Peptide based vaccine design: synthesis and immunological characterization of branched polypeptide conjugates comprising the 276-284 immunodominant epitope of HSV-1 glycoprotein D.

The importance of the length and conjugation site of a protective epitope peptide (276SALLEDPVG284) from glycoprotein D of herpes simplex virus in branched polypeptide conjugates has been investigated. A new set of peptides, with a single attachment site and truncated sequences, was prepared. The immunogenicity of conjugates and the specificity of antibody responses elicited were investigated in BALB/c, C57/B1/6 and CBA mice. It was found that the covalent coupling of the peptide comprising the 276-284 sequence of gD through its Asp residue at position 281 did not influence the immunogenic properties of the epitope, while involvement of the side chain of Glu at position 280 almost completely abolished immunogenicity. These results clearly indicated that the conjugation site of the epitope peptide influenced the intensity and specificity of antibody responses. Comparison of the immunological properties of conjugates containing truncated gD peptides revealed the presence of two epitopes within the 276-284 region. One of the proposed epitopes is situated at the N-terminal (276-281) region, while the other is located at the C-terminal end of the sequence (279-284). Binding data demonstrated that some of the peptides comprising these epitopes induced gD-specific responses in their conjugated form and also elicited an immune response that conferred protection against lethal HSV-1 infection. The correlation of peptide- and gD-specific antibody responses with the protective effect of the immune response is discussed.     

Exploring antibody recognition of sequence space through random-sequence peptide microarrays

A universal platform for efficiently mapping antibody epitopes would be of great use for many applications, ranging from antibody therapeutic development to vaccine design. Here we tested the feasibility of using a random peptide microarray to map antibody epitopes. Although peptide microarrays are physically constrained to ～10(4) peptides per array, compared with 10(8) permitted in library panning approaches such as phage display, they enable a much more high though put and direct measure of binding. Long (20 mer) random sequence peptides were chosen for this study to look at an unbiased sampling of sequence space. This sampling of sequence space is sparse, as an exact epitope sequence is unlikely to appear. Commercial monoclonal antibodies with known linear epitopes or polyclonal antibodies raised against engineered 20-mer peptides were used to evaluate this array as an epitope mapping platform. Remarkably, peptides with the most sequence similarity to known epitopes were only slightly more likely to be recognized by the antibody than other random peptides. We explored the ability of two methods singly and in combination to predict the actual epitope from the random sequence peptides bound. Though the epitopes were not directly evident, subtle motifs were found among the top binding peptides for each antibody. These motifs did have some predictive ability in searching for the known epitopes among a set of decoy sequences. The second approach using a windowing alignment strategy, was able to score known epitopes of monoclonal antibodies well within the test dataset, but did not perform as well on polyclonals. Random peptide microarrays of even limited diversity may serve as a useful tool to prioritize candidates for epitope mapping or antigen identification.     

Stepwise prediction of conformational discontinuous B-cell epitopes using the Mapitope algorithm

Mapping the epitope of an antibody is of great interest, since it contributes much to our understanding of the mechanisms of molecular recognition and provides the basis for rational vaccine design. Here we present Mapitope, a computer algorithm for epitope mapping. The algorithm input is a set of affinity isolated peptides obtained by screening phage display peptide-libraries with the antibody of interest. The output is usually 1-3 epitope candidates on the surface of the atomic structure of the antigen. We have systematically tested the performance of Mapitope by assessing the effect of the algorithm parameters on the final prediction. Thus, we have examined the effect of the statistical threshold (ST) parameter, relating to the frequency distribution and enrichment of amino acid pairs from the isolated peptides and the D (distance) and E (exposure) parameters which relate to the physical parameters of the antigen. Two model systems were analyzed in which the antibody of interest had previously been co-crystallized with the antigen and thus the epitope is a given. The Mapitope algorithm successfully predicted the epitopes in both models. Accordingly, we formulated a stepwise paradigm for the prediction of discontinuous conformational epitopes using peptides obtained from screening phage display libraries. We applied this paradigm to successfully predict the epitope of the Trastuzumab antibody on the surface of the Her-2/neu receptor in a third model system.     

