Mammalian thioredoxin reductase (TR) contains the rare amino acid selenocysteine (Sec), which is essential for the enzyme’s catalytic activity. Substitution of the catalytic Sec residue for a cysteine (Cys) residue, results in a drop in kcat of 100- fold. Homologous high molecular weight TRs from other eukaryotes such as D. melanogaster and C. elegans, have naturally evolved a Sec to Cys substitution in their active sites and these enzymes function with high catalytic activity without the need for a Sec residue. Thus, various TRs can catalyze an identical reaction with either a Cys or Sec residue. A natural assumption in the field has always been that the lower nucleophilicity of a Cys thiol, relative to the selenol of Sec, is the reason for the much lower activity of the mammalian Cys-containing mutant. However, here I provide an alternative explanation. High Mr TRs contain either a Cys-Cys or Cys-Sec dyad that forms an eight-membered ring in the oxidized state during the redox cycle of the enzyme. These eight-membered ring structures are rare in protein structures, presumably due to the strain induced in the intervening peptide bond between the Cys residues. Here I take a “chemical approach” to studying the enzyme mechanism of TR by breaking it into two pieces. This approach is possible because of TR’s structural and mechanistic similarity to glutathione reductase (GR). In comparison to GR, TR contains an additional thiol-disulfide exchange step resulting from the presence of a sixteen amino acid C-terminal extension containing either a vicinal disulfide bond or vicinal selenylsulfide bond. This additional thiol-disulfide exchange step is in the form of the reduction and opening of the eight-membered ring motif. I have constructed a truncated version of the enzyme lacking the amino acid sequence possessing the ring motif so that I could isolate this ring-opening step from the rest of the catalytic cycle by using peptide disulfides/selenylsulfides as substrates. The results of this study using peptide substrates show that the ring opening step is the step of the catalytic cycle that is most effected by Sec to Cys substitution because the higher pKa of the Cys thiolate in comparison to the Sec selenolate means that the Cys residue must be protonated in this step.

Human hydroxysteroid sulfotransferase (hSULT2A1) catalyzes the sulfation of a broad range of endogenous (e.g., hormones, neurotransmitters, bile acids) as well as xenobiotic (e.g, drugs, environmental pollutants) compounds. Alteration in the catalytic activity of hSULT2A1 can lead to outcomes like endocrine disruptions or aberrant drug metabolism and xenobiotic toxicity. Oxidative and electrophilic stresses are known to cause physiological damage and be implicated as possible underlying pathologic mechanisms of a wide range of diseases. To examine the oxidative as well as electrophilic regulation of hSULT2A1, model oxidants (glutathione disulfide (GSSG), 5,5'-dithiobis(2-nitrobenzoic acid) (DTNB), diamide, tert-butyl hydroperoxide (TBHP)) and electrophiles such as quinone metabolites of polychlorinated biphenyls (PCB-quinones) and phenyl-p- benzoquinone were chosen for this study. Mechanistic studies correlating the enzyme structural modifications with alteration in the catalytic properties were performed to elucidate the catalytic regulative mechanism of an individual oxidant or electrophile. Thiol oxidants including GSSG, DTNB, and diamide showed catalytic regulation of hSULT2A1. Changes in protein intrinsic fluorescence indicated conformational alterations in hSULT2A1 following the reaction with diamide. Binding properties of hSULT2A1 for its substrates were also altered after reaction with these thiol oxidants, which could be one major reason for the kinetic alteration due to oxidative modification. Formation of mixed disulfides with cysteines in hSULT2A1 was also identified as a result of reaction with GSSG and DTNB. TBHP was chosen as a model for lipid peroxides, and reaction with this hydroperoxide decreased the catalytic function of hSULT2A1. The dissociation constant for binding of dehydroepiandrosterone (DHEA) was significantly altered with TBHP-pretreatment, but this did not affect the binding of 3',5'-adenosine diphosphate (PAP) to the enzyme. Structural analysis identified cysteine sulfonic acids and methionine sulfoxide formation after reaction of hSULT2A1 with TBHP, which could account for the alterations in the binding properties and the catalytic activity. Both PCB-quinones and PBQ could regulate the catalytic activity of hSULT2A1. Although PCB-quinones only caused decreases in the catalytic activity at all concentrations tested, pretreatment with PBQ indicated that lower concentrations resulted in an increase in the catalytic activity of hSULT2A1 that was followed by a decrease in the catalytic activity of hSULT2A1 upon increasing the concentration of PBQ in the pretreatment. Differences in the dissociation constants of PAP after PBQ-pretreatment were also observed, indicating the key role played by these PCB-quinones in altering the binding of either PAP or the sulfuryl donors, PAPS. Adducts at cysteines in hSULT2A1 were formed following reactions with PCB-quinones and PBQ. Small amounts of cysteine sulfonic acids and methionine sulfoxides were also formed following reaction of the protein with PCB-quinones and PBQ. Therefore, alterations in both the catalytic function as well as the structural properties of hSULT2A1 by interaction with oxidants and electrophiles may lead to changes in the metabolism of xenobiotics, as well as alterations in the endogenous balance of various steroid hormones. Such changes may be an important component in physiological damage that occurs under oxidative and electrophilic stress.

