A Novel Database of Disulfide Patterns and its Application to the Discovery of Distantly Related Homologs

Expression of mRNAs Encoding Hypothalamic Small Proteins, Neurosecretory Protein GL and Neurosecretory Protein GM, in the Japanese Quail, Coturnix japonica

Neurosecretory protein GL (NPGL) and neurosecretory protein GM (NPGM) are novel neuropeptides that have been discovered in the hypothalamic infundibulum of chickens. NPGL and NPGM play important roles in lipid metabolism in juvenile chickens. The physiological functions of NPGL and NPGM in sexually mature birds remain unknown. The Japanese quail (Coturnix japonica) seems to be an appropriate model for analyzing NPGL and NPGM during sexual maturity. However, studies on NPGL or NPGM have yet to be reported in the Japanese quail. In the present study, we identified cDNAs encoding precursor proteins of NPGL and NPGM in the quail hypothalamus. In situ hybridization revealed that NPGL mRNA-expressing cells in the hypothalamus were localized in the infundibular nucleus and median eminence, and NPGM mRNA-expressing cells were only found in the mammillary nucleus. Immunohistochemistry revealed that NPGM-like immunoreactive cells were distributed in the mammillary nucleus, whereas NPGL-like immunoreactive cells were not detected in the hypothalamus. Real-time PCR analysis indicated that the expression of NPGL mRNA was higher in the hypothalamus of females than in that of males, and NPGM mRNA expression showed no sex differences. NPGL and NPGM mRNA expression in males was upregulated after 24 h of food deprivation. In females, only NPGM mRNA expression was increased by fasting. These results suggest that the physiological functions of NPGL and NPGM are different in quail, and these factors are involved in sex differences in energy metabolism.

Micro and macroevolution of sea anemone venom phenotype

Venom is a complex trait with substantial inter- and intraspecific variability resulting from strong selective pressures acting on the expression of many toxic proteins. However, understanding the processes underlying toxin expression dynamics that determine the venom phenotype remains unresolved. By interspecific comparisons we reveal that toxin expression in sea anemones evolves rapidly and that in each species different toxin family dictates the venom phenotype by massive gene duplication events. In-depth analysis of the sea anemone, Nematostella vectensis, revealed striking variation of the dominant toxin (Nv1) diploid copy number across populations (1-24 copies) resulting from independent expansion/contraction events, which generate distinct haplotypes. Nv1 copy number correlates with expression at both the transcript and protein levels with one population having a near-complete loss of Nv1 production. Finally, we establish the dominant toxin hypothesis which incorporates observations in other venomous lineages that animals have convergently evolved a similar strategy in shaping their venom.

Redox Systems Biology: Harnessing the Sentinels of the Cysteine Redoxome

Significance: Cellular redox processes are highly interconnected, yet not in equilibrium, and governed by a wide range of biochemical parameters. Technological advances continue refining how specific redox processes are regulated, but broad understanding of the dynamic interconnectivity between cellular redox modules remains limited. Systems biology investigates multiple components in complex environments and can provide integrative insights into the multifaceted cellular redox state. This review describes the state of the art in redox systems biology as well as provides an updated perspective and practical guide for harnessing thousands of cysteine sensors in the redoxome for multiparameter characterization of cellular redox networks. Recent Advances: Redox systems biology has been applied to genome-scale models and large public datasets, challenged common conceptions, and provided new insights that complement reductionist approaches. Advances in public knowledge and user-friendly tools for proteome-wide annotation of cysteine sentinels can now leverage cysteine redox proteomics datasets to provide spatial, functional, and protein structural information. Critical Issues: Careful consideration of available analytical approaches is needed to broadly characterize the systems-level properties of redox signaling networks and be experimentally feasible. The cysteine redoxome is an informative focal point since it integrates many aspects of redox biology. The mechanisms and redox modules governing cysteine redox regulation, cysteine oxidation assays, proteome-wide annotation of the biophysical and biochemical properties of individual cysteines, and their clinical application are discussed. Future Directions: Investigating the cysteine redoxome at a systems level will uncover new insights into the mechanisms of selectivity and context dependence of redox signaling networks.

Paralithocins, Antimicrobial Peptides with Unusual Disulfide Connectivity from the Red King Crab, Paralithodes camtschaticus

As part of an ongoing exploration of marine invertebrates as a source of new antimicrobial peptides, hemocyte extracts from the red king crab, Paralithodes camtschaticus, were studied. Three cationic cysteine (Cys)-rich peptides, named paralithocins 1-3, were isolated by bioassay-guided purification, and their amino acid sequences determined by Edman degradation and expressed sequences tag analysis. Disulfide bond mapping was performed by high-resolution tandem mass spectrometry. The peptides (38-51 amino acids in length) share a unique Cys motif composed of eight Cys, forming four disulfide bridges with a bond connectivity of (Cys relative position) Cys1-Cys8, Cys2-Cys6, Cys3-Cys5, and Cys4-Cys7, a disulfide arrangement that has not been previously reported among antimicrobial peptides. Thus, paralithocins 1-3 may be assigned to a previously unknown family of antimicrobial peptides within the group of Cys-rich antimicrobial peptides. Although none of the isolated peptides displayed antimicrobial activity against the target strains Escherichia coli, Pseudomonas aeruginosa, or Staphylococcus aureus, they inhibited the growth of several marine bacterial strains with minimal inhibitory concentrations in the 12.5-100 μM range. These findings corroborate the hypothesis that marine organisms are a valuable source for discovering bioactive peptides with new structural motifs.

