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Prediction of antigenic epitopes on protein surfaces by consensus scoring
Shide Liang, Dandan Zheng, Chi Zhang, Martin Zacharias
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-302
Abstract: We present a new antigen Epitope Prediction method, which uses ConsEnsus Scoring (EPCES) from six different scoring functions - residue epitope propensity, conservation score, side-chain energy score, contact number, surface planarity score, and secondary structure composition. Applied to unbounded antigen structures from an independent test set, EPCES was able to predict antigenic eptitopes with 47.8% sensitivity, 69.5% specificity and an AUC value of 0.632. The performance of the method is statistically similar to other published methods. The AUC value of EPCES is slightly higher compared to the best results of existing algorithms by about 0.034.Our work shows consensus scoring of multiple features has a better performance than any single term. The successful prediction is also due to the new score of residue epitope propensity based on atomic solvent accessibility.Realistic prediction of protein surface regions that are preferentially recognized by antibodies (antigenic epitopes) can help in the design of vaccine components and immuno-diagnostic reagents. Antigenic epitopes are classified as continuous or discontinues epitopes. If the residues involved in an epitope are contiguous in the polypeptide chain, this epitope is called a continuous epitope or a linear epitope. On the other hand, a discontinuous or non-linear epitope is composed of residues that are not necessarily continuous in the polypeptide sequence but have spatial proximity on the surface of a protein structure. A significant fraction of epitopes are discontinuous in the sense that antibody binding is not fully determined by a linear peptide segment but also influenced by adjacent surface regions [1].However, the majority of available epitope prediction methods focus on continuous epitopes due to the convenience of the investigation in which the amino acid sequence of a protein is taken as the input. Such prediction methods are based upon the amino acid properties including hydrophilicity [2,3], so
Large-scale analysis of antigenic diversity of T-cell epitopes in dengue virus  [cached]
Khan Asif M,Heiny AT,Lee Kenneth X,Srinivasan KN
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-s5-s4
Abstract: Background Antigenic diversity in dengue virus strains has been studied, but large-scale and detailed systematic analyses have not been reported. In this study, we report a bioinformatics method for analyzing viral antigenic diversity in the context of T-cell mediated immune responses. We applied this method to study the relationship between short-peptide antigenic diversity and protein sequence diversity of dengue virus. We also studied the effects of sequence determinants on viral antigenic diversity. Short peptides, principally 9-mers were studied because they represent the predominant length of binding cores of T-cell epitopes, which are important for formulation of vaccines. Results Our analysis showed that the number of unique protein sequences required to represent complete antigenic diversity of short peptides in dengue virus is significantly smaller than that required to represent complete protein sequence diversity. Short-peptide antigenic diversity shows an asymptotic relationship to the number of unique protein sequences, indicating that for large sequence sets (~200) the addition of new protein sequences has marginal effect to increasing antigenic diversity. A near-linear relationship was observed between the extent of antigenic diversity and the length of protein sequences, suggesting that, for the practical purpose of vaccine development, antigenic diversity of short peptides from dengue virus can be represented by short regions of sequences (~<100 aa) within viral antigens that are specific targets of immune responses (such as T-cell epitopes specific to particular human leukocyte antigen alleles). Conclusion This study provides evidence that there are limited numbers of antigenic combinations in protein sequence variants of a viral species and that short regions of the viral protein are sufficient to capture antigenic diversity of T-cell epitopes. The approach described herein has direct application to the analysis of other viruses, in particular those that show high diversity and/or rapid evolution, such as influenza A virus and human immunodeficiency virus (HIV).
EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results
Shide Liang, Dandan Zheng, Daron M Standley, Bo Yao, Martin Zacharias, Chi Zhang
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-381
Abstract: In this work, we present two novel server applications for discontinuous epitope prediction: EPSVR and EPMeta, where EPMeta is a meta server. EPSVR, EPMeta, and datasets are available at http://sysbio.unl.edu/services webcite.The server application for discontinuous epitope prediction, EPSVR, uses a Support Vector Regression (SVR) method to integrate six scoring terms. Furthermore, we combined EPSVR with five existing epitope prediction servers to construct EPMeta. All methods were benchmarked by our curated independent test set, in which all antigens had no complex structures with the antibody, and their epitopes were identified by various biochemical experiments. The area under the receiver operating characteristic curve (AUC) of EPSVR was 0.597, higher than that of any other existing single server, and EPMeta had a better performance than any single server - with an AUC of 0.638, significantly higher than PEPITO and Disctope (p-value < 0.05).Antigenic epitopes are regions of protein surface that are preferentially recognized by antibodies. Prediction of antigenic epitopes can help during the design of vaccine components and immuno-diagnostic reagents, but predicting effective epitopes is still an open problem in bioinformatics. Usually, B-cell antigenic epitopes are classified as either continuous or discontinuous. The majority of available epitope prediction methods focus on continuous epitopes [1-12].Although discontinuous epitopes dominate most antigenic epitope families [13], due to their computational complexity, only a very limited number of prediction methods exist for discontinuous epitope prediction: CEP [14], DiscoTope [15], PEPITO [16], ElliPro [17], SEPPA [18], EPITOPIA[19,20] and our previous work, EPCES [21]. All discontinuous epitope prediction methods require the three-dimensional structure of the antigenic protein. The small number of available antigen-antibody complex structures limits the development of reliable discontinuous epitope prediction
Efficient induction of CD25- iTreg by co-immunization requires strongly antigenic epitopes for T cells
Shuang Geng, Yang Yu, Youmin Kang, George Pavlakis, Huali Jin, Jinyao Li, Yanxin Hu, Weibin Hu, Shuang Wang, Bin Wang
BMC Immunology , 2011, DOI: 10.1186/1471-2172-12-27
Abstract: In the present study, we demonstrated the requirement of highly antigenic epitopes for CD25- iTreg induction. Firstly, we showed that the induction of CD25- iTreg by tolerogenic DC can be blocked by anti-MHC-II antibody. Next, both the number and the suppressive activity of CD25- iTreg correlated positively with the overt antigenicity of an epitope to activate T cells. Finally, in a mouse model of dermatitis, highly antigenic epitopes derived from a flea allergen not only induced more CD25- iTreg, but also more effectively prevented allergenic reaction to the allergen than did weakly antigenic epitopes.Our data thus indicate that efficient induction of CD25- iTreg requires highly antigenic peptide epitopes. This finding suggests that highly antigenic epitopes should be used for efficient induction of CD25- iTreg for clinical applications such as flea allergic dermatitis.The inducible regulatory T cells, or iTreg, differ from the naturally regulatory T cells (nTreg) in that the former are generated in the periphery through encounter with environmental antigens. It is also believed that iTreg play non-overlapping roles, relative to nTreg, in regulating peripheral tolerance [1-3]. Most iTreg reported to date have been CD25+ cells (CD4+CD25+Foxp3+), and it is well established that their induction requires suboptimal stimulation of the T cell receptor (TCR) and cytokines TGF-β and IL-2 [3]. The CD25+ iTreg thus appear to derive primarily from weakly stimulated CD4+ T cells.We previously identified a different subset of iTreg in mice that is CD25- (CD4+CD25-Foxp3+ and IL-10+TGF-beta+IFN-γ-). The CD25- iTreg were induced after co-immunization using a protein antigen and a DNA vaccine encoding the same antigen [4-7]. Unlike that of the CD25+ iTreg, the induction of the CD25- iTreg involved the generation of CD40low IL-10high tolerogenic dendritic cells (DCs), which in turn stimulated CD25- iTreg in an antigen-specific manner [4]. We further showed in mouse models that this
