Oxidation of the N-terminal domain of the wheat metallothionein Ec -1 leads to the formation of three distinct disulfide bridges.

Metallothioneins (MTs) are low molecular weight proteins, characterized by a high cysteine content and the ability to coordinate large amounts of d(10) metal ions, for example, Zn(II), Cd(II), and Cu(I), in form of metal-thiolate clusters. Depending on intracellular conditions such as redox potential or metal ion concentrations, MTs can occur in various states ranging from the fully metal-loaded holo- to the metal-free apo-form. The Cys thiolate groups in the apo-form can be either reduced or be involved in disulfide bridges. Although oxidation-mediated Zn(II) release might be a possible mechanism for the regulation of Zn(II) availability by MTs, no concise information regarding the associated pathways and the structure of oxidized apo-MT forms is available. Using the well-studied Zn2 γ-Ec -1 domain of the wheat Zn6 Ec -1 MT we attempt here to answer several question regarding the structure and biophysical properties of oxidized MT forms, such as: (1) does disulfide bond formation increase the stability against proteolysis, (2) is the overall peptide backbone fold similar for the holo- and the oxidized apo-MT form, and (3) are disulfide bridges specifically or randomly formed? Our investigations show that oxidation leads to three distinct disulfide bridges independently of the applied oxidation conditions and of the initial species used for oxidation, that is, the apo- or the holo-form. In addition, the oxidized apo-form is as stable against proteolysis as Zn2 γ-Ec -1, rendering the currently assumed degradation of oxidized MTs unlikely and suggesting a role of the oxidation process for the extension of protein lifetime in absence of sufficient amounts of metal ions. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 295-308, 2016.

In the picture: disulfide-poor conopeptides, a class of pharmacologically interesting compounds

During evolution, nature has embraced different strategies for species to survive. One strategy, applied by predators as diverse as snakes, scorpions, sea anemones and cone snails, is using venom to immobilize or kill a prey. This venom offers a unique and extensive source of chemical diversity as it is driven by the evolutionary pressure to improve prey capture and/or to protect their species. Cone snail venom is an example of the remarkable diversity in pharmacologically active small peptides that venoms can consist of. These venom peptides, called conopeptides, are classified into two main groups based on the number of cysteine residues, namely disulfide-rich and disulfide-poor conopeptides. Since disulfide-poor conotoxins are minor components of this venom cocktail, the number of identified peptides and the characterization of these peptides is far outclassed by its cysteine-rich equivalents. This review provides an overview of 12 families of disulfide-poor peptides identified to date as well as the state of affairs.

Prospective type 1 and type 2 disulfides of Keap1 protein.

Experiments were carried out to detect cysteine residues on human Keap1 protein that may be sensors of oxidative stress that gives rise to changes in the GSH/GSSG redox couple. Human Keap1 protein, at a final concentration of 6 microM, was incubated for two hours in aqueous buffer containing 0.010 M GSH, pH 8, in an argon atmosphere. Subsequently, excess iodoacetamide and trypsin were added to generate a peptide map effected by LCMS analysis. Peptides containing all 27 carboxamidomethylated cysteines were identified. Replacement of GSH by 0.010 M GSSG yielded a map in which 13 of the original carboxamidomethylated peptides were unperturbed, while other caboxamidomethylated cysteine-containing peptides were undetected, and a number of new cysteine-containing peptide peaks were observed. By mass analysis, and in some cases, by isolation, reduction, carboxamidomethylation, and reanalysis, these were identified as S-glutathionylated (Type 1) or Cys-Cys (Type 2) disulfides. Such peptides derived from the N-terminal, dimerization, central linker, Kelch repeat and C-terminal domains of Keap1. Experiments were carried out in which Keap1 was incubated similarly but in the presence of various GSH/GSSG ratios between 100 and 1 ([GSH + GSSG] = 0.010 M), with subsequent caraboxamidomethylation and trypsinolysis to determine differences in sensitivities of the different cysteines to the type 1 and type 2 modifications. Cysteines most sensitive to S-glutathionylation include Cys77, Cys297, Cys319, Cys368, and Cys434, while cysteine disulfides most readily formed are Cys23-Cys38 and Cys257-Cys297. The most reducing conditions at which these modifications are at GSH/GSSG = 10, which computes to an oxidation potential of E h = -268.5 mV, a physiologically relevant value. Under somewhat more oxidizing, but still physiologically relevant, conditions, GSH/GSSG = 1 ( E h = -231.1 mV), a Cys319-Cys319 disulfide is detected far from the dimerization domain of the Keap1 homodimer. The potential impact on protein structure of the glutathionylation of Cys434 and Cys368, the two modified residues in the Kelch repeat domain, was analyzed by docking and energy minimizations of glutathione residues attached to the Kelch repeat domain, whose coordinates are known. The energy minimizations indicated marked alterations in structure with a substantial constriction of Neh2 binding domain of the Keap1 Kelch repeat domain. This alteration appears to be enforced by an extended hydrogen-bonding network between residues on the glutathione moiety attached to Cys434 and amino acid side chains that have been shown to be essential for repression of Nrf2 by Keap1. The modifications of Keap1 detected in the present study are discussed in the context of previous work of others who have examined the sensitivity of cysteines on Keap1 to electrophile assault.