Engineering covalent loops in proteins can serve as an on/off switch to regulate threaded topologies

Knots in proteins are under active investigation motivating refinements of current techniques and the development of tools to better understand the knotted topology. A strong focus is to identify new knots and expand upon the current understanding of their complex topology. Previous work has shown that the knotted topology, even in the simplest case of knots, encompasses a variety of unique challenges in folding and tying a chain. To bypass many of the in vitro experimental complications involved in working with knots, it is useful to apply methodologies to a more simplified system. The pierced lasso bundles (PLB), we discovered where a single disulphide bridge holds the threaded topology together, presents a simpler system to study knots in vitro. Having a disulphide bridge as an on/off switch between the threaded/unthreaded topology is advantageous because a covalent loop allows manipulation of the knot without directly altering affecting secondary and tertiary structure. Because disulphide bridges are commonly used in protein engineering, a pierced lasso (PL) topology can be easily introduced into a protein of interest to form a knotted topology within a given secondary structure. It is also important to take into account that if formed, disulphides can inadvertently introduce an unwanted PL. This was found upon determination of the crystal structure (PDB code 2YHG) of the recently de novo designed nucleoside hydrolase. Our detailed investigations of the PL presented here will allow researchers to look at the introduction of disulphide bridges in a larger context with respect to potential geometrical consequences on the structure and functional properties of proteins.

An Evolutionary View on Disulfide Bond Connectivities Prediction Using Phylogenetic Trees and a Simple Cysteine Mutation Model

Disulfide bonds are crucial for many structural and functional aspects of proteins. They have a stabilizing role during folding, can regulate enzymatic activity and can trigger allosteric changes in the protein structure. Moreover, knowledge of the topology of the disulfide connectivity can be relevant in genomic annotation tasks and can provide long range constraints for ab-initio protein structure predictors. In this paper we describe PhyloCys, a novel unsupervised predictor of disulfide bond connectivity from known cysteine oxidation states. For each query protein, PhyloCys retrieves and aligns homologs with HHblits and builds a phylogenetic tree using ClustalW. A simplified model of cysteine co-evolution is then applied to the tree in order to hypothesize the presence of oxidized cysteines in the inner nodes of the tree, which represent ancestral protein sequences. The tree is then traversed from the leaves to the root and the putative disulfide connectivity is inferred by observing repeated patterns of tandem mutations between a sequence and its ancestors. A final correction is applied using the Edmonds-Gabow maximum weight perfect matching algorithm. The evolutionary approach applied in PhyloCys results in disulfide bond predictions equivalent to Sephiroth, another approach that takes whole sequence information into account, and is 26-29% better than state of the art methods based on cysteine covariance patterns in multiple sequence alignments, while requiring one order of magnitude fewer homologous sequences (10(3) instead of 10(4)), thus extending its range of applicability. The software described in this article and the datasets used are available at http://ibsquare.be/phylocys.

Evolution of an ancient venom: recognition of a novel family of cnidarian toxins and the common evolutionary origin of sodium and potassium neurotoxins in sea anemone

Despite Cnidaria (sea anemones, corals, jellyfish, and hydroids) being the oldest venomous animal lineage, structure-function relationships, phyletic distributions, and the molecular evolutionary regimes of toxins encoded by these intriguing animals are poorly understood. Hence, we have comprehensively elucidated the phylogenetic and molecular evolutionary histories of pharmacologically characterized cnidarian toxin families, including peptide neurotoxins (voltage-gated Na(+) and K(+) channel-targeting toxins: NaTxs and KTxs, respectively), pore-forming toxins (actinoporins, aerolysin-related toxins, and jellyfish toxins), and the newly discovered small cysteine-rich peptides (SCRiPs). We show that despite long evolutionary histories, most cnidarian toxins remain conserved under the strong influence of negative selection-a finding that is in striking contrast to the rapid evolution of toxin families in evolutionarily younger lineages, such as cone snails and advanced snakes. In contrast to the previous suggestions that implicated SCRiPs in the biomineralization process in corals, we demonstrate that they are potent neurotoxins that are likely involved in the envenoming function, and thus represent the first family of neurotoxins from corals. We also demonstrate the common evolutionary origin of type III KTxs and NaTxs in sea anemones. We show that type III KTxs have evolved from NaTxs under the regime of positive selection, and likely represent a unique evolutionary innovation of the Actinioidea lineage. We report a correlation between the accumulation of episodically adaptive sites and the emergence of novel pharmacological activities in this rapidly evolving neurotoxic clade.

