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eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models

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  • Michal Brylinski

Abstract

Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4–9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.

Suggested Citation

  • Michal Brylinski, 2014. "eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-15, September.
  • Handle: RePEc:plo:pcbi00:1003829
    DOI: 10.1371/journal.pcbi.1003829
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    References listed on IDEAS

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    1. Leif Ellingson & Jinfeng Zhang, 2012. "Protein Surface Matching by Combining Local and Global Geometric Information," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-14, July.
    2. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
    3. Michal Brylinski & Daswanth Lingam, 2012. "eThread: A Highly Optimized Machine Learning-Based Approach to Meta-Threading and the Modeling of Protein Tertiary Structures," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-12, November.
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