SVMTriP: A Method to Predict Antigenic Epitopes Using Support Vector Machine to Integrate Tri-Peptide Similarity and Propensity  [PDF]
Bo Yao, Lin Zhang, Shide Liang, Chi Zhang
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0045152
Abstract: Identifying protein surface regions preferentially recognizable by antibodies (antigenic epitopes) is at the heart of new immuno-diagnostic reagent discovery and vaccine design, and computational methods for antigenic epitope prediction provide crucial means to serve this purpose. Many linear B-cell epitope prediction methods were developed, such as BepiPred, ABCPred, AAP, BCPred, BayesB, BEOracle/BROracle, and BEST, towards this goal. However, effective immunological research demands more robust performance of the prediction method than what the current algorithms could provide. In this work, a new method to predict linear antigenic epitopes is developed; Support Vector Machine has been utilized by combining the Tri-peptide similarity and Propensity scores (SVMTriP). Applied to non-redundant B-cell linear epitopes extracted from IEDB, SVMTriP achieves a sensitivity of 80.1% and a precision of 55.2% with a five-fold cross-validation. The AUC value is 0.702. The combination of similarity and propensity of tri-peptide subsequences can improve the prediction performance for linear B-cell epitopes. Moreover, SVMTriP is capable of recognizing viral peptides from a human protein sequence background. A web server based on our method is constructed for public use. The server and all datasets used in the current study are available at http://sysbio.unl.edu/SVMTriP.
Antigenic epitopes prediction and MHC binder of a paralytic insecticidal toxin (ITX-1) of Tegenaria agrestis (hobo spider)
AG Ingale
Open Access Bioinformatics , 2010, DOI: http://dx.doi.org/10.2147/OAB.S11886
Abstract: ntigenic epitopes prediction and MHC binder of a paralytic insecticidal toxin (ITX-1) of Tegenaria agrestis (hobo spider) Original Research (3794) Total Article Views Authors: AG Ingale Published Date August 2010 Volume 2010:2 Pages 97 - 103 DOI: http://dx.doi.org/10.2147/OAB.S11886 AG Ingale Department of Biotechnology, School of Life Sciences, North Maharashtra University, Jalgaon, India Abstract: Spider peptide toxins with nanomolar affinities for their receptors are promising pharmacological tools for understanding the physiological role of ion channels and as leads for the development of novel therapeutic agents and strategies for ion channel-related diseases. Paralytic insecticidal toxin (Tegenaria agrestis) involved multiple antigenic components to direct and empower the immune system to protect the host from infection. MHC molecules are cell surface proteins, which take active part in host immune reactions and involvement of MHC class in response to almost all antigens, and it affects specific sites. Predicted MHC binding regions act like red flags for specific antigens and generate an immune response against the parent antigen. So a small fragment of antigen can induce an immune response against whole antigen. This theme is implemented in designing subunit and synthetic peptide vaccines. In this study, we analyzed secondary structure and antigenic determinants, which form antibodies against infection. The method integrates prediction of peptide MHC class binding and solvent accessible regions. Antigenic epitopes of paralytic insecticidal toxin are important antigenic determinants against the various toxic reactions and infections. There are 3 antigenic determinants in sequence. The results show highest pick at position 4–25 (QLMICLVLLPCFFCEPDEICRA) amino acid residue and 34–51 (YKSNVCNGCGDQVAACEA) amino acid residue.
