CysView: protein classification based on cysteine pairing patterns

A Three-Dimensional Model of Human Lysyl Oxidase, a Cross-Linking Enzyme

Lysyl oxidase (LOX) is a cross-linking enzyme identified 50 years ago, but its 3D structure is still unknown. We have thus built a 3D model of human LOX by homology modeling using the X-ray structure of human lysyl oxidase-like 2 as a template. This model is the first one to recapitulate all known biochemical features of LOX, namely, the coordination of the copper ion and the formation of the lysine tyrosylquinone cofactor and the disulfide bridges. Furthermore, this model is stable during a 1 μs molecular dynamics simulation. The catalytic site is located in a groove surrounded by two loops. The distance between these loops fluctuated during the simulations, which suggests that the groove forms a hinge with a variable opening, which is able to accommodate the various sizes of LOX substrates. This 3D model is a pre-requisite to perform docking experiments with LOX substrates and other partners to identify binding sites and to design new LOX inhibitors specific for therapeutic purpose.

Short toxin-like proteins attack the defense line of innate immunity

ClanTox (classifier of animal toxins) was developed for identifying toxin-like candidates from complete proteomes. Searching mammalian proteomes for short toxin-like proteins (coined TOLIPs) revealed a number of overlooked secreted short proteins with an abundance of cysteines throughout their sequences. We applied bioinformatics and data-mining methods to infer the function of several top predicted candidates. We focused on cysteine-rich peptides that adopt the fold of the three-finger proteins (TFPs). We identified a cluster of duplicated genes that share a structural similarity with elapid neurotoxins, such as α-bungarotoxin. In the murine proteome, there are about 60 such proteins that belong to the Ly6/uPAR family. These proteins are secreted or anchored to the cell membrane. Ly6/uPAR proteins are associated with a rich repertoire of functions, including binding to receptors and adhesion. Ly6/uPAR proteins modulate cell signaling in the context of brain functions and cells of the innate immune system. We postulate that TOLIPs, as modulators of cell signaling, may be associated with pathologies and cellular imbalance. We show that proteins of the Ly6/uPAR family are associated with cancer diagnosis and malfunction of the immune system.

Protein disulfide topology determination through the fusion of mass spectrometric analysis and sequence-based prediction using Dempster-Shafer theory

Background

Disulfide bonds constitute one of the most important cross-linkages in proteins and significantly influence protein structure and function. At the state-of-the-art, various methodological frameworks have been proposed for identification of disulfide bonds. These include among others, mass spectrometry-based methods, sequence-based predictive approaches, as well as techniques like crystallography and NMR. Each of these frameworks has its advantages and disadvantages in terms of pre-requisites for applicability, throughput, and accuracy. Furthermore, the results from different methods may concur or conflict in parts.

Results

In this paper, we propose a novel and theoretically rigorous framework for disulfide bond determination based on information fusion from different methods using an extended formulation of Dempster-Shafer theory. A key advantage of our approach is that it can automatically deal with concurring as well as conflicting evidence in a data-driven manner. Using the proposed framework, we have developed a method for disulfide bond determination that combines results from sequence-based prediction and mass spectrometric inference. This method leads to more accurate disulfide bond determination than any of the constituent methods taken individually. Furthermore, experiments indicate that the method improves the accuracy of bond identification as compared to leading extant methods at the state-of-the-art. Finally, the proposed framework is extensible in that results from any number of approaches can be incorporated. Results obtained using this framework can especially be useful in cases where the complexity of the bonding patterns coupled with specificities of the fragmentation pattern or limitations of computational models impair any single method to perform consistently across a diverse set of molecules.

Association of Putative Members to Family of Mosquito Odorant Binding Proteins: Scoring Scheme Using Fuzzy Functional Templates and Cys Residue Positions

Proteins may be related to each other very specifically as homologous subfamilies. Proteins can also be related to diverse proteins at the super family level. It has become highly important to characterize the existing sequence databases by their signatures to facilitate the function annotation of newly added sequences. The algorithm described here uses a scheme for the classification of odorant binding proteins on the basis of functional residues and Cys-pairing. The cysteine-based scoring scheme not only helps in unambiguously identifying families like odorant binding proteins (OBPs), but also aids in their classification at the subfamily level with reliable accuracy. The algorithm was also applied to yet another cysteine-rich family, where similar accuracy was observed that ensures the application of the protocol to other families.

