter/10.1007/978-94-024-1069-3_8
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-94-024-1069-3_8
    Scopus Count
    Collections
    Physical Science and Engineering (PSE) Division; Chemical Science Program; KAUST Catalysis Center (KCC); Book Chapters

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