Homology building as a means to define antigenic epitopes on dihydrofolate reductase (DHFR) from Plasmodium falciparum
Michael Alifrangis, Inge T Christensen, Flemming S J?rgensen, Anita M R?nn, Jimmy E Weng, Ming Chen, Ib C Bygbjerg, Worachart Sirawaraporn, Yaseelan Palarasah, Claus Koch
Malaria Journal , 2004, DOI: 10.1186/1475-2875-3-16
Abstract: A homology model of Pf-DHFR domain was employed to define an epitope for the development of site-specific antibodies against Pf-DHFR. The homology model suggested an exposed loop encompassing amino acid residues 64–100. A synthetic peptide of 37-mers whose sequence corresponded to the sequence of amino acid residues 64–100 of Pf-DHFR was synthesized and used to immunize mice for antibodies. Additionally, polyclonal antibodies recognizing a recombinant DHFR enzyme were produced in rabbits.Serum from mice immunized with the 37-mer showed strong reactivity against both the immunizing peptide, recombinant DHFR and a preparation of crude antigen from P. falciparum infected red blood cells. Five monoclonal antibodies were obtained, one of which showed reactivity towards crude antigen prepared from P. falciparum infected red cells. Western blot analysis revealed that both the polyclonal and monoclonal antibodies recognized Pf-DHFR. Our study provides insight into the potential use of homology models in general and of Pf-DHFR in particular in predicting antigenic malarial surface epitopes.Antibodies raised against short peptide fragments of a given protein have been reported to be able to cross-react with the native protein [1]. The identification of peptide epitopes simulating the native protein has traditionally been based on amino acid sequences or sequence motifs exposed on the outer surface of the protein structure, thereby making these peptides potential candidates as antigen epitopes. Examples of algorithms for selecting and defining properties of exposed peptide sequences include plots of hydrophilicity, hydrophobicity, external flexibility and antigenic index. However, these algorithms provide only crude approximations of the native structures, and antibodies raised against the selected peptides are often lacking reactivity or show low degree of cross-reactivity with the native protein [2]. In recent years, the number of proteins for which three-dimensional structu
Overcoming Antigenic Diversity by Enhancing the Immunogenicity of Conserved Epitopes on the Malaria Vaccine Candidate Apical Membrane Antigen-1  [PDF]
Sheetij Dutta ,Lisa S. Dlugosz,Damien R. Drew,Xiopeng Ge,Diouf Ababacar,Yazmin I. Rovira,J. Kathleen Moch,Meng Shi,Carole A. Long,Michael Foley,James G. Beeson,Robin F. Anders,Kazutoyo Miura,J. David Haynes,Adrian H. Batchelor
PLOS Pathogens , 2013, DOI: 10.1371/journal.ppat.1003840
Abstract: Malaria vaccine candidate Apical Membrane Antigen-1 (AMA1) induces protection, but only against parasite strains that are closely related to the vaccine. Overcoming the AMA1 diversity problem will require an understanding of the structural basis of cross-strain invasion inhibition. A vaccine containing four diverse allelic proteins 3D7, FVO, HB3 and W2mef (AMA1 Quadvax or QV) elicited polyclonal rabbit antibodies that similarly inhibited the invasion of four vaccine and 22 non-vaccine strains of P. falciparum. Comparing polyclonal anti-QV with antibodies against a strain-specific, monovalent, 3D7 AMA1 vaccine revealed that QV induced higher levels of broadly inhibitory antibodies which were associated with increased conserved face and domain-3 responses and reduced domain-2 response. Inhibitory monoclonal antibodies (mAb) raised against the QV reacted with a novel cross-reactive epitope at the rim of the hydrophobic trough on domain-1; this epitope mapped to the conserved face of AMA1 and it encompassed the 1e-loop. MAbs binding to the 1e-loop region (1B10, 4E8 and 4E11) were ~10-fold more potent than previously characterized AMA1-inhibitory mAbs and a mode of action of these 1e-loop mAbs was the inhibition of AMA1 binding to its ligand RON2. Unlike the epitope of a previously characterized 3D7-specific mAb, 1F9, the 1e-loop inhibitory epitope was partially conserved across strains. Another novel mAb, 1E10, which bound to domain-3, was broadly inhibitory and it blocked the proteolytic processing of AMA1. By itself mAb 1E10 was weakly inhibitory but it synergized with a previously characterized, strain-transcending mAb, 4G2, which binds close to the hydrophobic trough on the conserved face and inhibits RON2 binding to AMA1. Novel inhibition susceptible regions and epitopes, identified here, can form the basis for improving the antigenic breadth and inhibitory response of AMA1 vaccines. Vaccination with a few diverse antigenic proteins could provide universal coverage by redirecting the immune response towards conserved epitopes.
