Q-SiteFinder

Q-SiteFinder: an energy-based method for the prediction of protein–ligand binding sites. Results: There is at least one successful prediction in the top three predicted sites in 90% of proteins tested when using Q-SiteFinder. This success rate is higher than that of a commonly used pocket detection algorithm (Pocket-Finder) which uses geometric criteria. Additionally, Q-SiteFinder is twice as effective as Pocket-Finder in generating predicted sites that map accurately onto ligand coordinates. It also generates predicted sites with the lowest average volumes of the methods examined in this study. Unlike pocket detection, the volumes of the predicted sites appear to show relatively low dependence on protein volume and are similar in volume to the ligands they contain. Restricting the size of the pocket is important for reducing the search space required for docking and de novo drug design or site comparison. The method can be applied in structural genomics studies where protein binding sites remain uncharacterized since the 86% success rate for unbound proteins appears to be only slightly lower than that of ligand-bound proteins. Availability: Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder

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References in zbMATH (referenced in 4 articles )

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  1. Kumari, Sweta; Mohana Priya, Arumugam; Lulu, Sajitha; Tauqueer, Mohammad: Molecular modeling, simulation and virtual screening of ribosomal phosphoprotein P1 from \textitPlasmodiumfalciparum (2014)
  2. Shinde, Sonali; Mol, Milsee; Jamdar, Virashree; Singh, Shailza: Molecular modeling and molecular dynamics simulations of GPI 14 in \textitLeishmaniamajor: insight into the catalytic site for active site directed drug design (2014)
  3. Ausiello, Gabriele; Gherardini, Pier Federico; Gatti, Elena; Incani, Ottaviano; Helmer-Citterich, Manuela: Structural motifs recurring in different folds recognize the same ligand fragments (2009) ioport
  4. Kalinina, Olga V.; Gelfand, Mikhail S.; Russell, Robert B.: Combining specificity determining and conserved residues improves functional site prediction (2009) ioport