Hyperdimensional analysis of amino acid pair distributions in proteins

Our manuscript presents a novel approach to protein structure analyses. We have organized an 8-dimensional data cube with protein 3D-structural information from 8706 high-resolution non-redundant protein-chains with the aim of identifying packing rules at the amino acid pair level. The cube contains information about amino acid type, solvent accessibility, spatial and sequence distance, secondary structure and sequence length. We are able to pose structural queries to the data cube using program ProPack. The response is a 1, 2 or 3D graph. Whereas the response is of a statistical nature, the user can obtain an instant list of all PDB-structures where such pair is found. The user may select a particular structure, which is displayed highlighting the pair in question. The user may pose millions of different queries and for each one he will receive the answer in a few seconds. In order to demonstrate the capabilities of the data cube as well as the programs, we have selected well known structural features, disulphide bridges and salt bridges, where we illustrate how the queries are posed, and how answers are given. Motifs involving cysteines such as disulphide bridges, zinc-fingers and iron-sulfur clusters are clearly identified and differentiated. ProPack also reveals that whereas pairs of Lys residues virtually never appear in close spatial proximity, pairs of Arg are abundant and appear at close spatial distance, contrasting the belief that electrostatic repulsion would prevent this juxtaposition and that Arg-Lys is perceived as a conservative mutation. The presented programs can find and visualize novel packing preferences in proteins structures allowing the user to unravel correlations between pairs of amino acids. The new tools allow the user to view statistical information and visualize instantly the structures that underpin the statistical information, which is far from trivial with most other SW tools for protein structure analysis.

Selective loss of cysteine residues and disulphide bonds in a potato proteinase inhibitor II family

Disulphide bonds between cysteine residues in proteins play a key role in protein folding, stability, and function. Loss of a disulphide bond is often associated with functional differentiation of the protein. The evolution of disulphide bonds is still actively debated; analysis of naturally occurring variants can promote understanding of the protein evolutionary process. One of the disulphide bond-containing protein families is the potato proteinase inhibitor II (PI-II, or Pin2, for short) superfamily, which is found in most solanaceous plants and participates in plant development, stress response, and defence. Each PI-II domain contains eight cysteine residues (8C), and two similar PI-II domains form a functional protein that has eight disulphide bonds and two non-identical reaction centres. It is still unclear which patterns and processes affect cysteine residue loss in PI-II. Through cDNA sequencing and data mining, we found six natural variants missing cysteine residues involved in one or two disulphide bonds at the first reaction centre. We named these variants Pi7C and Pi6C for the proteins missing one or two pairs of cysteine residues, respectively. This PI-II-7C/6C family was found exclusively in potato. The missing cysteine residues were in bonding pairs but distant from one another at the nucleotide/protein sequence level. The non-synonymous/synonymous substitution (Ka/Ks) ratio analysis suggested a positive evolutionary gene selection for Pi6C and various Pi7C. The selective deletion of the first reaction centre cysteine residues that are structure-level-paired but sequence-level-distant in PI-II illustrates the flexibility of PI-II domains and suggests the functionality of their transient gene versions during evolution.

Amino acid patterns around disulfide bonds

Disulfide bonds provide an inexhaustible source of information on molecular evolution and biological specificity. In this work, we described the amino acid composition around disulfide bonds in a set of disulfide-rich proteins using appropriate descriptors, based on ANOVA (for all twenty natural amino acids or classes of amino acids clustered according to their chemical similarities) and Scheffé (for the disulfide-rich proteins superfamilies) statistics. We found that weakly hydrophilic and aromatic amino acids are quite abundant in the regions around disulfide bonds, contrary to aliphatic and hydrophobic amino acids. The density distributions (as a function of the distance to the center of the disulfide bonds) for all defined entities presented an overall unimodal behavior: the densities are null at short distances, have maxima at intermediate distances and decrease for long distances. In the end, the amino acid environment around the disulfide bonds was found to be different for different superfamilies, allowing the clustering of proteins in a biologically relevant way, suggesting that this type of chemical information might be used as a tool to assess the relationship between very divergent sets of disulfide-rich proteins.

Improving the accuracy of predicting disulfide connectivity by feature selection

Disulfide bonds are primary covalent cross-links formed between two cysteine residues in the same or different protein polypeptide chains, which play important roles in the folding and stability of proteins. However, computational prediction of disulfide connectivity directly from protein primary sequences is challenging due to the nonlocal nature of disulfide bonds in the context of sequences, and the number of possible disulfide patterns grows exponentially when the number of cysteine residues increases. In the previous studies, disulfide connectivity prediction was usually performed in high-dimensional feature space, which can cause a variety of problems in statistical learning, such as the dimension disaster, overfitting, and feature redundancy. In this study, we propose an efficient feature selection technique for analyzing the importance of each feature component. On the basis of this approach, we selected the most important features for predicting the connectivity pattern of intra-chain disulfide bonds. Our results have shown that the high-dimensional features contain redundant information, and the prediction performance can be further improved when these high-dimensional features are reduced to a lower but more compact dimensional space. Our results also indicate that the global protein features contribute little to the formation and prediction of disulfide bonds, while the local sequential and structural information play important roles. All these findings provide important insights for structural studies of disulfide-rich proteins.

