Characterization of the Cysteine Content in Proteins Utilizing Cysteine Selenylation with 266 nm Ultraviolet Photodissociation (UVPD)

Parker, William R.; Brodbelt, Jennifer S.

doi:10.1007/s13361-016-1405-1

Cited by 10 publications

(12 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The value of bond-selective dissociation was demonstrated previously for a simple protein in disulfide mapping experiments at 266 nm, which produces a set of doublets for each precursor ion. 33 Paek and coworkers have also demonstrated that searching MS 2 spectra for conserved fragmentation patterns drastically reduces the number of crosslinked candidates. 41…”

Section: Resultsmentioning

confidence: 99%

“…Homolytic dissociation of the S-Se bond allows for analysis of free cysteine content. 33 These methods are convenient and facilitate simple analysis, but generally do not afford sequence information since the peptide backbone does not readily absorb 266 nm photons. 213 nm UVPD offers a unique compromise between the selectivity of 266 nm and the extensive dissociation observed at 193 nm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simplified identification of disulfide, trisulfide, and thioether pairs with 213 nm UVPD

Bonner

Talbert

Akkawi

et al. 2018

Analyst

View full text Add to dashboard Cite

Disulfide heterogeneity and other non-native crosslinks introduced during therapeutic antibody production and storage could have considerable negative effects on clinical efficacy, but tracking these modifications remains challenging. Analysis must also be carried out cautiously to avoid introduction of disulfide scrambling or reduction, necessitating the use of low pH digestion with less specific proteases. Herein we demonstrate that 213 nm ultraviolet photodissociation streamlines disulfide elucidation through bond-selective dissociation of sulfur-sulfur and carbon-sulfur bonds in combination with less specific backbone dissociation. Importantly, both types of fragmentation can be initiated in a single MS/MS activation stage. In addition to disulfide mapping, it is also shown that thioethers and trisulfides can be identified by characteristic fragmentation patterns. The photochemistry resulting from 213 nm excitation facilitates a simplified, two-tiered data processing approach that allows observation of all native disulfide bonds, scrambled disulfide bonds, and non-native sulfur-based linkages in a pepsin digest of Rituximab. Native disulfides represented the majority of bonds according to ion count, but the highly solvent-exposed heavy/light interchain disulfides were found to be most prone to modification. Production and storage methods that facilitate non-native links are discussed. Due to the importance of heavy and light chain connectivity for antibody structure and function, this region likely requires particular attention in terms of its influence on maintaining structural fidelity.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simplified identification of disulfide, trisulfide, and thioether pairs with 213 nm UVPD

Bonner

Talbert

Akkawi

et al. 2018

Analyst

View full text Add to dashboard Cite

show abstract

“…16 Selenylation is mostly used to derivatize and protect the cysteine thiol group from oxidation, in vitro. 17 This variety of cysteine functions and their possible implication on a wide range of biological functions, make the cysteine residue an important target for function prediction in a given protein (Figure 1). Amino acid function prediction became increasingly important with the advent of the structure genomics consortium, 18 where a large number of protein crystal structures were solved with unknown functions; 3970 such structures were reported on 25 September 2020 in PDB database.…”

Section: Introductionmentioning

confidence: 99%

DeepCys: Structure‐based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains

et al. 2021

View full text Add to dashboard Cite

Cysteine (Cys) is the most reactive amino acid participating in a wide range of biological functions. In-silico predictions complement the experiments to meet the need of functional characterization. Multiple Cys function prediction algorithm is scarce, in contrast to specific function prediction algorithms. Here we present a deep neural network-based multiple Cys function prediction, available on web-server (DeepCys) (https://deepcys.herokuapp.com/). DeepCys model was trained and tested on two independent datasets curated from protein crystal structures. This prediction method requires three inputs, namely, PDB identifier (ID), chain ID and residue ID for a given Cys and outputs the probabilities of four cysteine functions, namely, disulphide, metal-binding, thioether and sulphenylation and predicts the most probable Cys function. The algorithm exploits the local and global protein properties, like, sequence and secondary structure motifs, buried fractions, microenvironments and protein/ enzyme class. DeepCys outperformed most of the multiple and specific Cys function algorithms. This method can predict maximum number of cysteine functions. Moreover, for the first time, explicitly predicts thioether function. This tool was used to elucidate the cysteine functions on domains of unknown functions belonging to cytochrome C oxidase subunit-II like transmembrane domains.

show abstract

“…10,11 One group of compounds that has been highlighted in the scientific community, both in the synthesis and the development of new therapeutic agents, is composed of organoselenium compounds. These compounds are obtained from reactions with elemental selenium 12 and electrophilic 13,14 Considering the potential of organoselenium compounds in the synthesis of new pharmaceutical drug candidates, a series of nine selenoglycolicamides were planned for evaluating an in silico study as new structures of drug candidates, obeying the Lipinski's rules. The compounds were synthesized using our selenoglycolic acid synthesis protocol, and these are the early studies of microbiological activity against bacteria (Staphylococcus aureus) and fungi (Candida albicans and Candida tropicalis).…”

Section: Introductionmentioning

confidence: 99%

Synthesis, in silico Study and Antimicrobial Evaluation of New Selenoglycolicamides

Souza

Sousa

Lira

et al. 2018

J. Braz. Chem. Soc.

View full text Add to dashboard Cite

Nine new compounds derived from selenoglycolic acid were synthesized, and their structures were fully characterized by elemental analysis, infrared (IR), 1 H and 13 C nuclear magnetic resonance (NMR). The compounds were evaluated in an in silico study and showed strong to moderate antibacterial activity against several strains of Staphylococcus aureus. In particular, three compounds exhibited excellent antibacterial activity, with minimum inhibitory concentrations (MICs) between 16 and 64 μg mL -1. Furthermore, two of the nine compounds showed antifungal activity, with MIC of 1024 and 512 μg mL -1 . In silico studies of the parameters of Lipinski's rule of five indicate that these compounds have potential to be new drug candidates.

show abstract

Characterization of the Cysteine Content in Proteins Utilizing Cysteine Selenylation with 266 nm Ultraviolet Photodissociation (UVPD)

Cited by 10 publications

References 36 publications

Simplified identification of disulfide, trisulfide, and thioether pairs with 213 nm UVPD

Simplified identification of disulfide, trisulfide, and thioether pairs with 213 nm UVPD

DeepCys: Structure‐based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains

Synthesis, in silico Study and Antimicrobial Evaluation of New Selenoglycolicamides

Contact Info

Product

Resources

About