Of the 20 standard amino acids, cysteines are the only amino acids that have a reactive sulphur atom, thus enabling two cysteines to form strong covalent bonds known as disulfide bonds. Even though almost all proteins have cysteines, not all of them have disulfide bonds. Disulfide bonds provide structural stability to proteins and hence are an important constraint in determining the structure of a protein. As a result, disulfide bonds are used to study various protein properties, one of them being protein folding. Protein structure prediction is the problem of predicting the three-dimensional structure of a protein from its one-dimensional amino acid sequence. Ab initio methods are a group of methods that attempt to solve this problem from first principles, using only basic physico-chemical properties of proteins. These methods use structure libraries of short amino acid fragments in the process of predicting the structure of a protein. The protein structures from which these structure libraries are created are not classified in any other way apart from being non-redundant. In this thesis, we investigate the structural dissimilarities of short amino acid fragments when occurring in proteins with disulfide bonds and when occurring in those proteins without disulfide bonds. We are interested in this because, as mentioned earlier, the protein structures from which the structure libraries of ab initio methods are created, are not classified in any form. This means that any significant structural difference in amino acids and short fragments when occurring in proteins with and without disulfide bonds would remain unnoticed as these structure libraries have both fragments from proteins with disulfide bonds and without disulfide bonds together. Our investigation of structural dissimilarities of amino acids and short fragments is done in four phases. In phase one, by statistically analysing the phi and psi backbone dihedral angle distributions we show that these fragments have significantly different structures in terms of dihedral angles when occurring in proteins with and without disulfide bonds. In phase two, using directional statistics we investigate how structurally different are the 20 different amino acids and the short fragments when occurring in proteins with and without disulfide bonds. In phase three of our work, we investigate the differences in secondary structure preference of the 20 amino acids in proteins with and without disulfide bonds. In phase four, we further investigate and show that there are significant differences within the same secondary structure region of amino acids when they occur in proteins with and without disulfide bonds. Finally, we present the design and implementation details of a dihedral angle and secondary structure database of short amino acid fragments (DASSD) that is publicly available. Thus, in this thesis we show previously unknown significant structure differences in terms of backbone dihedral angles and secondary structures in amino acids and short fragments when they occur in proteins with and without disulfide bonds.

Knowledge on cysteine oxidation state and disulfide bond connectivity is of great importance to protein chemistry and 3-D structures. This research is aimed at finding the most relevant features in prediction of cysteines oxidation states and the disulfide bonds connectivity of proteins. Models predicting the oxidation states of cysteines are developed with machine learning techniques such as Support Vector Machines (SVMs) and Associative Neural Networks (ASNNs). A record high prediction accuracy of oxidation state, 95%, is achieved by incorporating the oxidation states of N-terminus cysteines, flanking sequences of cysteines and global information on the protein chain (number of cysteines, length of the chain and amino acids composition of the chain etc.) into the SVM encoding. This is 5% higher than the current methods. This indicates to us that the oxidation states of amino terminal cysteines infer the oxidation states of other cysteines in the same protein chain. Satisfactory prediction results are also obtained with the newer and more inclusive SPX dataset, especially for chains with higher number of cysteines. Compared to literature methods, our approach is a one-step prediction system, which is easier to implement and use. A side by side comparison of SVM and ASNN is conducted. Results indicated that SVM outperform ASNN on this particular problem. For the prediction of correct pairings of cysteines to form disulfide bonds, we first study disulfide connectivity by calculating the local interaction potentials between the flanking sequences of the cysteine pairs. The obtained interaction potential is further adjusted by the coefficients related to the binding motif of enzymes during disulfide formation and also by the linear distance between the cysteine pairs. Finally, maximized weight matching algorithm is applied and performance of the interaction potentials evaluated. Overall prediction accuracy is unsatisfactory compared with the literature. SVM is used to predict the disulfide connectivity with the assumption that oxidation states of cysteines on the protein are known. Information on binding region during disulfide formation, distance between cysteine pairs, global information of the protein chain and the flanking sequences around the cysteine pairs are included in the SVM encoding. Prediction results illustrate the advantage of using possible anchor region information.