Predicting disulfide connectivity patterns.

Disulfide bonds play an important role in stabilizing protein structure and regulating protein function. Therefore, the ability to infer disulfide connectivity from protein sequences will be valuable in structural modeling and functional analysis. However, to predict disulfide connectivity directly from sequences presents a challenge to computational biologists due to the nonlocal nature of disulfide bonds, i.e., the close spatial proximity of the cysteine pair that forms the disulfide bond does not necessarily imply the short sequence separation of the cysteine residues. Recently, Chen and Hwang (Proteins 2005;61:507-512) treated this problem as a multiple class classification by defining each distinct disulfide pattern as a class. They used multiple support vector machines based on a variety of sequence features to predict the disulfide patterns. Their results compare favorably with those in the literature for a benchmark dataset sharing less than 30% sequence identity. However, since the number of disulfide patterns grows rapidly when the number of disulfide bonds increases, their method performs unsatisfactorily for the cases of large number of disulfide bonds. In this work, we propose a novel method to represent disulfide connectivity in terms of cysteine pairs, instead of disulfide patterns. Since the number of bonding states of the cysteine pairs is independent of that of disulfide bonds, the problem of class explosion is avoided. The bonding states of the cysteine pairs are predicted using the support vector machines together with the genetic algorithm optimization for feature selection. The complete disulfide patterns are then determined from the connectivity matrices that are constructed from the predicted bonding states of the cysteine pairs. Our approach outperforms the current approaches in the literature.

A classification of disulfide patterns and its relationship to protein structure and function.

We report a detailed classification of disulfide patterns to further understand the role of disulfides in protein structure and function. The classification is applied to a unique searchable database of disulfide patterns derived from the SwissProt and Pfam databases. The disulfide database contains seven times the number of publicly available disulfide annotations. Each disulfide pattern in the database captures the topology and cysteine spacing of a protein domain. We have clustered the domains by their disulfide patterns and visualized the results using a novel representation termed the "classification wheel." The classification is applied to 40,620 protein domains with 2-10 disulfides. The effectiveness of the classification is evaluated by determining the extent to which proteins of similar structure and function are grouped together through comparison with the SCOP and Pfam databases, respectively. In general, proteins with similar disulfide patterns have similar structure and function, even in cases of low sequence similarity, and we illustrate this with specific examples. Using a measure of disulfide topology complexity, we find that there is a predominance of less complex topologies. We also explored the importance of loss or addition of disulfides to protein structure and function by linking classification wheels through disulfide subpattern comparisons. This classification, when coupled with our disulfide database, will serve as a useful resource for searching and comparing disulfide patterns, and understanding their role in protein structure, folding, and stability. Proteins in the disulfide clusters that do not contain structural information are prime candidates for structural genomics initiatives, because they may correspond to novel structures.