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Reactivity, Selectivity, and Stability in Sulfenic Acid Detection: A Comparative Study of Nucleophilic and Electrophilic Probes.

ABSTRACT: The comparative reaction efficiencies of currently used nucleophilic and electrophilic probes toward cysteine sulfenic acid have been thoroughly evaluated in two different settings-(i) a small molecule dipeptide based model and (ii) a recombinant protein model. We further evaluated the stability of corresponding thioether and sulfoxide adducts under reducing conditions which are commonly encountered during proteomic protocols and in cell analysis. Powered by the development of new cyclic and linear C-nucleophiles, the unsurpassed efficiency in the capture of sulfenic acid under competitive conditions is achieved and thus holds great promise as highly potent tools for activity-based sulfenome profiling.

SUBMITTER: Gupta V

PROVIDER: S-EPMC4886738 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Reactivity, Selectivity, and Stability in Sulfenic Acid Detection: A Comparative Study of Nucleophilic and Electrophilic Probes.

Gupta Vinayak V Paritala Hanumantharao H Carroll Kate S KS

Bioconjugate chemistry 20160509 5

The comparative reaction efficiencies of currently used nucleophilic and electrophilic probes toward cysteine sulfenic acid have been thoroughly evaluated in two different settings-(i) a small molecule dipeptide based model and (ii) a recombinant protein model. We further evaluated the stability of corresponding thioether and sulfoxide adducts under reducing conditions which are commonly encountered during proteomic protocols and in cell analysis. Powered by the development of new cyclic and lin ...[more]

PMID: 27123991

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Project description:BackgroundReactive oxygen species-mediated cysteine sulfenic acid modification has emerged as an important regulatory mechanism in cell signaling. The stability of sulfenic acid in proteins is dictated by the local microenvironment and ability of antioxidants to reduce this modification. Several techniques for detecting this cysteine modification have been developed, including direct and in situ methods.Scope of reviewThis review presents a historical discussion of sulfenic acid chemistry and highlights key examples of this modification in proteins. A comprehensive survey of available detection techniques with advantages and limitations is discussed. Finally, issues pertaining to rates of sulfenic acid formation, reduction, and chemical trapping methods are also covered.Major conclusionsEarly chemical models of sulfenic acid yielded important insights into the unique reactivity of this species. Subsequent pioneering studies led to the characterization of sulfenic acid formation in proteins. In parallel, the discovery of oxidant-mediated cell signaling pathways and pathological oxidative stress has led to significant interest in methods to detect these modifications. Advanced methods allow for direct chemical trapping of protein sulfenic acids directly in cells and tissues. At the same time, many sulfenic acids are short-lived and the reactivity of current probes must be improved to sample these species, while at the same time, preserving their chemical selectivity. Inhibitors with binding scaffolds can be rationally designed to target sulfenic acid modifications in specific proteins.General significanceEver increasing roles for protein sulfenic acids have been uncovered in physiology and pathology. A more complete understanding of sulfenic acid-mediated regulatory mechanisms will continue to require rigorous and new chemical insights. This article is part of a Special Issue entitled Current methods to study reactive oxygen species - pros and cons and biophysics of membrane proteins. Guest Editor: Christine Winterbourn.

Dataset Information

Reactivity, Selectivity, and Stability in Sulfenic Acid Detection: A Comparative Study of Nucleophilic and Electrophilic Probes.

Publications

Reactivity, Selectivity, and Stability in Sulfenic Acid Detection: A Comparative Study of Nucleophilic and Electrophilic Probes.

Similar Datasets

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