Automated identification of binding sites for phosphorylated ligands in protein structures

Dario Ghersi, Roberto Sanchez

Research output: Contribution to journalArticle

Abstract

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. Proteins 2012;.

Original languageEnglish (US)
Pages (from-to)2347-2358
Number of pages12
JournalProteins: Structure, Function and Bioinformatics
Volume80
Issue number10
DOIs
StatePublished - Oct 1 2012

Fingerprint

Binding Sites
Ligands
Proteins
Phosphopeptides
Mutagenesis
Phosphorylation
Protein Binding
Conservation
Adenosine Triphosphate
Experiments
Therapeutics

Keywords

  • Binding site
  • Docking
  • Function
  • Identification
  • Ligand
  • Pocket
  • Structure

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology

Cite this

Automated identification of binding sites for phosphorylated ligands in protein structures. / Ghersi, Dario; Sanchez, Roberto.

In: Proteins: Structure, Function and Bioinformatics, Vol. 80, No. 10, 01.10.2012, p. 2347-2358.

Research output: Contribution to journalArticle

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