DBCP: a web server for disulfide bonding connectivity pattern prediction without the prior knowledge of the bonding state of cysteines

The proper prediction of the location of disulfide bridges is efficient in helping to solve the protein folding problem. Most of the previous works on the prediction of disulfide connectivity pattern use the prior knowledge of the bonding state of cysteines. The DBCP web server provides prediction of disulfide bonding connectivity pattern without the prior knowledge of the bonding state of cysteines. The method used in this server improves the accuracy of disulfide connectivity pattern prediction (Q_p) over the previous studies reported in the literature. This DBCP server can be accessed at http://120.107.8.16/dbcp or http://140.120.14.136/dbcp.

Conformational changes in redox pairs of protein structures

Disulfides are conventionally viewed as structurally stabilizing elements in proteins but emerging evidence suggests two disulfide subproteomes exist. One group mediates the well known role of structural stabilization. A second redox-active group are best known for their catalytic functions but are increasingly being recognized for their roles in regulation of protein function. Redox-active disulfides are, by their very nature, more susceptible to reduction than structural disulfides; and conversely, the Cys pairs that form them are more susceptible to oxidation. In this study, we searched for potentially redox-active Cys Pairs by scanning the Protein Data Bank for structures of proteins in alternate redox states. The PDB contains over 1134 unique redox pairs of proteins, many of which exhibit conformational differences between alternate redox states. Several classes of structural changes were observed, proteins that exhibit: disulfide oxidation following expulsion of metals such as zinc; major reorganisation of the polypeptide backbone in association with disulfide redox-activity; order/disorder transitions; and changes in quaternary structure. Based on evidence gathered supporting disulfide redox activity, we propose disulfides present in alternate redox states are likely to have physiologically relevant redox activity.

Tick-derived Kunitz-type inhibitors as antihemostatic factors

Endogenous Kunitz-type inhibitors target a large number of serine proteinases, including coagulation factors VIIa and Xa, but not thrombin. By contrast, several two-domain Kunitz inhibitors of this major procoagulant proteinase have been isolated from both soft ticks (e.g., ornithodorin from Ornithodoros moubata) and hard ticks (e.g., boophilin from Rhipicephalus (Boophilus) microplus). Surprisingly, these anticoagulants do not follow the canonical mechanism of proteinase inhibition. Instead, their N-terminal residues bind across the thrombin active-site cleft, while C-terminal modules interact with the basic exosite I. The reactive-site loop of boophilin remains fully accessible in its complex with thrombin, and might interact with FXa according to the standard mechanism. A conceptually similar inhibition mechanism is employed by a related inhibitor of the TF-FVIIa complex isolated from Ixodes scapularis, ixolaris. Significant variations to the Kunitz fold are encountered in several of these factors, and are particularly evident in the single-domain FXa inhibitor, O. moubata TAP, and in soft tick-derived platelet antiaggregants (e.g., O. moubata disagregin). Altogether, these antihemostatic factors illustrate the divergence between hard and soft ticks. The unsurpassed versatility of tick-derived Kunitz inhibitors establishes them as valuable tools for biochemical investigations, but also as lead compounds for the development of novel antithrombotics.

Evolutionary history of GS3, a gene conferring grain length in rice

Unlike maize and wheat, where artificial selection is associated with an almost uniform increase in seed or grain size, domesticated rice exhibits dramatic phenotypic diversity for grain size and shape. Here we clone and characterize GS3, an evolutionarily important gene controlling grain size in rice. We show that GS3 is highly expressed in young panicles in both short- and long-grained varieties but is not expressed in leaves or panicles after flowering, and we use genetic transformation to demonstrate that the dominant allele for short grain complements the long-grain phenotype. An association study revealed that a C to A mutation in the second exon of GS3 (A allele) was associated with enhanced grain length in Oryza sativa but was absent from other Oryza species. Linkage disequilibrium (LD) was elevated and there was a 95.7% reduction in nucleotide diversity (theta(pi)) across the gene in accessions carrying the A allele, suggesting positive selection for long grain. Haplotype analysis traced the origin of the long-grain allele to a Japonica-like ancestor and demonstrated introgression into the Indica gene pool. This study indicates a critical role for GS3 in defining the seed morphologies of modern subpopulations of O. sativa and enhances the potential for genetic manipulation of grain size in rice.

Analysis on conservation of disulphide bonds and their structural features in homologous protein domain families

Background

Disulphide bridges are well known to play key roles in stability, folding and functions of proteins. Introduction or deletion of disulphides by site-directed mutagenesis have produced varying effects on stability and folding depending upon the protein and location of disulphide in the 3-D structure. Given the lack of complete understanding it is worthwhile to learn from an analysis of extent of conservation of disulphides in homologous proteins. We have also addressed the question of what structural interactions replaces a disulphide in a homologue in another homologue.