Identification of a Human Cyclin D1-Derived Peptide that Induces Human Cytotoxic CD4 T Cells

Cyclin D1 is over-expressed in various human tumors and therefore can be a potential oncogenic target antigen. However, only a limited number of T cell epitopes has been characterized. We aimed at identifying human cyclin D1-derived peptides that include both CD4 and CD8 T cell epitopes and to test if such multi-epitope peptides could yield improved cytotoxic CD8 T cell responses as well as cytotoxic CD4 T cells. Five HLA-DR.B1-binding peptides containing multiple overlapping CD4 epitopes and HLA-A0201-restricted CD8 T cell epitopes were predicted by computer algorithms. Immunogenicity of the synthetic peptides was assessed by stimulating T cells from healthy donors in vitro and the epitope recognition was measured by IFN-γ ELISPOT and ⁵¹Chromium release assays. A HLA-DR.B1 peptide, designed “DR-1”, in which a HLA-A0201-binding epitopes (D1-1) was imbedded, induced CD3 T cell responses against both DR-1 and D1-1 peptides in IFN-γ ELISPOT assay. This suggested processing of the shorter D1-1 epitope from the DR-1 sequence. However, only DR-1-stimulated CD4 or CD3 T cells possessed cytotoxicity against peptide-pulsed autologous DCs and a cancer cell line, that expresses a high level of cyclin D1. Monoclonal antibody to HLA-DR abrogated the epitope-specific responses of both CD3 and CD4 T cells, demonstrating class II-mediated killing. Our studies suggest a possible role of CD4 T cells in anti-tumor immunity as cytotoxic effectors against HLA-DR expressing cancers and provide a rationale for designing peptide vaccines that include CD4 epitopes.     

SVMTriP: A Method to Predict Antigenic Epitopes Using Support Vector Machine to Integrate Tri-Peptide Similarity and Propensity

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.     

Development of monoclonal antibodies against different protein and carbohydrate epitopes of dipeptidyl peptidase IV from rat liver plasma membranes.

Dipeptidyl peptidase IV (DPP IV) is a serine exopeptidase expressed at high levels in rat kidney, liver and lung. We established eight monoclonal antibodies against partially purified DPP IV from rat liver plasma membranes. By means of a competitive dot blot assay with purified DPP IV, these antibodies were shown to recognize four different epitopes of the glycoprotein, designated A - D. The epitopes are located on the extracellular domain of DPP IV, as shown by papain digestion of liver plasma membranes. Treatment of DPP IV with neuraminidase and glycopeptide N-glycosidase F, as well as incubation of hepatocytes with the alpha-mannosidase I inhibitor deoxymannojirimycin, revealed that epitope A may be formed by a mannose-rich sugar chain and epitope D might represent a complex carbohydrate structure in the mature glycoprotein, while the epitopes B and C are formed by the protein moiety. Concanavalin A reduced the binding of monoclonal antibody to epitope A by 78%. Binding to epitope D was blocked by 73% with wheat germ lectin, and by more than 99% with sialic acid; epitopes B and C were unaffected by any of the lectins or sugars tested. The immunological cross-reactivity with DPP IV from Morris hepatoma 7777 was demonstrated with monoclonal antibodies against epitopes A-C. Epitope D was not recognized on hepatoma DPP IV. However, in addition to DPP IV, four hepatoma plasma membrane glycoproteins were precipitated by the monoclonal antibody against the epitope D, indicating that this epitope is not uniquely restricted to DPP IV.     

