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    Blind prediction of interfacial water positions in CAPRI

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    Authors
    Lensink, Marc F.
    Moal, Iain H.
    Bates, Paul A.
    Kastritis, Panagiotis L.
    Melquiond, Adrien S.J.
    Karaca, Ezgi
    Schmitz, Christophe
    van Dijk, Marc
    Bonvin, Alexandre M.J.J.
    Eisenstein, Miriam
    Pierce, Brian G.
    Hwang, Howook
    Vreven, Thom
    Weng, Zhiping
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    UMass Chan Affiliations
    Program in Bioinformatics and Integrative Biology
    Document Type
    Journal Article
    Publication Date
    2014-04-01
    Keywords
    Algorithms
    Colicins
    Computational Biology
    Models, Molecular
    Molecular Docking Simulation
    Protein Conformation
    *Protein Interaction Mapping
    Water
    Biochemistry, Biophysics, and Structural Biology
    Bioinformatics
    Computational Biology
    Integrative Biology
    Systems Biology
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    Link to Full Text
    http://dx.doi.org/10.1002/prot.24439
    Abstract
    We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 A, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.
    Source
    Proteins. 2014 Apr;82(4):620-32. doi: 10.1002/prot.24439. Epub 2013 Nov 23. Link to article on publisher's site
    DOI
    10.1002/prot.24439
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/25920
    PubMed ID
    24155158
    Notes

    Full author list omitted for brevity. For the full list of authors, see article.

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    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1002/prot.24439
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