Dataset Information

Mapping the sevoflurane-binding sites of calmodulin.

ABSTRACT: General anesthetics, with sevoflurane (SF) being the first choice inhalational anesthetic agent, provide reversible, broad depressor effects on the nervous system yet have a narrow margin of safety. As characterization of low-affinity binding interactions of volatile substances is exceptionally challenging with the existing methods, none of the numerous cellular targets proposed as chief protagonists in anesthesia could yet be confirmed. The recognition that most critical functions modulated by volatile anesthetics are under the control of intracellular Ca(2+) concentration, which in turn is primarily regulated by calmodulin (CaM), motivated us for characterization of the SF-CaM interaction. Solution NMR (Nuclear Magnetic Resonance) spectroscopy was used to identify SF-binding sites using chemical shift displacement, NOESY and heteronuclear Overhauser enhancement spectroscopy (HOESY) experiments. Binding affinities were measured using ITC (isothermal titration calorimetry). SF binds to both lobes of (Ca(2+))4-CaM with low mmol/L affinity whereas no interaction was observed in the absence of Ca(2+). SF does not affect the calcium binding of CaM. The structurally closely related SF and isoflurane are shown to bind to the same clefts. The SF-binding clefts overlap with the binding sites of physiologically relevant ion channels and bioactive small molecules, but the binding affinity suggests it could only interfere with very weak CaM targets.

SUBMITTER: Brath U

PROVIDER: S-EPMC4186402 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Mapping the sevoflurane-binding sites of calmodulin.

Brath Ulrika U Lau Kelvin K Van Petegem Filip F Erdélyi Máté M

Pharmacology research & perspectives 20140212 1

General anesthetics, with sevoflurane (SF) being the first choice inhalational anesthetic agent, provide reversible, broad depressor effects on the nervous system yet have a narrow margin of safety. As characterization of low-affinity binding interactions of volatile substances is exceptionally challenging with the existing methods, none of the numerous cellular targets proposed as chief protagonists in anesthesia could yet be confirmed. The recognition that most critical functions modulated by ...[more]

PMID: 25505574

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Project description:Background Analysis of the 3D structures of protein–ligand binding sites can provide valuable insights for drug discovery. Binding site comparison (BSC) studies can be employed to elucidate the function of orphan proteins or to predict the potential for polypharmacology. Many previous binding site analyses only consider binding sites surrounding an experimentally observed bound ligand. Results To encompass potential protein–ligand binding sites that do not have ligands known to bind, we have incorporated fpocket cavity detection software and assessed the impact of this inclusion on BSC performance. Using fpocket, we generated a database of ligand-independent potential binding sites and applied the BSC tool, SiteHopper, to analyze similarity relationships between protein binding sites. We developed a method for clustering potential binding sites using a curated dataset of structures for six therapeutically relevant proteins from diverse protein classes in the protein data bank. Two clustering methods were explored; hierarchical clustering and a density-based method adept at excluding noise and outliers from a dataset. We introduce circular plots to visualize binding site structure space. From the datasets analyzed in this study, we highlight a structural relationship between binding sites of cationic trypsin and prothrombin, protein targets known to bind structurally similar small molecules, exemplifying the potential utility of objectively and holistically mapping binding site space from the structural proteome. Conclusions We present a workflow for the objective mapping of potential protein–ligand binding sites derived from the currently available structural proteome. We show that ligand-independent binding site detection tools can be introduced without excessive penalty on BSC performance. Clustering combined with intuitive visualization tools can be applied to map relationships between the 3D structures of protein binding sites.Graphical abstract Mapping binding site space. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0180-0) contains supplementary material, which is available to authorized users.

Dataset Information

Mapping the sevoflurane-binding sites of calmodulin.

Publications

Mapping the sevoflurane-binding sites of calmodulin.

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