Applying bioinformatics for antibody epitope prediction using affinity-selected mimotopes – relevance for vaccine design

To properly characterize protective polyclonal antibody responses, it is necessary to examine epitope specificity. Most antibody epitopes are conformational in nature and, thus, cannot be identified using synthetic linear peptides. Cyclic peptides can function as mimetics of conformational epitopes (termed mimotopes), thereby providing targets, which can be selected by immunoaffinity purification. However, the management of large collections of random cyclic peptides is cumbersome. Filamentous bacteriophage provides a useful scaffold for the expression of random peptides (termed phage display) facilitating both the production and manipulation of complex peptide libraries. Immunoaffinity selection of phage displaying random cyclic peptides is an effective strategy for isolating mimotopes with specificity for a given antiserum. Further epitope prediction based on mimotope sequence is not trivial since mimotopes generally display only small homologies with the target protein. Large numbers of unique mimotopes are required to provide sufficient sequence coverage to elucidate the target epitope. We have developed a method based on pattern recognition theory to deal with the complexity of large collections of conformational mimotopes. The analysis consists of two phases: 1) The learning phase where a large collection of epitope-specific mimotopes is analyzed to identify epitope specific "signs" and 2) The identification phase where immunoaffinity-selected mimotopes are interrogated for the presence of the epitope specific "signs" and assigned to specific epitopes. We are currently using computational methods to define epitope "signs" without the need for prior knowledge of specific mimotopes. This technology provides an important tool for characterizing the breadth of antibody specificities within polyclonal antisera.     

Estimation and extraction of B-cell linear epitopes predicted by mathematical morphology approaches

B-cell epitope prediction facilitates the design and synthesis of short peptides for various immunological applications. Several algorithms have been developed to predict B-cell linear epitopes (LEs) from primary sequences of antigens, providing important information for immunobiological experiments and antibody design. This paper describes two robust methods, LE prediction with/without local peak extraction (LEP-LP and LEP-NLP), based on antigenicity scale and mathematical morphology for the prediction of B-cell LEs. Previous studies revealed that LEs could occur in regions with low-to-moderate but not globally high antigenicity scales. Hence, we developed a method adopting mathematical morphology to extract local peaks from a linear combination of the propensity scales of physico-chemical characteristics at each antigen residue. Comparison among LEP-LP/LEP-NLP, BepiPred and BEPITOPE revealed that our algorithms performed better in retrieving epitopes with low-to-moderate antigenicity and achieved comparable performance according to receiver operation characteristics (ROC) curve analysis. Of the identified LEs, over 30% were unable to be predicted by BepiPred and BEPITOPE employing an average threshold of antigenicity index or default settings. Our LEP-LP method provides a bioinformatics approach for predicting B-cell LEs with low- to-moderate antigenicity. The web-based server was established at http://biotools.cs.ntou.edu.tw/lepd_antigenicity. php for free use.     

Synthesis and characterization of a recombinant myohemerythrin protein encoded by a synthetic gene.

The antigenic epitopes of the myohemerythrin (MHr) molecule have been studied extensively. The critical amino acid residues responsible for its immune recognition have been identified by using synthetic peptides and the technique of epitope scanning. To assess the true relevance of these techniques for determining the molecular mechanism of antigenic recognition and immunogenicity, the results obtained with isolated peptides should be tested in the context of the folded protein. To this end, we have designed and constructed a synthetic MHr gene, in modular form, which will allow subsequent alterations of nucleotide sequence encoding epitopes of interest. We have produced the recombinant protein at high level, and have shown by several criteria that it possesses the chemical, physical and immunological properties of the native worm protein. Thus, we have developed a valuable system for detailed immunological studies of the structure and chemistry required for antibody binding to protein.     

Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools

A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools.     

