mkgridXf : Consistent Identification of Plausible Binding Sites Despite the Elusive Nature of Cavities and Grooves in Protein Dynamics - Institut Pasteur Accéder directement au contenu
Article Dans Une Revue Journal of Chemical Information and Modeling Année : 2019

mkgridXf : Consistent Identification of Plausible Binding Sites Despite the Elusive Nature of Cavities and Grooves in Protein Dynamics

Résumé

We describe here a method to identify potential binding sites in ensembles of protein structures as obtained by molecular dynamics simulations. This is a highly important task in the context of structure based drug discovery, and many methods exist for the much simpler case of static structures. However , during molecular dynamics, the cavities and grooves that are used to define binding sites merge, split, appear and disappear, and cover a large volume. Combined with the large number of sites (∼10 5 and more) these characteristics hamper a consistent and comprehensive definition of binding sites. Our method is based on the calculation of instantaneous cavities and of the pockets delineating them. Classification of the pockets over the structure ensemble generates consensus pockets, which define sites. Sites are reported as lists of atoms or residues. This avoids the pitfalls of the classification of cavities by spatial overlap, used in most existing methods, which is bound to fail on non-ordered or unaligned ensembles, or as soon as significant molecular motions are involved. To achieve a robust and consistent classification we thoroughly optimized and benchmarked the method. For this we assembled from the literature a set of reference sites on systems involving significant functional molecular motions. We tested different descriptors, metrics and clustering methods. The resulting method is able to perform a global analysis of potential sites efficiently. Tests on examples show that our approach can make predictions of potential sites on the whole surface of a protein, and identify novel sites absent from static structures.
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Dates et versions

pasteur-02503276 , version 1 (09-03-2020)

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Damien Monet, Nathan Desdouits, Michael Nilges, Arnaud Blondel. mkgridXf : Consistent Identification of Plausible Binding Sites Despite the Elusive Nature of Cavities and Grooves in Protein Dynamics. Journal of Chemical Information and Modeling, 2019, 59 (8), pp.3506-3518. ⟨10.1021/acs.jcim.9b00103⟩. ⟨pasteur-02503276⟩
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