No description available.

<p>Stabilization of proteins is of great interest for the biotechnological society, industrial as well as research areas. Proteins with high stability are more suitable as reagents, easier to handle, store, transport and use in industrial processes. One way to stabilize a protein is to introduce a disulfide bridge into the structure by protein engineering. In this report the formation of a disulfide bridge between engineered cysteines in non ideal conformations in human carbonic anhydrase has been investigated. The disulfide bridge is not formed when the protein is in its native state. It is shown that when the protein is exposed to mild concentrations of urea in the presence of DTTox the disulfide bridge is formed. Also upon refolding in vitro, in a non oxidative environment, disulfide bridges are formed. This observation is worth to notice, since the disulfide bridge does not form to any appreciable extent when the protein is expressed and folded in vivo in Escherichia coli.</p>

Stabilization of proteins is of great interest for the biotechnological society, industrial as well as research areas. Proteins with high stability are more suitable as reagents, easier to handle, store, transport and use in industrial processes. One way to stabilize a protein is to introduce a disulfide bridge into the structure by protein engineering. In this report the formation of a disulfide bridge between engineered cysteines in non ideal conformations in human carbonic anhydrase has been investigated. The disulfide bridge is not formed when the protein is in its native state. It is shown that when the protein is exposed to mild concentrations of urea in the presence of DTTox the disulfide bridge is formed. Also upon refolding in vitro, in a non oxidative environment, disulfide bridges are formed. This observation is worth to notice, since the disulfide bridge does not form to any appreciable extent when the protein is expressed and folded in vivo in Escherichia coli.

Disulfide bond formation is an essential process for the folding and biological activity of most extracellular proteins; however, it may become the limiting step when the production of these proteins is attempted in heterologous hosts such as Escherichia coli. The rearrangement of incorrect disulfide bonds between cysteines that do not normally interact in the native structure of a protein is carried out by disulfide isomerase enzymes. The disulfide isomerase present in the bacterial secretory compartment (the periplasmic space) is the homodimeric enzyme DsbC. The objective of this dissertation was to understand the key features of how DsbC catalyzes disulfide bond isomerization. Chimeric disulfide isomerases comprising of protein domains that share a similar function, or are homologous to domains of DsbC were constructed in an effort to understand the effect of the domain orientation in the dimeric protein, and the need for a substrate binding region in disulfide isomerases. We successfully created a series of fusion enzymes, FkpA-DsbAs, which catalyze in vivo disulfide isomerization with comparable efficiency to DsbC. These enzymes comprise of the peptide binding region of the periplasmic chaperone FkpA, which is functionally and structurally similar to the binding domain of DsbC but share no amino acid homology with it, fused to the bacterial oxidase DsbA. In addition, these chimeric enzymes were shown to assist in the initial formation of disulfide bonds, a function that is normally exhibited only by DsbA. Directed evolution of the FkpA-DsbA proteins conferred improved resistance to CuCl₂, a phenotype dependent on disulfide bond isomerization and highlighted the importance of an optimal catalytic site. The bacterial disulfide isomerase DsbC is a homodimeric V-shaped enzyme that consists of a dimerization domain, two α-helical linkers and two opposing catalytic domains. The functional significance of the existence of two catalytic domains of DsbC is not well understood yet. The fact that identical subunits naturally dimerize to generate DsbC has so far limited the study of the individual catalytic sites in the homodimer. In chapter 3 we discuss the engineering, in vivo function, and biochemical characterization chapter 3 we discuss the engineering, in vivo function, and biochemical characterization of DsbC variants covalently linked via (Gly3Ser) flexible linkers. We have either inactivated one of the catalytic sites (CGYC), or entirely removed one of the catalytic domains while maintaining the putative binding area intact. Our results support the hypotheses that dual catalytic domains in DsbC are not necessary for disulfide bond isomerization, but are important in terms of increasing the effective concentration of catalytic equivalents, and that the availability of a substrate binding region is a determining feature in isomerization. Finally, we have carried out initial studies to map the residues and sequence motifs that are recognized in substrate proteins that interact with DsbC. Although the main putative binding region of DsbC has been localized within the limits of the hydrophobic cleft that emerges from the interaction of the N-terminal domains of this enzyme, and, a few native substrates have already been identified, no information on the features of substrate proteins that are recognized by the enzyme has been reported. To address this problem, we have screened two different, 15 amino-acid random peptide libraries for binding to DsbC. We have successfully isolated several peptides with high affinity for the enzyme. Possible consensus binding motifs were identified and their significance in substrate recognition will be examined in future studies. / text

