Prediction of tyrosine sulfation sites in animal viruses

Synthesis and Reactivity of Masked Organic Sulfates

Nature offers a variety of structurally unique, sulfated endobiotics including sulfated glycosaminoglycans, sulfated tyrosine peptides, sulfated steroids/bile acids/catecholamines. Sulfated molecules display a large number of biological activities including antithrombotic, antimicrobial, anticancer, anti-inflammatory, and others, which arise from modulation of intracellular signaling and enhanced in vivo retention of certain hormones. These characteristics position sulfated molecules very favorably as drug-like agents. However, few have reached the clinic. Major hurdles exist in realizing sulfated molecules as drugs. This state-of-the-art has been transformed through recent works on the development of sulfate masking technologies for both alkyl (sulfated carbohydrates, sulfated steroids) and aryl (sTyr-bearing peptides/proteins, sulfated flavonoids) sulfates. This review compiles the literature on different strategies implemented for different types of sulfate groups. Starting from early efforts in protection of sulfate groups to the design of newer SuFEx, trichloroethyl, and gem-dimethyl-based protection technologies, this review presents the evolution and application of concepts in realizing highly diverse, sulfated molecules as candidate drugs and/or prodrugs. Overall, the newer strategies for sulfate masking and demasking are likely to greatly enhance the design and development of sulfated molecules as non-toxic drugs of the future.

Bioinformatics and Translation Elongation

Codon usage depends on mutation bias, tRNA-mediated selection, and the need for high efficiency and accuracy in translation. One codon in a synonymous codon family is often strongly over-used, especially in highly expressed genes, which often leads to a high dN/dS ratio because dS is very small. Many different codon usage indices have been proposed to measure codon usage and codon adaptation. Sense codon could be misread by release factors and stop codons misread by tRNAs, which also contribute to codon usage in rare cases. This chapter outlines the conceptual framework on codon evolution, illustrates codon-specific and gene-specific codon usage indices, and presents their applications. A new index for codon adaptation that accounts for background mutation bias (Index of Translation Elongation) is presented and contrasted with codon adaptation index (CAI) which does not consider background mutation bias. They are used to re-analyze data from a recent paper claiming that translation elongation efficiency matters little in protein production. The reanalysis disproves the claim.

High-Throughput Screening of Sulfated Proteins by Using a Genome-Wide Proteome Microarray and Protein Tyrosine Sulfation System

Protein tyrosine sulfation (PTS) is a widespread posttranslational modification that induces intercellular and extracellular responses by regulating protein-protein interactions and enzymatic activity. Although PTS affects numerous physiological and pathological processes, only a small fraction of the total predicted sulfated proteins has been identified to date. Here, we localized the potential sulfation sites of Escherichia coli proteins on a proteome microarray by using a 3'-phosphoadenosine 5'-phosphosulfate (PAPS) synthase-coupled tyrosylprotein sulfotransferase (TPST) catalysis system that involves in situ PAPS generation and TPST catalysis. Among the 4256 E. coli K12 proteins, 875 sulfated proteins were identified using antisulfotyrosine primary and Cy3-labeled antimouse secondary antibodies. Our findings add considerably to the list of potential proteins subjected to tyrosine sulfation. Similar procedures can be applied to identify sulfated proteins in yeast and human proteome microarrays, and we expect such approaches to contribute substantially to the understanding of important human diseases.

Position weight matrix, gibbs sampler, and the associated significance tests in motif characterization and prediction

Position weight matrix (PWM) is not only one of the most widely used bioinformatic methods, but also a key component in more advanced computational algorithms (e.g., Gibbs sampler) for characterizing and discovering motifs in nucleotide or amino acid sequences. However, few generally applicable statistical tests are available for evaluating the significance of site patterns, PWM, and PWM scores (PWMS) of putative motifs. Statistical significance tests of the PWM output, that is, site-specific frequencies, PWM itself, and PWMS, are in disparate sources and have never been collected in a single paper, with the consequence that many implementations of PWM do not include any significance test. Here I review PWM-based methods used in motif characterization and prediction (including a detailed illustration of the Gibbs sampler for de novo motif discovery), present statistical and probabilistic rationales behind statistical significance tests relevant to PWM, and illustrate their application with real data. The multiple comparison problem associated with the test of site-specific frequencies is best handled by false discovery rate methods. The test of PWM, due to the use of pseudocounts, is best done by resampling methods. The test of individual PWMS for each sequence segment should be based on the extreme value distribution.