Prediction of antigenic epitopes and MHC binders of neurotoxin alpha-KTx 3.8 from Mesobuthus tamulus sindicus
VS Gomase, K Shyamkumar
African Journal of Biotechnology , 2009,
Abstract: The potassium channel inhibitor alpha-KTx 3.8, a 38-residue peptide was isolated from the venom of Mesobuthus tamulus sindicus. In this assay we have predicted the binding affinity of alpha-KTx 3.8 having 38 amino acids, which shows 30 nonamers. Peptide fragments of the neurotoxin can be used to select nonamers for use in rational vaccine design and to increase the understanding of roles of the immune system in neurotoxin studies. Small segment ‘4-INVKCRGSPQCIQPCR-19’of neurotoxin protein called the antigenic epitopes is sufficient for eliciting the desired immune response. We also found the SVM based MHCII-IAb peptide regions, 26- GKCMNGKCH, 20- DAGMRFGKC, 1- GVPINVKCR, 19- RDAGMRFGK, (optimal score is 0.388); MHCII-IAd peptide regions, 20- DAGMRFGKC, 14- CIQPCRDAG, 10- GSPQCIQPC, 25- FGKCMNGKC, (optimal score is 0.386); MHCII-IAg7 peptide regions, 18- CRDAGMRFG, 17- PCRDAGMRF, 14- CIQPCRDAG, 3- PINVKCRGS, (optimal score is 1.341); and MHCIIRT1. B peptide regions, 16- QPCRDAGMR, 29- MNGKCHCTP, 8- CRGSPQCIQ, 7- KCRGSPQCI, (optimal score is -0.039) which represented predicted binders from neurotoxin protein. CTL epitope with their (ANN/SVM) scores were predicted to be 1- GVPINVKCR (0.81/0.87220559). This theme is implemented in designing subunit and synthetic peptide vaccines. We have predicted a successful immunization.
Antigenic Analysis of Monoclonal Antibodies against Different Epitopes of σB Protein of Avian Reovirus  [PDF]
Chun-hong Yin, Li-ting Qin, Mei-yu Sun, Yu-long Gao, Xiao-le Qi, Hong-lei Gao, Yong-qiang Wang, Xiao-mei Wang
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0081533
Abstract: Background Avian reovirus (ARV) causes arthritis, tenosynovitis, runting-stunting syndrome (RSS), malabsorption syndrome (MAS) and immunosuppression in chickens. σB is one of the major structural proteins of ARV, which is able to induce group-specific antibodies against the virus. Methods and Results The present study described the identification of two linear B-cell epitopes in ARV σB through expressing a set of partially overlapping and consecutive truncated peptides spanning σB screened with two monoclonal antibodies (mAbs) 1F4 and 1H3-1.The data indicated that 21KTPACW26 (epitope A) and 32WDTVTFH38 (epitope B) were minimal determinants of the linear B cell epitopes. Antibodies present in the serum of ARV-positive chickens recognized the minimal linear epitopes in Western blot analyses. By sequence alignment analysis, we determined that the epitopes A and B were not conserved among ARV, duck reovirus (DRV) and turkey reovirus (TRV) strains. Western blot assays, confirmed that epitopes A and B were ARV-specific epitopes, and they could not react with the corresponding peptides of DRV and TRV. Conclusions and Significance We identified 21KTPACW26 and 32WDTVTFH38 as σB -specific epitopes recognized by mAbs 1F4 and 1H3-1, respectively. The results in this study may have potential applications in development of diagnostic techniques and epitope-based marker vaccines against ARV groups.
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