Results

Using a dataset involving 34,752 pairwise comparisons of homologous protein domains corresponding to 300 protein domain families of known 3-D structures, we provide a comprehensive analysis of extent of conservation of disulphide bridges and their structural features. We report that only 54% of all the disulphide bonds compared between the homologous pairs are conserved, even if, a small fraction of the non-conserved disulphides do include cytoplasmic proteins. Also, only about one fourth of the distinct disulphides are conserved in all the members in protein families. We note that while conservation of disulphide is common in many families, disulphide bond mutations are quite prevalent. Interestingly, we note that there is no clear relationship between sequence identity between two homologous proteins and disulphide bond conservation. Our analysis on structural features at the sites where cysteines forming disulphide in one homologue are replaced by non-Cys residues show that the elimination of a disulphide in a homologue need not always result in stabilizing interactions between equivalent residues.

Conclusion

We observe that in the homologous proteins, disulphide bonds are conserved only to a modest extent. Very interestingly, we note that extent of conservation of disulphide in homologous proteins is unrelated to the overall sequence identity between homologues. The non-conserved disulphides are often associated with variable structural features that were recruited to be associated with differentiation or specialisation of protein function.

Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure

MOTIVATION

Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications.

RESULTS

We have developed a novel method to predict disulfide connectivity patterns from protein primary sequence, using a support vector regression (SVR) approach based on multiple sequence feature vectors and predicted secondary structure by the PSIPRED program. The results indicate that our method could achieve a prediction accuracy of 74.4% and 77.9%, respectively, when averaged on proteins with two to five disulfide bridges using 4-fold cross-validation, measured on the protein and cysteine pair on a well-defined non-homologous dataset. We assessed the effects of different sequence encoding schemes on the prediction performance of disulfide connectivity. It has been shown that the sequence encoding scheme based on multiple sequence feature vectors coupled with predicted secondary structure can significantly improve the prediction accuracy, thus enabling our method to outperform most of other currently available predictors. Our work provides a complementary approach to the current algorithms that should be useful in computationally assigning disulfide connectivity patterns and helps in the annotation of protein sequences generated by large-scale whole-genome projects.

AVAILABILITY

The prediction web server and Supplementary Material are accessible at http://foo.maths.uq.edu.au/~huber/disulfide

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.

Radiolytic modification of sulfur-containing amino acid residues in model peptides: fundamental studies for protein footprinting

Protein footprinting based on hydroxyl radical-mediated modification and quantitative mass spectroscopic analysis is a proven technique for examining protein structure, protein-ligand interactions, and structural allostery upon protein complex formation. The reactive and solvent-accessible amino acid side chains function as structural probes; however, correct structural analysis depends on the identification and quantification of all the relevant oxidative modifications within the protein sequence. Sulfur-containing amino acids are oxidized readily and the mechanisms of oxidation are particularly complex, although they have been extensively investigated by EPR and other spectroscopic methods. Here we have undertaken a detailed mass spectrometry study (using electrospray ionization mass spectrometry and tandem mass spectrometry) of model peptides containing cysteine (Cys-SH), cystine (disulfide bonded Cys), and methionine after oxidation using gamma-rays or synchrotron X-rays and have compared these results to those expected from oxidation mechanisms proposed in the literature. Radiolysis of cysteine leads to cysteine sulfonic acid (+48 Da mass shift) and cystine as the major products; other minor products including cysteine sulfinic acid (+32 Da mass shift) and serine (-16 Da mass shift) are observed. Radiolysis of cystine results in the oxidative opening of the disulfide bond and generation of cysteine sulfonic acid and sulfinic acid; however, the rate of oxidation is significantly less than that for cysteine. Radiolysis of methionine gives rise primarily to methionine sulfoxide (+16 Da mass shift); this can be further oxidized to methionine sulfone (+32 Da mass shift) or another product with a -32 Da mass shift likely due to aldehyde formation at the gamma-carbon. Due to the high reactivity of sulfur-containing amino acids, the extent of oxidation is easily influenced by secondary oxidation events or the presence of redox reagents used in standard proteolytic digestions; when these are accounted for, a reactivity order of cysteine > methionine approximately tryptophan > cystine is observed.

Analycys: A database for conservation and conformation of disulphide bonds in homologous protein domains

Disulphide bonds in proteins are known to play diverse roles ranging from folding to structure to function. Thorough knowledge of the conservation status and structural state of the disulphide bonds will help in understanding of the differences in homologous proteins. Here we present a database for the analysis of conservation and conformation of disulphide bonds in SCOP structural families. This database has a wide range of applications including mapping of disulphide bond mutation patterns, identification of disulphide bonds important for folding and stabilization, modeling of protein tertiary structures and in protein engineering. The database can be accessed at: http://bioinformatics.univ-reunion.fr/analycys/.