乳房链球菌GapC蛋白的表达及其B细胞抗原表位的预测与鉴定

乳房链球菌Streptococcus uberis的GapC蛋白是一种位于该菌表面的具有甘油醛-3-磷酸脱氢酶活性的蛋白,其参与细胞活动,表现出多种生物学活性,此外还具有良好的抗原性。文中旨在对乳房链球菌GapC蛋白可能的B细胞抗原表位进行预测,分析和验证候选表位肽的免疫原性。利用S. uberis分离株RF5-1克隆gapC基因,构建重组表达质粒pET-28a-GapC,诱导表达GapC重组蛋白,并以纯化蛋白免疫家兔,获得抗GapC多抗。利用生物信息学软件预测并分析GapCB细胞抗原表位的三维结构和空间位置及对GapC蛋白及表位的同源性比较。结果表明,表达纯化了44kDa的GapC蛋白具有良好的反应性。利用表位预测软件筛选并合成针对S.uberisGapC蛋白的6个线性和3个构象优势B细胞表位多肽,三维结构的分析显示,筛选的多肽具有良好的抗原表位形成条件。以纯化的S.uberis GapC蛋白免疫家兔制备多抗,通过间接ELISA对抗原表位进行鉴定。ELISA检测结果显示,9条抗原表位肽均可不同程度地与抗GapC多抗反应,其中表位266AANDSYGYTEDPIVSSD282与多抗反应...     

Sequence and Structure Based Binding Prediction Study of HLA Class I and cTAP Binding Peptides for Japanese Encephalitis Vaccine Development

Japanese encephalitis is a major threat in developing countries, even the availability of several conventional vaccines, which demand development of more effective vaccines. The present study used propred I and Immune Epitope Database Artificial Neural Network (ANN) algorithm (IEDB-ANN) to identify the conserve and promiscuous T cell epitopes from JEV proteome followed by structure based analysis of potential epitopes. Among all identified 102 epitopes, ten epitope were promiscuous but two epitopes of glycoprotein viz. ⁵⁵LVTVNPFVA⁶³ and ³⁸IPIVSVASL⁴⁶ were found most promiscuous, highly conserved and high population coverage in comparison of known antigenic positive control peptides. The B cell epitopes of glycoprotein also share these two T cell epitopes revealed by BCPred algorithm which can be a basis to confer the protection by neutralizing antibody combined with an effective cell-mediated response. Further, Autodock 4.2 and NAMD–VMD molecular dynamics simulation were used for docking and molecular dynamics simulation respectively, to validate epitope and allele complex binding stability. The 3D structure models were generated for epitopes and corresponding HLA allele by Pepstr and Modeller 9.10 respectively. Epitope LVTVNPFVA–B5101 allele complex showed best energy minimization and stability over the time window during simulation. Here we also present the binding sequel of epitope LVTVNPFVA and its eventual transport through cTAP1 (PDB ID: 1JJ7) revealed by Autodock 4.2, which is an essential path for HLA class I binding epitopes to elicit immune response. The docking experiment of epitope LVTVNPFVA and cTAP1 very well show a 2 H-bond with a binding energy of ?1.88 kcal/mol and other binding state of epitope forming no H-bond with a binding energy of ?1.13 kcal/mol in the lower area of cTAP1 cavity. These results show a smooth pass through of the epitope across the channel of cTAP1. Overall, identified peptides have potential application in the design and development of short peptide based vaccines and diagnostic agents for Japanese encephalitis.     

MHCPred 2.0

The accurate computational prediction of T-cell epitopes can greatly reduce the experimental overhead implicit in candidate epitope identification within genomic sequences. In this article we present MHCPred 2.0, an enhanced version of our online, quantitative T-cell epitope prediction server. The previous version of MHCPred included mostly alleles from the human leukocyte antigen A (HLA-A) locus. In MHCPred 2.0, mouse models are added and computational constraints removed. Currently the server includes 11 human HLA class I, three human HLA class II, and three mouse class I models. Additionally, a binding model for the human transporter associated with antigen processing (TAP) is incorporated into the new MHCPred. A tool for the design of heteroclitic peptides is also included within the server. To refine the veracity of binding affinities prediction, a confidence percentage is also now calculated for each peptide predicted. AVAILABILITY: As previously, MHCPred 2.0 is freely available at the URL http://www.jenner.ac.uk/MHCPred/ CONTACT: Darren R. Flower (darren.flower@jenner.ac.uk).     