Short toxin-like proteins abound in Cnidaria genomes

Cnidaria is a rich phylum that includes thousands of marine species. In this study, we focused on Anthozoa and Hydrozoa that are represented by the Nematostella vectensis (Sea anemone) and Hydra magnipapillata genomes. We present a method for ranking the toxin-like candidates from complete proteomes of Cnidaria. Toxin-like functions were revealed using ClanTox, a statistical machine-learning predictor trained on ion channel inhibitors from venomous animals. Fundamental features that were emphasized in training ClanTox include cysteines and their spacing along the sequences. Among the 83,000 proteins derived from Cnidaria representatives, we found 170 candidates that fulfill the properties of toxin-like-proteins, the vast majority of which were previously unrecognized as toxins. An additional 394 short proteins exhibit characteristics of toxin-like proteins at a moderate degree of confidence. Remarkably, only 11% of the predicted toxin-like proteins were previously classified as toxins. Based on our prediction methodology and manual annotation, we inferred functions for over 400 of these proteins. Such functions include protease inhibitors, membrane pore formation, ion channel blockers and metal binding proteins. Many of the proteins belong to small families of paralogs. We conclude that the evolutionary expansion of toxin-like proteins in Cnidaria contributes to their fitness in the complex environment of the aquatic ecosystem.

Scorpion toxins specific for potassium (K+) channels: a historical overview of peptide bioengineering

Scorpion toxins have been central to the investigation and understanding of the physiological role of potassium (K⁺) channels and their expansive function in membrane biophysics. As highly specific probes, toxins have revealed a great deal about channel structure and the correlation between mutations, altered regulation and a number of human pathologies. Radio- and fluorescently-labeled toxin isoforms have contributed to localization studies of channel subtypes in expressing cells, and have been further used in competitive displacement assays for the identification of additional novel ligands for use in research and medicine. Chimeric toxins have been designed from multiple peptide scaffolds to probe channel isoform specificity, while advanced epitope chimerization has aided in the development of novel molecular therapeutics. Peptide backbone cyclization has been utilized to enhance therapeutic efficiency by augmenting serum stability and toxin half-life in vivo as a number of K⁺-channel isoforms have been identified with essential roles in disease states ranging from HIV, T-cell mediated autoimmune disease and hypertension to various cardiac arrhythmias and Malaria. Bioengineered scorpion toxins have been monumental to the evolution of channel science, and are now serving as templates for the development of invaluable experimental molecular therapeutics.

CMD: A Database to Store the Bonding States of Cysteine Motifs with Secondary Structures

Computational approaches to the disulphide bonding state and its connectivity pattern prediction are based on various descriptors. One descriptor is the amino acid sequence motifs flanking the cysteine residue motifs. Despite the existence of disulphide bonding information in many databases and applications, there is no complete reference and motif query available at the moment. Cysteine motif database (CMD) is the first online resource that stores all cysteine residues, their flanking motifs with their secondary structure, and propensity values assignment derived from the laboratory data. We extracted more than 3 million cysteine motifs from PDB and UniProt data, annotated with secondary structure assignment, propensity value assignment, and frequency of occurrence and coefficiency of their bonding status. Removal of redundancies generated 15875 unique flanking motifs that are always bonded and 41577 unique patterns that are always nonbonded. Queries are based on the protein ID, FASTA sequence, sequence motif, and secondary structure individually or in batch format using the provided APIs that allow remote users to query our database via third party software and/or high throughput screening/querying. The CMD offers extensive information about the bonded, free cysteine residues, and their motifs that allows in-depth characterization of the sequence motif composition.

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.

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.

