{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T17:28:58Z","timestamp":1793035738392,"version":"4.5.0"},"update-to":[{"DOI":"10.1371\/journal.pntd.0012985","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T00:00:00Z","timestamp":1746748800000}}],"reference-count":74,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T00:00:00Z","timestamp":1745884800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62202083"],"award-info":[{"award-number":["62202083"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010031","name":"Postdoctoral Research Foundation of China","doi-asserted-by":"publisher","award":["2022M710618"],"award-info":[{"award-number":["2022M710618"]}],"id":[{"id":"10.13039\/501100010031","id-type":"DOI","asserted-by":"publisher"}]},{"name":"High-level Talent Research Start-up Project of Sichuan University of Arts and Science","award":["2024GCC16Z"],"award-info":[{"award-number":["2024GCC16Z"]}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Background<\/jats:title>\n<jats:p>The identification of B-cell epitopes (BCEs) is fundamental to advancing epitope-based vaccine design, therapeutic antibody development, and diagnostics, such as in neglected tropical diseases caused by parasitic pathogens. However, the structural complexity of parasite antigens and the high cost of experimental validation present certain challenges. Advances in Artificial Intelligence (AI)-driven protein engineering, particularly through machine learning and deep learning, offer efficient solutions to enhance prediction accuracy and reduce experimental costs.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methodology\/Principal findings<\/jats:title>\n<jats:p>Here, we present deepBCE-Parasite, a Transformer-based deep learning model designed to predict linear BCEs from peptide sequences. By leveraging a state-of-the-art self-attention mechanism, the model achieved remarkable predictive performance, achieving an accuracy of approximately 81% and an AUC of 0.90 in both 10-fold cross-validation and independent testing. Comparative analyses against 12 handcrafted features and four conventional machine learning algorithms (GNB, SVM, RF, and LGBM) highlighted the superior predictive power of the model. As a case study, deepBCE-Parasite predicted eight BCEs from the leucine aminopeptidase (LAP) protein in <jats:italic>Fasciola hepatica<\/jats:italic> proteomic data. Dot-blot immunoassays confirmed the specific binding of seven synthetic peptides to positive sera, validating their IgG reactivity and demonstrating the model\u2019s efficacy in BCE prediction.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Conclusions\/Significance<\/jats:title>\n<jats:p>deepBCE-Parasite demonstrates excellent performance in predicting BCEs across diverse parasitic pathogens, offering a valuable tool for advancing the design of epitope-based vaccines, antibodies, and diagnostic applications in parasitology.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pntd.0012985","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T18:14:14Z","timestamp":1745950454000},"page":"e0012985","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":10,"title":["Transformer-based deep learning enables improved B-cell epitope prediction in parasitic pathogens: A proof-of-concept study on Fasciola hepatica"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0587-0542","authenticated-orcid":true,"given":"Rui-Si","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kui","family":"Gu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Ehsan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sayed Haidar","family":"Abbas Raza","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun-Ren","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,4,29]]},"reference":[{"issue":"12","key":"pntd.0012985.ref001","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1001920","article-title":"World Health Organization estimates of the global and regional disease burden of 11 foodborne parasitic diseases, 2010: a data synthesis","volume":"12","author":"PR Torgerson","year":"2015","journal-title":"PLoS Med"},{"issue":"1","key":"pntd.0012985.ref002","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.pt.2018.10.006","article-title":"100 questions in livestock helminthology research","volume":"35","author":"ER Morgan","year":"2019","journal-title":"Trends Parasitol"},{"issue":"9","key":"pntd.0012985.ref003","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1111\/pim.12343","article-title":"A prospective view of animal and human Fasciolosis","volume":"38","author":"K Cwiklinski","year":"2016","journal-title":"Parasite Immunol"},{"issue":"3","key":"pntd.0012985.ref004","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1079\/JOH2005296","article-title":"Epidemiology of fascioliasis in human endemic areas","volume":"79","author":"S