Disulfide connectivity prediction with 70% accuracy using two-level models

Disulfide bridges stabilize protein structures covalently and play an important role in protein folding. Predicting disulfide connectivity precisely helps towards the solution of protein structure prediction. Previous methods for disulfide connectivity prediction either infer the bonding potential of cysteine pairs or rank alternative disulfide bonding patterns. As a result, these methods encode data according to cysteine pairs (pair-wise) or disulfide bonding patterns (pattern-wise). However, using either encoding scheme alone cannot fully utilize the local and global information of proteins, so the accuracies of previous methods are limited. In this work, we propose a novel two-level framework to predict disulfide connectivity. With this framework, both the pair-wise and pattern-wise encoding schemes are considered. Our models were validated on the datasets derived from SWISS-PROT 39 and 43, and the results demonstrate that our models can combine both local and global information. Compared to previous methods, significant improvements were obtained by our models. Our work may also provide insights to further improvements of disulfide connectivity prediction and increase its applicability in protein structure analysis and prediction.

Exploring synonymous codon usage preferences of disulfide-bonded and non-disulfide bonded cysteines in the E. coli genome

High-quality data about protein structures and their gene sequences are essential to the understanding of the relationship between protein folding and protein coding sequences. Firstly we constructed the EcoPDB database, which is a high-quality database of Escherichia coli genes and their corresponding PDB structures. Based on EcoPDB, we presented a novel approach based on information theory to investigate the correlation between cysteine synonymous codon usages and local amino acids flanking cysteines, the correlation between cysteine synonymous codon usages and synonymous codon usages of local amino acids flanking cysteines, as well as the correlation between cysteine synonymous codon usages and the disulfide bonding states of cysteines in the E. coli genome. The results indicate that the nearest neighboring residues and their synonymous codons of the C-terminus have the greatest influence on the usages of the synonymous codons of cysteines and the usage of the synonymous codons has a specific correlation with the disulfide bond formation of cysteines in proteins. The correlations may result from the regulation mechanism of protein structures at gene sequence level and reflect the biological function restriction that cysteines pair to form disulfide bonds. The results may also be helpful in identifying residues that are important for synonymous codon selection of cysteines to introduce disulfide bridges in protein engineering and molecular biology. The approach presented in this paper can also be utilized as a complementary computational method and be applicable to analyse the synonymous codon usages in other model organisms.

Native and modeled disulfide bonds in proteins: knowledge-based approaches toward structure prediction of disulfide-rich polypeptides

Structure prediction and three-dimensional modeling of disulfide-rich systems are challenging due to the limited number of such folds in the structural databank. We exploit the stereochemical compatibility of substructures in known protein structures to accommodate disulfide bonds in predicting the structures of disulfide-rich polypeptides directly from disulfide connectivity pattern and amino acid sequence in the absence of structural homologs and any other structural information. This knowledge-based approach is illustrated using structure prediction of 40 nonredundant bioactive disulfide-rich polypeptides such as toxins, growth factors, and endothelins available in the structural databank. The polypeptide conformation could be predicted in 35 out of 40 nonredundant entries (87%). Nonhomologous templates could be identified and models could be obtained within 2 A deviation from the query in 29 peptides (72%). This procedure can be accessed from the World Wide Web (http://www.ncbs.res.in/ approximately faculty/mini/dsdbase/dsdbase.html).

Analysis of disulphide bond connectivity patterns in protein tertiary structure

The analysis of disulphide bond containing proteins in the Protein Data Bank (PDB) revealed that out of 27,209 protein structures analyzed, 12,832 proteins contain at least one intra-chain disulphide bond and 811 proteins contain at least one inter-chain disulphide bond. The intra-chain disulphide bond containing proteins can be grouped into 256 categories based on the number of disulphide bonds and the disulphide bond connectivity patterns (DBCPs) that were generated according to the position of half-cystine residues along the protein chain. The PDB entries corresponding to these 256 categories represent 509 unique SCOP superfamilies. A simple web-based computational tool is made freely available at the website that allows flexible queries to be made on the database in order to retrieve useful information on the disulphide bond containing proteins in the PDB. The database is useful to identify the different SCOP superfamilies associated with a particular disulphide bond connectivity pattern or vice versa. It is possible to define a query based either on a single field or a combination of the following fields, i.e., PDB code, protein name, SCOP superfamily name, number of disulphide bonds, disulphide bond connectivity pattern and the number of amino acid residues in a protein chain and retrieve information that match the criterion. Thereby, the database may be useful to select suitable protein structural templates in order to model the more distantly related protein homologs/analogs using the comparative modeling methods.

