Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide.
TL;DR: A structural homology exists between the two viruses, despite minimal primary sequence conservation, and a synthetic peptide containing the HAV-specific amino acid sequence of one of these sites induced anti-HAV-neutralizing antibodies.
Abstract: Comparative surface feature analyses of the VP1 sequences of hepatitis A virus (HAV) and poliovirus type 1 allowed an alignment of the two sequences and an identification of probable HAV neutralization antigenic sites. A synthetic peptide containing the HAV-specific amino acid sequence of one of these sites induced anti-HAV-neutralizing antibodies. It is concluded that a structural homology exists between the two viruses, despite minimal primary sequence conservation.
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TL;DR: Scansite identifies short protein sequence motifs that are recognized by modular signaling domains, phosphorylated by protein Ser/Thr- or Tyr-kinases or mediate specific interactions with protein or phospholipid ligands, allowing segments of biological pathways to be constructed in silico.
Abstract: Scansite identifies short protein sequence motifs that are recognized by modular signaling domains, phosphorylated by protein Ser/Thr- or Tyr-kinases or mediate specific interactions with protein or phospholipid ligands. Each sequence motif is represented as a position-specific scoring matrix (PSSM) based on results from oriented peptide library and phage display experiments. Predicted domain-motif interactions from Scansite can be sequentially combined, allowing segments of biological pathways to be constructed in silico. The current release of Scansite, version 2.0, includes 62 motifs characterizing the binding and/or substrate specificities of many families of Ser/Thr- or Tyr-kinases, SH2, SH3, PDZ, 14-3-3 and PTB domains, together with signature motifs for PtdIns(3,4,5)P(3)-specific PH domains. Scansite 2.0 contains significant improvements to its original interface, including a number of new generalized user features and significantly enhanced performance. Searches of all SWISS-PROT, TrEMBL, Genpept and Ensembl protein database entries are now possible with run times reduced by approximately 60% when compared with Scansite version 1.0. Scansite 2.0 allows restricted searching of species-specific proteins, as well as isoelectric point and molecular weight sorting to facilitate comparison of predictions with results from two-dimensional gel electrophoresis experiments. Support for user-defined motifs has been increased, allowing easier input of user-defined matrices and permitting user-defined motifs to be combined with pre-compiled Scansite motifs for dual motif searching. In addition, a new series of Sequence Match programs for non-quantitative user-defined motifs has been implemented. Scansite is available via the World Wide Web at http://scansite.mit.edu.
1,619 citations
Cites methods from "Induction of hepatitis A virus-neut..."
...On the next line, a plot of the predicted surface accessibility at each residue, calculated using a 6 amino acid running window (19) is shown....
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TL;DR: An improved method for predicting linear B-cell epitopes by combining the hidden Markov model with one of the best propensity scale methods, which performs significantly better than any of the other methods tested.
Abstract: Background: B-cell epitopes are the sites of molecules that are recognized by antibodies of the immune system. Knowledge of B-cell epitopes may be used in the design of vaccines and diagnostics tests. It is therefore of interest to develop improved methods for predicting B-cell epitopes. In this paper, we describe an improved method for predicting linear B-cell epitopes. Results: In order to do this, three data sets of linear B-cell epitope annotated proteins were constructed. A data set was collected from the literature, another data set was extracted from the AntiJen database and a data sets of epitopes in the proteins of HIV was collected from the Los Alamos HIV database. An unbiased validation of the methods was made by testing on data sets on which they were neither trained nor optimized on. We have measured the performance in a nonparametric way by constructing ROC-curves. Conclusion: The best single method for predicting linear B-cell epitopes is the hidden Markov model. Combining the hidden Markov model with one of the best propensity scale methods, we obtained the BepiPred method. When tested on the validation data set this method performs significantly better than any of the other methods tested. The server and data sets are publicly available at http://www.cbs.dtu.dk/services/BepiPred.
1,153 citations
Cites methods or result from "Induction of hepatitis A virus-neut..."
...[9] gave slightly better results than the other scales tested....
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...The scales used in this study are based on antigenicity [20], hydrophilicity [6], inverted hydrophobicity [21,22], accessibility [9] and secondary structure [7,8]....
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...[9] (accessibility) gave slightly better results than the other scales tested....
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TL;DR: The standard feed‐forward (FNN) and recurrent neural network (RNN) have been used in this study for predicting B‐cell epitopes in an antigenic sequence and it has been observed that RNN (JE) was more successful than FNN in the prediction of B‐ cell epitopes.
Abstract: B-cell epitopes play a vital role in the development of peptide vaccines, in diagnosis of diseases, and also for allergy research. Experimental methods used for characterizing epitopes are time consuming and demand large resources. The availability of epitope prediction method(s) can rapidly aid experimenters in simplifying this problem. The standard feed-forward (FNN) and recurrent neural network (RNN) have been used in this study for predicting B-cell epitopes in an antigenic sequence. The networks have been trained and tested on a clean data set, which consists of 700 non-redundant B-cell epitopes obtained from Bcipep database and equal number of non-epitopes obtained randomly from Swiss-Prot database. The networks have been trained and tested at different input window length and hidden units. Maximum accuracy has been obtained using recurrent neural network (Jordan network) with a single hidden layer of 35 hidden units for window length of 16. The final network yields an overall prediction accuracy of 65.93% when tested by fivefold cross-validation. The corresponding sensitivity, specificity, and positive prediction values are 67.14, 64.71, and 65.61%, respectively. It has been observed that RNN (JE) was more successful than FNN in the prediction of B-cell epitopes. The length of the peptide is also important in the prediction of B-cell epitopes from antigenic sequences. The webserver ABCpred is freely available at www.imtech.res.in/raghava/abcpred/.