Mas-Coma","year":"2005","journal-title":"J Helminthol"},{"key":"pntd.0012985.ref005","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.ijpddr.2019.05.001","article-title":"Refugia and anthelmintic resistance: Concepts and challenges","volume":"10","author":"JE Hodgkinson","year":"2019","journal-title":"Int J Parasitol Drugs Drug Resist"},{"key":"pntd.0012985.ref006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jgar.2019.01.023","article-title":"Drug resistance in protozoan parasites: an incessant wrestle for survival","volume":"18","author":"PK Pramanik","year":"2019","journal-title":"J Glob Antimicrob Resist"},{"key":"pntd.0012985.ref007","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0065-2776(08)60363-6","article-title":"The chemistry and mechanism of antibody binding to protein antigens","volume":"43","author":"ED Getzoff","year":"1988","journal-title":"Adv Immunol"},{"key":"pntd.0012985.ref008","doi-asserted-by":"crossref","first-page":"6760830","DOI":"10.1155\/2016\/6760830","article-title":"An Introduction to B-cell epitope mapping and in silico epitope prediction","volume":"2016","author":"L Potocnakova","year":"2016","journal-title":"J Immunol Res"},{"key":"pntd.0012985.ref009","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-1-59745-450-6_1","article-title":"What is a B-cell epitope?","volume":"524","author":"MHV Van Regenmortel","year":"2009","journal-title":"Methods Mol Biol"},{"key":"pntd.0012985.ref010","doi-asserted-by":"crossref","first-page":"59","DOI":"10.3389\/fcimb.2016.00059","article-title":"Toxoplasma gondii-derived synthetic peptides containing B- and T-cell epitopes from GRA2 protein are able to enhance mice survival in a model of experimental toxoplasmosis","volume":"6","author":"LM Bastos","year":"2016","journal-title":"Front Cell Infect Microbiol"},{"issue":"1","key":"pntd.0012985.ref011","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1186\/s13071-020-04260-6","article-title":"Identification of protective peptides of Fasciola hepatica-derived cathepsin L1 (FhCL1) in vaccinated sheep by a linear B-cell epitope mapping approach","volume":"13","author":"L Buffoni","year":"2020","journal-title":"Parasit Vectors"},{"issue":"7","key":"pntd.0012985.ref012","doi-asserted-by":"crossref","first-page":"958","DOI":"10.1016\/j.vaccine.2018.01.020","article-title":"Antibody recognition of cathepsin L1-derived peptides in Fasciola hepatica-infected and\/or vaccinated cattle and identification of protective linear B-cell epitopes","volume":"36","author":"L Garza-Cuartero","year":"2018","journal-title":"Vaccine"},{"issue":"7","key":"pntd.0012985.ref013","article-title":"Identification of a linear B-cell epitope on the Schistosoma japonicum saposin protein, SjSAP4: Potential as a component of a multi-epitope diagnostic assay","volume":"16","author":"Y Mu","year":"2022","journal-title":"PLoS Negl Trop Dis"},{"key":"pntd.0012985.ref014","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/1745-7580-6-6","article-title":"Identification of conformational B-cell epitopes in an antigen from its primary sequence","volume":"6","author":"HR Ansari","year":"2010","journal-title":"Immunome Res"},{"issue":"1","key":"pntd.0012985.ref015","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbab423","article-title":"epitope3D: a machine learning method for conformational B-cell epitope prediction","volume":"23","author":"BM da Silva","year":"2022","journal-title":"Brief Bioinform"},{"key":"pntd.0012985.ref016","doi-asserted-by":"crossref","first-page":"1322712","DOI":"10.3389\/fimmu.2024.1322712","article-title":"DiscoTope-3.0: improved B-cell epitope prediction using inverse folding latent representations","volume":"15","author":"MH H\u00f8ie","year":"2024","journal-title":"Front Immunol"},{"key":"pntd.0012985.ref017","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkae386","article-title":"SEMA 2.0: web-platform for B-cell conformational epitopes prediction using artificial intelligence","volume":"52","author":"NV Ivanisenko","year":"2024","journal-title":"Nucleic Acids Res"},{"key":"pntd.0012985.ref018","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1186\/1471-2105-11-381","article-title":"EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results","volume":"11","author":"S Liang","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"pntd.0012985.ref019","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1186\/1471-2105-9-514","article-title":"ElliPro: a new structure-based tool for the prediction of antibody epitopes","volume":"9","author":"J Ponomarenko","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"pntd.0012985.ref020","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkz413","article-title":"SEPPA 3.0-enhanced spatial epitope prediction enabling glycoprotein antigens","volume":"47","author":"C