Structural classification of small, disulfide-rich protein domains

Disulfide-rich domains are small protein domains whose global folds are stabilized primarily by the formation of disulfide bonds and, to a much lesser extent, by secondary structure and hydrophobic interactions. Disulfide-rich domains perform a wide variety of roles functioning as growth factors, toxins, enzyme inhibitors, hormones, pheromones, allergens, etc. These domains are commonly found both as independent (single-domain) proteins and as domains within larger polypeptides. Here, we present a comprehensive structural classification of approximately 3000 small, disulfide-rich protein domains. We find that these domains can be arranged into 41 fold groups on the basis of structural similarity. Our fold groups, which describe broader structural relationships than existing groupings of these domains, bring together representatives with previously unacknowledged similarities; 18 of the 41 fold groups include domains from several SCOP folds. Within the fold groups, the domains are assembled into families of homologs. We define 98 families of disulfide-rich domains, some of which include newly detected homologs, particularly among knottin-like domains. On the basis of this classification, we have examined cases of convergent and divergent evolution of functions performed by disulfide-rich proteins. Disulfide bonding patterns in these domains are also evaluated. Reducible disulfide bonding patterns are much less frequent, while symmetric disulfide bonding patterns are more common than expected from random considerations. Examples of variations in disulfide bonding patterns found within families and fold groups are discussed.

Limited tendency of α-helical residues to form disulfide bridges: a structural explanation

Disulfide bridges have an enormous impact on the structure of a large number of proteins and polypeptides. Understanding the structural basis that regulates their formation may be important for the design of novel peptide-based molecules with a specific fold and stability. Here we report a statistical analysis of the relationships between secondary structure and disulfide bond formation, carried out using a large database of protein structures. Our analyses confirm the observation sporadically reported in previous investigations that cysteine residues located in alpha-helices display a limited tendency to form disulfide bridges. The very low occurrence of the disulfide bond in all alpha-chains compared to all beta-chains indicates that this property is also evident when proteins with different topologies are investigated. Taking advantage of the large database that endorsed the analysis on relatively rare motifs, we demonstrate that cysteine residues embedded in 3(10) helices present a good tendency to form disulfide bonds. This result is somewhat surprising since 3(10) helices are commonly assimilated into alpha-helices. A plausible structural explanation for the observed data has been derived combining analyses of disulfide bond sequence separation and of the length of the different secondary structure elements.

Zona pellucida domain proteins

Many eukaryotic proteins share a sequence designated as the zona pellucida (ZP) domain. This structural element, present in extracellular proteins from a wide variety of organisms, from nematodes to mammals, consists of approximately 260 amino acids with eight conserved cysteine (Cys) residues and is located close to the C terminus of the polypeptide. ZP domain proteins are often glycosylated, modular structures consisting of multiple types of domains. Predictions can be made about some of the structural features of the ZP domain and ZP domain proteins. The functions of ZP domain proteins vary tremendously, from serving as structural components of egg coats, appendicularian mucous houses, and nematode dauer larvae, to serving as mechanotransducers in flies and receptors in mammals and nonmammals. Generally, ZP domain proteins are present in filaments and/or matrices, which is consistent with the role of the domain in protein polymerization. A general mechanism for assembly of ZP domain proteins has been presented. It is likely that the ZP domain plays a common role despite its presence in proteins of widely diverse functions.

Prediction of disulfide connectivity from protein sequences

The difficulties in predicting disulfide connectivity from protein sequences lie in the nonlocal properties of the disulfide bridges that involve cysteine pairs at large sequence separation. Though some progress has been recently made in the prediction of disulfide connectivity, the current methods predict less than half of the disulfide patterns for the data set sharing less than 30% sequence identity. In this report, we use the support vector machines based on sequence features such as the coupling between the local sequence environments of cysteine pair, the cysteines sequence separations, and the global sequence descriptor, such as amino acid content. Our approach is able to predict 55% of the disulfide patterns of proteins with two to five disulfide bridges, which is 11-26% higher than other methods 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.

Cripto-1: an oncofetal gene with many faces

Human Cripto-1 (CR-1), a member of the epidermal growth factor (EGF)-CFC family, has been implicated in embryogenesis and in carcinogenesis. During early vertebrate development, CR-1 functions as a co-receptor for Nodal, a transforming growth factor beta (TGFbeta) family member and is essential for mesoderm and endoderm formation and anterior-posterior and left-right axis establishment. In adult tissues, CR-1 is expressed at a low level in all stages of mammary gland development and expression increases during pregnancy and lactation. Overexpression of CR-1 in mouse mammary epithelial cells leads to their transformation in vitro and, when injected into mammary glands, produces ductal hyperplasias. CR-1 can also enhance migration, invasion, branching morphogenesis and epithelial to mesenchymal transition (EMT) of several mouse mammary epithelial cell lines. Furthermore, transgenic mouse studies have shown that overexpression of a human CR-1 transgene in the mammary gland under the transcriptional control of the mouse mammary tumor virus (MMTV) promoter results in mammary hyperplasias and papillary adenocarcinomas. Finally, CR-1 is expressed at high levels in approximately 50 to 80% of different types of human carcinomas, including breast, cervix, colon, stomach, pancreas, lung, ovary, and testis. In conclusion, EGF-CFC proteins play dual roles as embryonic pattern formation genes and as oncogenes. While during embryogenesis EGF-CFC proteins perform specific and regulatory functions related to cell and tissue patterning, inappropriate expression of these molecules in adult tissues can lead to cellular proliferation and transformation and therefore may be important in the etiology and/or progression of cancer.