Copper is an essential trace element and required for various biological processes, but free copper is toxic. Therefore, copper is tightly regulated in living cells and disruptions in this homeostatic machinery are implicated in numerous diseases. The current understanding of copper homeostasis is substantial but incomplete, particularly in regard to storage and exchange at the subcellular level. Intracellular copper is primarily present in the monovalent oxidation state. Therefore, copper(I) selective fluorescent probes can be utilized for imaging exchangeable copper ions in live cells, but these probes are often lipophilic and hence poorly water soluble. To address this problem, water-soluble fluorescent probes with greatly improved contrast ratio and fluorescence quantum yield are characterized in this work. This work also describes a novel application of water-soluble fluorescent probes, in-gel detection of copper proteins with solvent accessible Cu(I) sites under non-denaturing conditions. Knowledge of copper(I) stability constants of proteins is important to elucidate the mechanisms of cellular copper homeostasis. Due to the high affinity of most Cu(I)-binding proteins, the stability constants cannot be determined directly by titration of the apo-protein with Cu(I). Therefore, accurate determination of Cu(I) stability constants of proteins critically depends on the Cu(I) affinity standards. However, the previously reported binding affinity values of the frequently used Cu(I) affinity standards are largely inconsistent impeding reliable data acquisition for the Cu(I) stability constants of proteins. To solve this problem, a set of water-soluble ligands are developed in this work that form colorless, air-stable copper(I)-complexes with 1:1 stoichiometry. These ligands can be applied as copper(I) buffering agents and affinity standards in order to study copper biochemistry. Copper(I) binding proteins are an integral part of the copper homeostatic machinery and they work in conjunction to regulate copper uptake, distribution, and excretion. However, available evidence indicates the existence of putative copper-binding proteins that are yet to be characterized. Therefore, several proteomics-based methods are developed in this work by employing the strategy to label Cu(I)-binding cysteines in a copper-dependent manner which lays the foundation for the identification of new copper proteins from cellular extracts.

The work here presents two main parts. In the first part, chapters 1 – 3 focus on dynamical systems modeling in plant immunity, whereas chapters 4 – 6 describe contributions to computational modeling and analysis of proteomics and genomics data. Chapter 1 investigates dynamical and biochemical patterns of reversibly oxidized cysteines (RevOxCys) during effector-triggered immunity (ETI) in Arabidopsis, examines the regulatory patterns associated with Arabidopsis thimet oligopeptidase 1 and 2’s (TOP1 and TOP2), roles in the RevOxCys events during ETI, and analyzes the redox phenotype of the top1top2 mutant. The second chapter investigates the peptidome dynamics during ETI in wild-type (WT) and top1top2 mutant, introduces a novel method to learn the cleavage motif for TOPs and predicts and validates bioactive peptides association with TOPs activity. The third chapter examines gene expression dynamics during Systemic Acquired Resistance (SAR). Time-series clustering identifies unique oscillatory patterns in gene transcription associated with the early onset of SAR. It then describes a mathematical model using ordinary differential equations to represent WT's transcriptional dynamics. The second part of this dissertation explores imputation and statistical modeling for proteomics data analysis and proposes a network inference methodology for polymorphic cysteines. The fourth chapter analyzes the performance of linear models (limma) and the effect of imputation in proteomics data. It shows the advantage of data imputation over filtering and the benefit of using limma over t-test for the statistical decision of differences in means between conditions for different peptides, PTMs, etc. The fifth chapter proposes a statistical model for proteomics data analysis using mean-variance (M-V) trend modeling. It describes a gamma regression to model the dependency of the variance on the mean of observations. Finally, a Bayesian decision model is proposed; the model shows an improvement over existing methods in statistical decision performance. The sixth and final chapter describes a network inference procedure that identifies genetic dependencies between polymorphic cysteines. It models the interactions between cysteines (nodes) as signed edges for positive or inhibitory relations. It utilizes local network structures for inferences about the relationship between the cysteines. The algorithm exhibits stability and efficiency, converging rapidly to inferred solutions.