Zhou","year":"2019","journal-title":"Nucleic Acids Res"},{"issue":"3","key":"pntd.0012985.ref021","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac035","article-title":"LBCEPred: a machine learning model to predict linear B-cell epitopes","volume":"23","author":"W Alghamdi","year":"2022","journal-title":"Brief Bioinform"},{"issue":"12","key":"pntd.0012985.ref022","doi-asserted-by":"crossref","DOI":"10.1002\/pro.4497","article-title":"BepiPred-3.0: Improved B-cell epitope prediction using protein language models","volume":"31","author":"JN Clifford","year":"2022","journal-title":"Protein Sci"},{"issue":"4","key":"pntd.0012985.ref023","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1093\/bioinformatics\/btaa773","article-title":"EpiDope: a deep neural network for linear B-cell epitope prediction","volume":"37","author":"M Collatz","year":"2021","journal-title":"Bioinformatics"},{"key":"pntd.0012985.ref024","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.3389\/fimmu.2018.01695","article-title":"iBCE-EL: a new ensemble learning framework for improved linear B-cell epitope prediction","volume":"9","author":"B Manavalan","year":"2018","journal-title":"Front Immunol"},{"key":"pntd.0012985.ref025","doi-asserted-by":"crossref","first-page":"1117027","DOI":"10.3389\/fmicb.2023.1117027","article-title":"DeepLBCEPred: A Bi-LSTM and multi-scale CNN-based deep learning method for predicting linear B-cell epitopes","volume":"14","author":"Y Qi","year":"2023","journal-title":"Front Microbiol"},{"issue":"1","key":"pntd.0012985.ref026","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1002\/prot.21078","article-title":"Prediction of continuous B-cell epitopes in an antigen using recurrent neural network","volume":"65","author":"S Saha","year":"2006","journal-title":"Proteins"},{"issue":"9","key":"pntd.0012985.ref027","article-title":"SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity","volume":"7","author":"B Yao","year":"2012","journal-title":"PLoS One"},{"key":"pntd.0012985.ref028","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.molbiopara.2016.11.005","article-title":"WormBase ParaSite - a comprehensive resource for helminth genomics","volume":"215","author":"KL Howe","year":"2017","journal-title":"Mol Biochem Parasitol"},{"key":"pntd.0012985.ref029","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/978-1-4939-7737-6_5","article-title":"EuPathDB: the eukaryotic pathogen genomics database resource","volume":"1757","author":"S Warrenfeltz","year":"2018","journal-title":"Methods Mol Biol"},{"issue":"5","key":"pntd.0012985.ref030","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.ijpara.2017.12.001","article-title":"Advances in Fasciola hepatica research using \u201comics\u201d technologies","volume":"48","author":"K Cwiklinski","year":"2018","journal-title":"Int J Parasitol"},{"issue":"12","key":"pntd.0012985.ref031","doi-asserted-by":"crossref","first-page":"982","DOI":"10.3390\/pathogens9120982","article-title":"Proteomic profiling of the liver, hepatic lymph nodes, and spleen of buffaloes infected with Fasciola gigantica","volume":"9","author":"R-S Hu","year":"2020","journal-title":"Pathogens"},{"issue":"3","key":"pntd.0012985.ref032","article-title":"Transcriptomic landscape of hepatic lymph nodes, peripheral blood lymphocytes and spleen of swamp buffaloes infected with the tropical liver fluke Fasciola gigantica","volume":"16","author":"R-S Hu","year":"2022","journal-title":"PLoS Negl Trop Dis"},{"key":"pntd.0012985.ref033","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gky1006","article-title":"The Immune Epitope Database (IEDB): 2018 update","volume":"47","author":"R Vita","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"pntd.0012985.ref034","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1186\/1471-2164-6-79","article-title":"Bcipep: a database of B-cell epitopes","volume":"6","author":"S Saha","year":"2005","journal-title":"BMC Genomics"},{"issue":"23","key":"pntd.0012985.ref035","doi-asserted-by":"crossref","first-page":"3150","DOI":"10.1093\/bioinformatics\/bts565","article-title":"CD-HIT: accelerated for clustering the next-generation sequencing data","volume":"28","author":"L Fu","year":"2012","journal-title":"Bioinformatics"},{"issue":"10","key":"pntd.0012985.ref036","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkab122","article-title":"iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization","volume":"49","author":"Z Chen","year":"2021","journal-title":"Nucleic Acids Res"},{"issue":"2","key":"pntd.0012985.ref037","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s13748-015-0080-y","article-title":"Feature selection for high-dimensional data","volume":"5","author":"V Bol\u00f3n-Canedo","year":"2016","journal-title":"Prog Artif Intell"},{"key":"pntd.0012985.ref038","first-page":"3146","article-title":"Lightgbm: A highly