B细胞表位作图研究进展

抗原-抗体的特异性结合是由抗体表面的抗原决定簇与抗原表面的表位基序间的特异性互补识别决定的。B细胞表位作图既包括B细胞抗原表位基序的鉴定(即确定抗原分子上被B细胞表面受体或抗体特异性识别并结合的氨基酸基序),也包括绘制抗原蛋白的全部或接近全部的B细胞表位基序在其一级或高级结构上的分布图谱的过程。B细胞表位作图是研发表位疫苗、治疗性表位抗体药物和建立疾病免疫诊断方法的重要前提。目前,已经建立了多种B细胞表位鉴定或绘制抗原蛋白B细胞表位图谱的实验方法。基于抗原-单抗复合物晶体结构的X-射线晶体学分析的B细胞表位作图和基于抗原蛋白或抗原片段的突变体库筛选技术的B细胞表位作图可以在氨基酸水平,甚至原子水平上揭示抗原分子上与单抗特异性结合的关键基序;其它B细胞表位作图方法(如基于ELISA的肽库筛选技术)常常只能获得包含B细胞表位的抗原性肽段,因而,很少用于最小表位基序的鉴定;而改良的生物合成肽法多用于B细胞表位的最小基序鉴定和精细作图。鉴于每种B细胞作图方法都存在各自的优势与不足,B细胞表位作图往往需要多种作图方法的有机结合。本文对目前常用的B细胞表位作图的实验方法及其在动物疫病防控中的应用进行综述,以期为研究者设计最佳的表位作图方案提供参考。     

A new method for mapping discontinuous antibody epitopes to reveal structural features of proteins.

Antibodies that bind to protein surfaces of interest can be used to report the three-dimensional structure of the protein as follows: Proteins are composed of linear polypeptide chains that fold together in complex spatial patterns to create the native protein structure. These folded structures form binding sites for antibodies. Antibody binding sites are typically "assembled" on the protein surface from segments that are far apart in the primary amino acid sequence of the target proteins. Short amino acid probe sequences that bind to the active region of each antibody can be used as witnesses to the antibody epitope surface and these probes can be efficiently selected from random sequence peptide libraries. This paper presents a new method to align these antibody epitopes to discontinuous regions of the one-dimensional amino acid sequence of a target protein. Such alignments of the epitopes indicate how segments of the protein sequence must be folded together in space and thus provide long-range constraints for solving the 3-D protein structure. This new antibody-based approach is applicable to the large fraction of proteins that are refractory to current approaches for structure determination and has the additional advantage of requiring very small amounts of the target protein. The binding site of an antibody is a surface, not just a continuous linear sequence, so the epitope mapping alignment problem is outside the scope of classical string alignment algorithms, such as Smith-Waterman. We formalize the alignment problem that is at the heart of this new approach, prove that the epitope mapping alignment problem is NP-complete, and give some initial results using a branch-and-bound algorithm to map two real-life cases. Initial results for two validation cases are presented for a graph-based protein surface neighbor mapping procedure that promises to provide additional spatial proximity information for the amino acid residues on the protein surface.     

Localization of epitopes of herpes simplex virus type 1 glycoprotein D.

We previously defined eight groups of monoclonal antibodies which react with distinct epitopes of herpes simplex virus glycoprotein D (gD). One of these, group VII antibody, was shown to react with a type-common continuous epitope within residues 11 to 19 of the mature glycoprotein (residues 36 to 44 of the predicted sequence of gD). In the current investigation, we have localized the sites of binding of two additional antibody groups which recognize continuous epitopes of gD. The use of truncated forms of gD as well as computer predictions of secondary structure and hydrophilicity were instrumental in locating these epitopes and choosing synthetic peptides to mimic their reactivity. Group II antibodies, which are type common, react with an epitope within residues 268 to 287 of the mature glycoprotein (residues 293 to 312 of the predicted sequence). Group V antibodies, which are gD-1 specific, react with an epitope within residues 340 to 356 of the mature protein (residues 365 to 381 of the predicted sequence). Four additional groups of monoclonal antibodies appear to react with discontinuous epitopes of gD-1, since the reactivity of these antibodies was lost when the glycoprotein was denatured by reduction and alkylation. Truncated forms of gD were used to localize these four epitopes to the first 260 amino acids of the mature protein. Competition experiments were used to assess the relative positions of binding of various pairs of monoclonal antibodies. In several cases, when one antibody was bound, there was no interference with the binding of an antibody from another group, indicating that the epitopes were distinct. However, in other cases, there was competition, indicating that these epitopes might share some common amino acids.     