Solution structure of the phytotoxic protein PcF: the first characterized member of the Phytophthora PcF toxin family

The PcF protein from Phytophthora cactorum is the first member of the "PcF toxin family" from the plant pathogens Phytophthora spp. It is able to induce withering in tomato and strawberry leaves. The lack of sequence similarity with other proteins hampers the identification of the molecular mechanisms responsible for its toxicity. Here, we show that the six cysteines form a disulphide pattern that is exclusive for PcF and essential for the protein withering activity. The NMR solution structure identifies a novel fold among protein effectors: a helix-loop-helix motif. The presence of a negatively charged surface suggests that it might act as a site of electrostatic interaction. Interestingly, a good fold match with Ole e 6, a plant protein with allergenic activity, highlighted the spatial superimposition of a stretch of identical residues. This finding suggests a possible biological activity based on molecular mimicry.

ClanTox: a classifier of short animal toxins

Toxins are detected in sporadic species along the evolutionary tree of the animal kingdom. Venomous animals include scorpions, snakes, bees, wasps, frogs and numerous animals living in the sea such as the stonefish, snail, jellyfish, hydra and more. Interestingly, proteins that share a common scaffold with animal toxins also exist in non-venomous species. However, due to their short length and primary sequence diversity, these, toxin-like proteins remain undetected by classical search engines and genome annotation tools. We construct a toxin classification machine and web server called ClanTox (Classifier of Animal Toxins) that is based on the extraction of sequence-driven features from the primary protein sequence followed by the application of a classification system trained on known animal toxins. For a given input list of sequences, from venomous or non-venomous settings, the ClanTox system predicts whether each sequence is toxin-like. ClanTox provides a ranked list of positively predicted candidates according to statistical confidence. For each protein, additional information is presented including the presence of a signal peptide, the number of cysteine residues and the associated functional annotations. ClanTox is a discovery-prediction tool for a relatively overlooked niche of toxin-like cell modulators, many of which are therapeutic agent candidates. The ClanTox web server is freely accessible at http://www.clantox.cs.huji.ac.il.

DISULFIND: a disulfide bonding state and cysteine connectivity prediction server

DISULFIND is a server for predicting the disulfide bonding state of cysteines and their disulfide connectivity starting from sequence alone. Optionally, disulfide connectivity can be predicted from sequence and a bonding state assignment given as input. The output is a simple visualization of the assigned bonding state (with confidence degrees) and the most likely connectivity patterns. The server is available at .

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.

HCA and HML isolated from the red marine algae Hypnea cervicornis and Hypnea musciformis define a novel lectin family

HCA and HML represent lectins isolated from the red marine algae Hypnea cervicornis and Hypnea musciformis, respectively. Hemagglutination inhibition assays suggest that HML binds GalNAc/Gal substituted with a neutral sugar through 1-3, 1-4, or 1-2 linkages in O-linked mucin-type glycans, and Fuc(alpha1-6)GlcNAc of N-linked glycoproteins. The specificity of HCA includes the epitopes recognized by HML, although the glycoproteins inhibited distinctly HML and HCA. The agglutinating activity of HCA was inhibited by GalNAc, highlighting the different fine sugar epitope-recognizing specificity of each algal lectin. The primary structures of HCA (9193+/-3 Da) and HML (9357+/-1 Da) were determined by Edman degradation and tandem mass spectrometry of the N-terminally blocked fragments. Both lectins consist of a mixture of a 90-residue polypeptide containing seven intrachain disulfide bonds and two disulfide-bonded subunits generated by cleavage at the bond T50-E51 (HCA) and R50-E51 (HML). The amino acid sequences of HCA and HML display 55% sequence identity (80% similarity) between themselves, but do not show discernible sequence and cysteine spacing pattern similarities with any other known protein structure, indicating that HCA and HML belong to a novel lectin family. Alignment of the amino acid sequence of the two lectins revealed the existence of internal domain duplication, with residues 1-47 and 48-90 corresponding to the N- and C-terminal domains, respectively. The six conserved cysteines in each domain may form three intrachain cysteine linkages, and the unique cysteine residues of the N-terminal (Cys46) and the C-terminal (Cys71) domains may form an intersubunit disulfide bond.