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Automated identification of binding sites forphosphorylated ligands in protein structures
  • Dario Ghersi, University of Nebraska at Omaha
  • Roberto Sanchez, Mount Sinai School of Medicine
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Phosphorylation is a crucial step in many cellular processes, ranging from metabolic reactions involved in energy transformation to signaling cascades. In many instances, protein domains specifically recognize the phosphogroup. Knowledge of the binding site provides insights into the interaction, and it can also be exploited for therapeutic purposes. Previous studies have shown that proteins interacting with phosphogroups are highly heterogeneous, and no single property can be used to reliably identify the binding site. Here we present an energy-based computational procedure that exploits the protein three-dimensional structure to identify binding sites involved in the recognition of phosphogroups. The procedure is validated on three datasets containing more than 200 proteins binding to ATP, phosphopeptides, and phosphosugars. A comparison against other three generic binding site identification approaches shows higher accuracy values for our method, with a correct identification rate in the 80–90% range for the top three predicted sites. Addition of conservation information further improves the performance. The method presented here can be used as a first step in functional annotation or to guide mutagenesis experiments and further studies such as molecular docking.


This is the peer reviewed version of the following article: Ghersi D, Sanchez R, “Automated Identification of Binding Sites for Phosphorylated Ligands in Protein Structures”, Proteins 2012, 80:2347-58, which has been published in final form at This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Citation Information
Dario Ghersi and Roberto Sanchez. "Automated identification of binding sites forphosphorylated ligands in protein structures" Proteins Vol. 80 Iss. 10 (2012) p. 2347 - 2358
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