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Predicting the disruption by UO2(2+) of a protein-ligand interaction.

ABSTRACT: The uranyl cation (UO(2) (2+)) can be suspected to interfere with the binding of essential metal cations to proteins, underlying some mechanisms of toxicity. A dedicated computational screen was used to identify UO(2) (2+) binding sites within a set of nonredundant protein structures. The list of potential targets was compared to data from a small molecules interaction database to pinpoint specific examples where UO(2) (2+) should be able to bind in the vicinity of an essential cation, and would be likely to affect the function of the corresponding protein. The C-reactive protein appeared as an interesting hit since its structure involves critical calcium ions in the binding of phosphorylcholine. Biochemical experiments confirmed the predicted binding site for UO(2) (2+) and it was demonstrated by surface plasmon resonance assays that UO(2) (2+) binding to CRP prevents the calcium-mediated binding of phosphorylcholine. Strikingly, the apparent affinity of UO(2) (2+) for native CRP was almost 100-fold higher than that of Ca(2+). This result exemplifies in the case of CRP the capability of our computational tool to predict effective binding sites for UO(2) (2+) in proteins and is a first evidence of calcium substitution by the uranyl cation in a native protein.

SUBMITTER: Pible O

PROVIDER: S-EPMC3005792 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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Predicting the disruption by UO2(2+) of a protein-ligand interaction.

Pible Olivier O Vidaud Claude C Plantevin Sophie S Pellequer Jean-Luc JL Quéméneur Eric E

Protein science : a publication of the Protein Society 20101101 11

The uranyl cation (UO(2) (2+)) can be suspected to interfere with the binding of essential metal cations to proteins, underlying some mechanisms of toxicity. A dedicated computational screen was used to identify UO(2) (2+) binding sites within a set of nonredundant protein structures. The list of potential targets was compared to data from a small molecules interaction database to pinpoint specific examples where UO(2) (2+) should be able to bind in the vicinity of an essential cation, and would ...[more]

PMID: 20842713

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Project description:Most of the biological processes are governed through specific protein-ligand interactions. Discerning different components that contribute toward a favorable protein- ligand interaction could contribute significantly toward better understanding protein function, rationalizing drug design and obtaining design principles for protein engineering. The Protein Data Bank (PDB) currently hosts the structure of ?68?000 protein-ligand complexes. Although several databases exist that classify proteins according to sequence and structure, a mere handful of them annotate and classify protein-ligand interactions and provide information on different attributes of molecular recognition. In this study, an exhaustive comparison of all the biologically relevant ligand-binding sites (84?846 sites) has been conducted using PocketMatch: a rapid, parallel, in-house algorithm. PocketMatch quantifies the similarity between binding sites based on structural descriptors and residue attributes. A similarity network was constructed using binding sites whose PocketMatch scores exceeded a high similarity threshold (0.80). The binding site similarity network was clustered into discrete sets of similar sites using the Markov clustering (MCL) algorithm. Furthermore, various computational tools have been used to study different attributes of interactions within the individual clusters. The attributes can be roughly divided into (i) binding site characteristics including pocket shape, nature of residues and interaction profiles with different kinds of atomic probes, (ii) atomic contacts consisting of various types of polar, hydrophobic and aromatic contacts along with binding site water molecules that could play crucial roles in protein-ligand interactions and (iii) binding energetics involved in interactions derived from scoring functions developed for docking. For each ligand-binding site in each protein in the PDB, site similarity information, clusters they belong to and description of site attributes are provided as a relational database-protein-ligand interaction clusters (PLIC). Database URL: http://proline.biochem.iisc.ernet.in/PLIC.

Dataset Information

Predicting the disruption by UO2(2+) of a protein-ligand interaction.

Publications

Predicting the disruption by UO2(2+) of a protein-ligand interaction.

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