1,112 citations
TL;DR: It is shown that Smad2 and Smad3 interacted with the kinase‐deficient TGF‐β type I receptor (TβR)‐I after it was phosphorylated by TβR‐II kinase, which suggests that T GF‐β induces heteromeric complexes of Smad 2, 3 and 4, and their concomitant translocation to the nucleus, which is required for efficient TGF-β signal transduction.
Abstract: Smad family members are newly identified essential intracellular signalling components of the transforming growth factor-beta (TGF-beta) superfamily. Smad2 and Smad3 are structurally highly similar and mediate TGF-beta signals. Smad4 is distantly related to Smads 2 and 3, and forms a heteromeric complex with Smad2 after TGF-beta or activin stimulation. Here we show that Smad2 and Smad3 interacted with the kinase-deficient TGF-beta type I receptor (TbetaR)-I after it was phosphorylated by TbetaR-II kinase. TGF-beta1 induced phosphorylation of Smad2 and Smad3 in Mv1Lu mink lung epithelial cells. Smad4 was found to be constitutively phosphorylated in Mv1Lu cells, the phosphorylation level remaining unchanged upon TGF-beta1 stimulation. Similar results were obtained using HSC4 cells, which are also growth-inhibited by TGF-beta. Smads 2 and 3 interacted with Smad4 after TbetaR activation in transfected COS cells. In addition, we observed TbetaR-activation-dependent interaction between Smad2 and Smad3. Smads 2, 3 and 4 accumulated in the nucleus upon TGF-beta1 treatment in Mv1Lu cells, and showed a synergistic effect in a transcriptional reporter assay using the TGF-beta-inducible plasminogen activator inhibitor-1 promoter. Dominant-negative Smad3 inhibited the transcriptional synergistic response by Smad2 and Smad4. These data suggest that TGF-beta induces heteromeric complexes of Smads 2, 3 and 4, and their concomitant translocation to the nucleus, which is required for efficient TGF-beta signal transduction.
1,039 citations
TL;DR: The Lasergene software suite provides the functions and customization tools needed so that users can perform analyses the software writers never imagined.
Abstract: Lasergene's eight modules provide tools that enable users to accomplish each step of sequence analysis, from trimming and assembly of sequence data, to gene discovery, annotation, gene product analysis, sequence similarity searches, sequence alignment, phylogenetic analysis, oligonucleotide primer design, cloning strategies, and publication of the results. The Lasergene software suite provides the functions and customization tools needed so that users can perform analyses the software writers never imagined.
963 citations
References
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TL;DR: The algorithm is shown to be at least as good as, and usually superior to, the reported prediction methods assessed in the same way and the implication in protein folding is discussed.
4,360 citations
"Induction of hepatitis A virus-neut..." refers background in this paper
...(7) showed no predicted structural simi-...
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...(7) or comparable potentials described by Chou and Fasman (2)....
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...(7), the predicted alpha helical potentials of poliovirus VP1 (1 to 302) and HAV VP1 (5 to 306) aligned poorly, with the alignment having a correlation coefficient (r) of -0....
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TL;DR: The method was developed using 12 proteins for which extensive immunochemical analysis has been carried out and subsequently was used to predict antigenic determinants for the following proteins, finding that the prediction success rate depended on averaging group length.
Abstract: A method is presented for locating protein antigenic determinants by analyzing amino acid sequences in order to find the point of greatest local hydrophilicity. This is accomplished by assigning each amino acid a numerical value (hydrophilicity value) and then repetitively averaging these values along the peptide chain. The point of highest local average hydrophilicity is invariably located in, or immediately adjacent to, an antigenic determinant. It was found that the prediction success rate depended on averaging group length, with hexapeptide averages yielding optimal results. The method was developed using 12 proteins for which extensive immunochemical analysis has been carried out and subsequently was used to predict antigenic determinants for the following proteins: hepatitis B surface antigen, influenza hemagglutinins, fowl plague virus hemagglutinin, human histocompatibility antigen HLA-B7, human interferons, Escherichia coli and cholera enterotoxins, ragweed allergens Ra3 and Ra5, and streptococcal M protein. The hepatitis B surface antigen sequence was synthesized by chemical means and was shown to have antigenic activity by radioimmunoassay.
3,767 citations
"Induction of hepatitis A virus-neut..." refers result in this paper
...Comparisons of surface profiles of poliovirus and HAV VP1 generated by the amino acid hydrophilicity-based method of Hopp and Woods (9) give results similar to those obtained with the surface probability method, though visually not as striking and with a significantly lower correlation coefficient....
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TL;DR: This work has shown that effective methods of peptide synthesis are crucial to progress in this area, because only by synthesis can adequate amounts of important peptides be made available for chemical, biologi...
Abstract: The last two decades have been an era of rapid progress in peptide research. This era was begun by the work of Sanger on the amino acid sequence determination of insulin and by du Vigneaud on the structure determination and synthesis of oxytocin. This period has seen impressive progress in the structure elucidation and synthesis of many peptides of natural origin and of great biological significance, as well as in methods for sequence determination and chemical synthesis of peptides [1–4]. Perfection of techniques and instruments for automatic determination of the amino acid sequence of peptides and proteins has made possible a greatly broadened understanding of genetics and evolution as well as the more chemical areas of mechanism of action of enzymes and hormones, and physical chemistry of peptides and proteins. Effective methods of peptide synthesis are crucial to progress in this area, because only by synthesis can adequate amounts of important peptides be made available for chemical, biologi...
3,519 citations
2,751 citations