Epitope-Based Peptides Prediction from Proteome of Nipah Virus

The identification of MHC class II epitope-based peptides are urgently needed for appropriate vaccination against Nipah virus (NiV) because there are currently no approved vaccines for human NiV infection. In the present study, prediction and modeling of T cell epitopes of NiV antigenic proteins nucleocapsid, phosphoprotein, matrix, fusion, glycoprotein, L protein, W protein, V protein and C protein followed by the binding simulation studies of predicted highest binding scores with their corresponding MHC class II alleles were done. Immunoinformatic tool ProPred was used to predict the promiscuous MHC class II epitopes of viral antigenic proteins. PEPstr server did the 3D structure models of the epitopes and Modeller 9.10 did alleles. We docked epitope with allele structure using the AutoDock 4.2 Tool. The docked peptide–allele complex structure was optimized using molecular dynamics simulation for 5 ps with the CHARMM-22 force field using NAnoscale Molecular Dynamics program incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating the stability of complex structure by calculating RMSD values. Epitope MKLQFSLGS of Matrix protein has considerable binding energy and score with DRBI*0421 MHC class II allele. This predicted peptide has potential to induce T cell-mediated immune response and is expected to useful in designing epitope-based vaccines against NiV after further testing by wet lab studies.     

Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates: E coli 536

Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 < 50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.     

Epitope-Analyzer: A structure-based webtool to analyze broadly neutralizing epitopes

The antigenic epitope regions of pathogens (e.g., viruses) are recognized by antibodies (Abs) and subsequently cleared by the host immune system, thereby protecting us from disease. Some of these epitopes are conserved among different variants or subgroups of pathogens (e.g., Influenza (FLU) viruses, Coronaviruses), hence can be targeted for potential broad-neutralization. Here we report a web-based tool, Epitope Analyzer (EA), that rapidly identifies conformational epitope and paratope residues in an antigen–antibody complex structure. Furthermore, the tool provides the ways and means to analyze broadly neutralizing epitopes by comparing the equivalent epitope residues in similar antigen structures. The similarity in the epitope residues between (multiple) pairs of similar antigen molecules suggest the presence of conserved epitopes that can be targeted by broadly neutralizing antibodies. These details can be used as a guide in developing effective treatments, such as the design of novel vaccines and formulation of cocktail of broadly neutralizing antibodies, against multiple variants or subgroups of viruses. The web application can be freely accessed from the URL, http://viperdb.scripps.edu/ea.php.     

Exact definition of species-specific and cross-reactive epitopes of the 65-kilodalton protein of Mycobacterium leprae using synthetic peptides

With the use of solid phase synthesis of peptides corresponding to major and minor peaks in a Hopp-Woods hydrophilicity plot, the epitopes for 10 of 14 known different mAb to the Mycobacterium leprae 65-kDa protein, a prominent T and B cell Ag of this bacillus, have been located in the primary structure. Five epitopes have been precisely mapped by using the synthetic peptides in inhibition ELISA experiments, and five others have been located on peptides of 22 amino acids or less in length. The epitope of an important species-specific antibody, IIIE9, which may be useful for seriodiagnosis of leprosy, appears to be distinguished from the epitope of the antibody IVD2, widely cross-reactive among mycobacteria, not by its sequence, but only by its critical residues. All epitopes studied appear continuous insofar as can be determined by this approach.