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    Protein Model Docking Benchmark 2

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    Anishchenko_2015.pdf (2.196Mb)
    Issue Date
    2015-05
    Author
    Anishchenko, Ivan
    Kundrotas, Petras J.
    Tuzikov, Alexander V.
    Vakser, Ilya A.
    Publisher
    Wiley
    Type
    Article
    Article Version
    Scholarly/refereed, author accepted manuscript
    Rights
    This is the peer reviewed version of the following article: Proteins, which has been published in final form at http://dx.doi.org/10.1002/prot.24784. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
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    Abstract
    Structural characterization of protein-protein interactions is essential for our ability to understand life processes. However, only a fraction of known proteins have experimentally determined structures. Such structures provide templates for modeling of a large part of the proteome, where individual proteins can be docked by template-free or template-based techniques. Still, the sensitivity of the docking methods to the inherent inaccuracies of protein models, as opposed to the experimentally determined high-resolution structures, remains largely untested, primarily due to the absence of appropriate benchmark set(s). Structures in such a set should have pre-defined inaccuracy levels and, at the same time, resemble actual protein models in terms of structural motifs/packing. The set should also be large enough to ensure statistical reliability of the benchmarking results. We present a major update of the previously developed benchmark set of protein models. For each interactor, six models were generated with the model-to-native Cα RMSD in the 1 to 6 Å range. The models in the set were generated by a new approach, which corresponds to the actual modeling of new protein structures in the “real case scenario,” as opposed to the previous set, where a significant number of structures were model-like only. In addition, the larger number of complexes (165 vs. 63 in the previous set) increases the statistical reliability of the benchmarking. We estimated the highest accuracy of the predicted complexes (according to CAPRI criteria), which can be attained using the benchmark structures. The set is available at http://dockground.bioinformatics.ku.edu.
    URI
    http://hdl.handle.net/1808/23571
    DOI
    https://doi.org/10.1002/prot.24784
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    • Molecular Biosciences Scholarly Works [530]
    Citation
    Anishchenko, I., Kundrotas, P. J., Tuzikov, A. V., & Vakser, I. A. (2015). Protein Models Docking Benchmark 2. Proteins, 83(5), 891–897. http://doi.org/10.1002/prot.24784

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    KU Libraries
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    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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