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All constructs were validated by DNA sequencing. For unfolding assays, oxidized proteins were incubated with urea at a final concentration ranging from 0. N-Acetyl-MetO was prepared as described MSR activities were calculated from the slope after subtracting the background absence of the enzyme considering that 1 mol of oxidized NADPH corresponds to 1 mol of MetO reduced.

The apparent stoichiometry was determined similarly using subsaturating concentrations of substrates: Kinetic and catalytic parameters were calculated from nonlinear regressions using GraphPad Prism 4. As a control, amounts of urea used in the urea-treated proteins were added to the oxidized protein samples less than 50 mm. The same samples were used to determine 8-anilinonaphthalenesulfonate ANS fluorescence. The percentage of oxidation per Met was calculated using the redundancy of the peptide containing the specific Met, oxidized or not.

The percentage of oxidation values corresponds to the number of times a MetO was found divided by the total number of times the peptide was found coveragemultiplied by This method allows quantifying the oxidation of each Met found in peptide-containing several Met, which is not possible using area integration. Yeast Spotting Assays MSRA expressed under the glycerolphosphate dehydrogenase promoter from the high copy number yeast expression vector p and MSR null strains was described previously After colony formation, single colonies were picked up from the plates and grown overnight in the media lacking histidine or leucine.

This procedure was also applied for empty vector transformation, which was used as a control. In the spotting assay, the indicated strains were grown overnight in appropriate media and diluted to an A of 0. Cells were prepared as indicated above, and the A was adjusted to 0. Cells were washed with the prewarmed PBS, and 1 ml of each culture was spread onto agar plates missing the appropriate amino acids for selection.

Plates were dried for 1 h at room temperature, and filter paper discs were placed in the middle of each plate. The diameter of cleared zones in each plate was measured with a ruler. In this regard, Cys properties make this amino acid a preferred residue for redox-dependent regulation of metal binding. This is a prominent feature of Cys-based metal-binding sites, often referred to as the redox switching of Cys residues 3233 Considering that metal-binding sites are often highly conserved, the presence of conserved proximal Cys residues can be a good indication that these residues may bind metals.

ScanProsite 39 but lack the ability to properly recognize many metal-binding sites i. More sophisticated approaches have been developed based on machine learning 4048 and nonlinear statistical methods An example is provided by the method called MetalDetector, freely available as a web-accessible service.

Analysis and Functional Prediction of Reactive Cysteine Residues

Structure-based approaches can be a valuable alternative for the prediction of metal-binding Cys residues. One interesting method involves the use of the empirical force field FoldX The searching algorithm uses geometric information typically found in metal-binding sites as a starting point to predict new sites. After analyzing the typical arrangement of Cys ligands around zinc coordination sites, the method can recognize similar structural patterns in terms of both the nature of ligands clustered in space and their relative geometries and therefore predict new metal-binding sites A standalone program implementing the algorithm for prediction of metal-binding sites as well as several other algorithms for energy-based evaluation and protein design is available at the FoldX web site.

Additionally, Cys can react with endogenous hydrogen sulfide H2Sa modification that can lead to various physiological 51 — 53 and structural 54 effects. All of the above can be classified as redox-based PTMs and are reversible. However, other important Cys modifications that are stable and do not involve a change in the redox state occur, for example, the formation of a thioether bond with farnesyl or geranylgeranyl groups, leading to protein lipidation and membrane anchoring 55 or covalent binding of protein cofactors, such as heme.

These Cys modifications may be classified into a separate category of functional Cys residues. Below, we focus on the reversible Cys modifications.

These PTMs can affect protein properties local structure, electrostatic interactions, etc. From a computational perspective, regulatory Cys residues are challenging to investigate. Recent progress in proteomics approaches provided a substantial improvement in both quantity and quality of the data produced. In turn, this allows bioinformaticians to start tackling the fundamental issue of the defining features of regulatory Cys.

To date, no reliable sequence-based predictive patterns have been developed for different types of regulatory Cys. Instead, high heterogeneity of sequence features was detected. As for the latter, an important role of uncharged H-bond donors, particularly Thr, was revealed Spatial but not sequence proximity to these residues can lead to activation of Cys, mainly by lowering its pKa. In the case of NO-Cys, sequence-based bioinformatics analyses also revealed high heterogeneity around modification sites 57 However, structural analyses provided new insights.

First, a QM-based study demonstrated that NO modification can induce a significant charge redistribution in the side chain of Cys, with only marginal effects on the backbone atoms In this study, specific force field parameters and charge schemes for NO-Cys were developed, paving the way for setting up docking experiments with NO-Cys-containing substrates, such as S-nitrosoglutathione Indeed, docking calculations could be a valid computational alternative for detection of specific Cys residues amenable to modification with different nitrosylated substrates NO-Cys, S-nitrosylated small peptides, etc.

Particularly challenging but certainly feasible is the investigation of the role of protein-protein interactions in the transfer of NO groups from one protein to another the so-called protein interaction-based transnitrosylation. This process has so far escaped detailed computational studies, partly due to the complexity of the system. However, the steady development of suitable docking software e.

RosettaDock and the information gained from previous studies 2959 may make it soon possible to investigate protein interaction-based transnitrosylation. Catalytic Cys Residues In many enzymes, Cys plays a critical role as a nucleophile in enzyme-catalyzed reactions. Such Cys residues represent a functional category of catalytic Cys residues. This category can be further subdivided into redox and non-redox Cys functions based on whether the redox state of Cys changes during catalysis.

Examples of enzymes with non-redox catalytic Cys residues are protein-tyrosine phosphatases, Cys peptidases, various members of the deubiquitination system, and dCMP hydroxymethylases. Other enzymes called thiol oxidoreductases present catalytic redox Cys in the active sites; here, the catalytic Cys function involves substrate oxidation or reduction, disulfide bond isomerization, and detoxification of various compounds.

To our knowledge, no computational approaches for the detection of catalytic non-redox Cys residues have been developed. Thus, we focus further on thiol oxidoreductases, for which better progress has been made. Thiol oxidoreductases are the only known enzymes that also use Sec as the catalytic residue. This very unique feature was used to develop a bioinformatics strategy for the prediction of thiol oxidoreductases. These pairs then serve as seeds for sequence analysis at the level of protein families and subfamilies.

Application of this method identified the majority of known thiol oxidoreductases and indicated the identity of the catalytic Cys. A key advantage of this approach, together with sensitivity, is its speed. High-throughput analyses are possible in a reasonable amount of time, allowing genome-wide analyses of thiol oxidoreductases Bioinformatics approaches applied to the study of thiol oxidoreductases are not limited to their prediction.