Incorporating support vector machine for identifying protein tyrosine sulfation sites

Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty-two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five-fold cross-validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in five-fold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites.

Predicting sulfotyrosine sites using the random forest algorithm with significantly improved prediction accuracy

BACKGROUND

Tyrosine sulfation is one of the most important posttranslational modifications. Due to its relevance to various disease developments, tyrosine sulfation has become the target for drug design. In order to facilitate efficient drug design, accurate prediction of sulfotyrosine sites is desirable. A predictor published seven years ago has been very successful with claimed prediction accuracy of 98%. However, it has a particularly low sensitivity when predicting sulfotyrosine sites in some newly sequenced proteins.

RESULTS

A new approach has been developed for predicting sulfotyrosine sites using the random forest algorithm after a careful evaluation of seven machine learning algorithms. Peptides are formed by consecutive residues symmetrically flanking tyrosine sites. They are then encoded using an amino acid hydrophobicity scale. This new approach has increased the sensitivity by 22%, the specificity by 3%, and the total prediction accuracy by 10% compared with the previous predictor using the same blind data. Meanwhile, both negative and positive predictive powers have been increased by 9%. In addition, the random forest model has an excellent feature for ranking the residues flanking tyrosine sites, hence providing more information for further investigating the tyrosine sulfation mechanism. A web tool has been implemented at http://ecsb.ex.ac.uk/sulfotyrosine for public use.

CONCLUSION

The random forest algorithm is able to deliver a better model compared with the Hidden Markov Model, the support vector machine, artificial neural networks, and others for predicting sulfotyrosine sites. The success shows that the random forest algorithm together with an amino acid hydrophobicity scale encoding can be a good candidate for peptide classification.

Binding thermodynamics of the N-terminal peptide of the CCR5 coreceptor to HIV-1 envelope glycoprotein gp120

The initial events of HIV-1 cell infection involve the sequential binding of the viral envelope glycoprotein gp120 to the cellular CD4 receptor and the coreceptor, usually CCR5 or CXCR4. Binding to the coreceptor triggers the chain of events that culminates with the entry of the virus into the cell. In this process, the interaction of gp120 with the tyrosine-sulfated N-terminus of CCR5 is critical; however, this interaction has never been characterized at a quantitative or thermodynamic level. Here, we present the first thermodynamic analysis of the interaction of gp120 with the N-terminal peptide of the CCR5 coreceptor. Microcalorimetric titrations demonstrate that measurable binding of S22 peptide, a 22-amino acid tyrosine-sulfated peptide corresponding to the CCR5 N-terminus, requires prior binding of CD4 to gp120. The S22 peptide binds to the gp120-CD4 complex with a binding affinity of 4.5 x 10(5) M(-1) (K(d) = 2.2 microM) in an enthalpically and entropically favorable process. An identical peptide lacking the sulfated tyrosine residues is unable to bind the gp120-CD4 complex. These results indicate that the sulfated tyrosines contribute close to -3.5 kcal/mol to the Gibbs energy of binding. Furthermore, the S22 peptide is a competitive inhibitor of the 17b HIV-1 neutralizing antibody, which is known to bind to the CCR5 coreceptor site in gp120. Together, these results point toward compounds containing sulfated aromatic groups as potential inhibitors of viral entry. In analogy to existing inhibitors that bind to the CCR5 coreceptor directly, these compounds will accomplish the same result by binding to the coreceptor site in gp120.