Cysteine separations profiles on protein sequences infer disulfide connectivity

MOTIVATION

Disulfide bonds play an important role in protein folding. A precise prediction of disulfide connectivity can strongly reduce the conformational search space and increase the accuracy in protein structure prediction. Conventional disulfide connectivity predictions use sequence information, and prediction accuracy is limited. Here, by using an alternative scheme with global information for disulfide connectivity prediction, higher performance is obtained with respect to other approaches.

RESULT

Cysteine separation profiles have been used to predict the disulfide connectivity of proteins. The separations among oxidized cysteine residues on a protein sequence have been encoded into vectors named cysteine separation profiles (CSPs). Through comparisons of their CSPs, the disulfide connectivity of a test protein is inferred from a non-redundant template set. For non-redundant proteins in SwissProt 39 (SP39) sharing less than 30% sequence identity, the prediction accuracy of a fourfold cross-validation is 49%. The prediction accuracy of disulfide connectivity for proteins in SwissProt 43 (SP43) is even higher (53%). The relationship between the similarity of CSPs and the prediction accuracy is also discussed. The method proposed in this work is relatively simple and can generate higher accuracies compared to conventional methods. It may be also combined with other algorithms for further improvements in protein structure prediction.

AVAILABILITY

The program and datasets are available from the authors upon request.

CONTACT

cykao@csie.ntu.edu.tw.

Cooperativity of the oxidization of cysteines in globular proteins

Based on the 639 non-homologous proteins with 2910 cysteine-containing segments of well-resolved three-dimensional structures, a novel approach has been proposed to predict the disulfide-bonding state of cysteines in proteins by constructing a two-stage classifier combining a first global linear discriminator based on their amino acid composition and a second local support vector machine classifier. The overall prediction accuracy of this hybrid classifier for the disulfide-bonding state of cysteines in proteins has scored 84.1% and 80.1%, when measured on cysteine and protein basis using the rigorous jack-knife procedure, respectively. It shows that whether cysteines should form disulfide bonds depends not only on the global structural features of proteins but also on the local sequence environment of proteins. The result demonstrates the applicability of this novel method and provides comparable prediction performance compared with existing methods for the prediction of the oxidation states of cysteines in proteins.

Disulfide bond assignment of the Ebola virus secreted glycoprotein SGP

The non-structural glycoprotein (SGP) of Ebola virus (EboV) is secreted in large amounts from infected cells as a disulfide-linked homodimer. In this communication, highly purified SGP, derived from Vero E6 cultures infected with the Zaire species of EboV, was used to determine the correct localization of inter- and intrachain disulfide bonds. Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry analysis of proteolytic cleavage fragments indicates that all cysteines (six per monomeric unit) form unique disulfide bonds. Monomers of the SGP homodimer are joined in a parallel manner by two intersubunit disulfide bonds formed between paired N-terminal and C-terminal cysteines (C53-C53' and C306-C306'). The remaining cysteines are involved in intrachain disulfide bonding (paired as C108-C135 and C121-C147), which resembles the disulfide bond topology of fibronectin type II domains. The findings presented here provide the foundation for future studies aimed at defining the structural and functional properties of SGP.

CysView: protein classification based on cysteine pairing patterns

CysView is a web-based application tool that identifies and classifies proteins according to their disulfide connectivity patterns. It accepts a dataset of annotated protein sequences in various formats and returns a graphical representation of cysteine pairing patterns. CysView displays cysteine patterns for those records in the data with disulfide annotations. It allows the viewing of records grouped by connectivity patterns. CysView's utility as an analysis tool was demonstrated by the rapid and correct classification of scorpion toxin entries from GenPept on the basis of their disulfide pairing patterns. It has proved useful for rapid detection of irrelevant and partial records, or those with incomplete annotations. CysView can be used to support distant homology between proteins. CysView is publicly available at http://research.i2r.a-star.edu.sg/CysView/.

Prediction of the disulfide-bonding state of cysteines in proteins based on dipeptide composition

In this paper, a novel approach has been introduced to predict the disulfide-bonding state of cysteines in proteins by means of a linear discriminator based on their dipeptide composition. The prediction is performed with a newly enlarged dataset with 8114 cysteine-containing segments extracted from 1856 non-homologous proteins of well-resolved three-dimensional structures. The oxidation of cysteines exhibits obvious cooperativity: almost all cysteines in disulfide-bond-containing proteins are in the oxidized form. This cooperativity can be well described by protein's dipeptide composition, based on which the prediction accuracy of the oxidation form of cysteines scores as high as 89.1% and 85.2%, when measured on cysteine and protein basis using the rigorous jack-knife procedure, respectively. The result demonstrates the applicability of this new relatively simple method and provides superior prediction performance compared with existing methods for the prediction of the oxidation states of cysteines in proteins.