Toward a framework for sulfoproteomics: Synthesis and characterization of sulfotyrosine-containing peptides

Tyrosine sulfation is one of the most common post-translational modifications in secreted and transmembrane proteins and a key modulator of extracellular protein-protein interactions. Several proteins known to be tyrosine sulfated play important roles in physiological processes, and in some cases a direct link between protein function and tyrosine sulfation has been established. In blood coagulation, tyrosine sulfation of factor VIII is required for efficient binding of von Willebrand factor; in leukocyte adhesion, tyrosine sulfation of the P-selectin glycoprotein ligand-1 mediates high-affinity binding to P-selectin; and in leukocyte chemotaxis, tyrosine sulfation of chemokine receptors is required for optimal interaction with chemokine ligands. Furthermore, tyrosine sulfation has been implicated in several infectious diseases. In particular, tyrosine sulfation of the HIV-1 co-receptor CCR5 is required for viral entry into host cells and tyrosine sulfation of the Duffy antigen/receptor for chemokines is crucial for erythrocyte invasion by the malaria parasite plasmodium vivax. Despite increasing interest in tyrosine sulfation in recent years, the sulfoproteome still remains largely unexplored. To date, only a relatively small number of sulfotyrosine-containing peptides and proteins have been identified, and a specific role for tyrosine sulfation has not been established for most of these. Here, we provide an overview of the biology and enzymology of tyrosine sulfation and discuss recent developments in preparative and analytical methods that are central to sulfoproteome research.

Protein sulfation analysis—A primer

The aim of this review is to present an overview of protein sulfation in the context of 'modificomics', i.e. post-translational modification-specific proteome research. In addition to a short introduction to the biology of protein sulfation (part 1), we will provide detailed discussion regarding (i) methods and tools for prediction of protein tyrosine sulfation sites (part 2), (ii) biochemical techniques used for protein sulfation analysis (part 3.1), and (iii) mass spectrometric strategies and methods applied to protein sulfation analysis (part 3.2). We will highlight strengths and limitations of different strategies and approaches (including references), providing a primer for newcomers to protein sulfation analysis.

Autoimmunity and tyrosine sulfation

Homeostasis of the immune system is achieved through refined regulation and communication between immunologically relevant receptor and their cognate ligands amongst mononuclear cells during ontogeny and day to day immune responses. An aberrance in not only the kinetics of receptor expression but also the relative diversity of expression alter these events. More importantly, improper modulation of ligand binding affinity can be a triggering event that results in autoimmunity. As one of the most common post-translational modifications, tyrosine sulfation possesses the ability to regulate mononuclear cell function at various stages of the immune response. For example, removal of sulfated tyrosine residues consistently decreases the binding affinity of the ligand to its corresponding receptor as exemplified by studies of several tyrosine sulfated proteins such as PSGL-1, CD44v5, CCR5, and CXCR4, all known to play a role in a variety of autoimmune diseases. This review defines possible roles that tyrosine sulfated proteins may play in the pathogenesis of autoimmune diseases.

CC and CX3C chemokines differentially interact with the N terminus of the human cytomegalovirus-encoded US28 receptor

Human cytomegalovirus (HCMV) is the causative agent of life-threatening systemic diseases in immunocompromised patients as well as a risk factor for vascular pathologies, like atherosclerosis, in immunocompetent individuals. HCMV encodes a G-protein-coupled receptor (GPCR), referred to as US28, that displays homology to the human chemokine receptor CCR1 and binds several chemokines of the CC family as well as the CX3C chemokine fractalkine with high affinity. Most importantly, following HCMV infection, US28 activates several intracellular pathways, either constitutively or in a chemokine-dependent manner. In this study, our goal was to understand the molecular interactions between chemokines and the HCMV-encoded US28 receptor. To achieve this goal, a double approach has been used, consisting in the analysis of both receptor and ligand mutants. This approach has led us to identify several amino acids located in the N terminus of US28 that differentially contribute to the high affinity binding of CC versus CX3C chemokines. Additionally, our results highlight the importance of secondary modifications occurring at US28, such as sulfation, for ligand recognition. Finally, the effects of chemokine dimerization and interaction with glycosaminoglycans (GAGs) on chemokine binding and activation of US28 were investigated as well using CCL4 as model ligand. In line with the two-state model describing chemokine/receptor interaction, we show that an aromatic residue in the N-loop region of CCL4 promotes tight binding to US28, whereas receptor activation depends on the presence of the N terminus of CCL4, as shown previously for CCR5.