efficient gradient boosting decision tree","volume":"30","author":"G Ke","year":"n.d","journal-title":"Advance neural information processing systems"},{"issue":"11","key":"pntd.0012985.ref039","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btad627","article-title":"Adaptive learning embedding features to improve the predictive performance of SARS-CoV-2 phosphorylation sites","volume":"39","author":"S Jiao","year":"2023","journal-title":"Bioinformatics"},{"issue":"5","key":"pntd.0012985.ref040","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btae297","article-title":"Integrated convolution and self-attention for improving peptide toxicity prediction","volume":"40","author":"S Jiao","year":"2024","journal-title":"Bioinformatics"},{"issue":"1","key":"pntd.0012985.ref041","article-title":"sAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure","volume":"39","author":"K Yan","year":"2023","journal-title":"Bioinformatics"},{"issue":"9","key":"pntd.0012985.ref042","doi-asserted-by":"crossref","first-page":"2837","DOI":"10.1007\/s00436-020-06833-x","article-title":"Proteomics and bioinformatics analysis of Fasciola hepatica somatic proteome in different growth phases","volume":"119","author":"J Xu","year":"2020","journal-title":"Parasitol Res"},{"issue":"12","key":"pntd.0012985.ref043","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1038\/nbt.1511","article-title":"MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification","volume":"26","author":"J Cox","year":"2008","journal-title":"Nat Biotechnol"},{"key":"pntd.0012985.ref044","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkac278","article-title":"DeepLoc 2.0: multi-label subcellular localization prediction using protein language models","volume":"50","author":"V Thumuluri","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"pntd.0012985.ref045","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkac1000","article-title":"The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest","volume":"51","author":"D Szklarczyk","year":"2023","journal-title":"Nucleic Acids Res"},{"issue":"5","key":"pntd.0012985.ref046","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.ijpara.2020.10.009","article-title":"Differential expression of microRNAs and tRNA fragments mediate the adaptation of the liver fluke Fasciola gigantica to its intermediate snail and definitive mammalian hosts","volume":"51","author":"R-S Hu","year":"2021","journal-title":"Int J Parasitol"},{"issue":"8016","key":"pntd.0012985.ref047","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with AlphaFold 3","volume":"630","author":"J Abramson","year":"2024","journal-title":"Nature"},{"key":"pntd.0012985.ref048","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkae1082","article-title":"InterPro: the protein sequence classification resource in 2025","volume":"53","author":"M Blum","year":"2025","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"pntd.0012985.ref049","doi-asserted-by":"crossref","first-page":"1954","DOI":"10.1128\/IAI.67.4.1954-1961.1999","article-title":"Vaccination with cathepsin L proteinases and with leucine aminopeptidase induces high levels of protection against fascioliasis in sheep","volume":"67","author":"L Piacenza","year":"1999","journal-title":"Infect Immun"},{"issue":"4","key":"pntd.0012985.ref050","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1093\/molbev\/mst010","article-title":"MAFFT multiple sequence alignment software version 7: improvements in performance and usability","volume":"30","author":"K Katoh","year":"2013","journal-title":"Mol Biol Evol"},{"key":"pntd.0012985.ref051","doi-asserted-by":"crossref","first-page":"124228","DOI":"10.1016\/j.ijbiomac.2023.124228","article-title":"Pretoria: An effective computational approach for accurate and high-throughput identification of CD8+ t-cell epitopes of eukaryotic pathogens","volume":"238","author":"P Charoenkwan","year":"2023","journal-title":"Int J Biol Macromol"},{"key":"pntd.0012985.ref052","doi-asserted-by":"crossref","first-page":"882995","DOI":"10.3389\/fcimb.2022.882995","article-title":"Machine learning and its applications for protozoal pathogens and protozoal infectious diseases","volume":"12","author":"R-S Hu","year":"2022","journal-title":"Front Cell Infect Microbiol"},{"key":"pntd.0012985.ref053","doi-asserted-by":"crossref","first-page":"935989","DOI":"10.3389\/fgene.2022.935989","article-title":"CD8TCEI-EukPath: a novel predictor to rapidly identify CD8+ T-cell epitopes of eukaryotic pathogens using a hybrid feature selection approach","volume":"13","author":"R-S Hu","year":"2022","journal-title":"Front Genet"},{"key":"pntd.0012985.ref054","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.82819","article-title":"Transformer-based deep learning for predicting protein properties in the life sciences","volume":"12","author":"A Chandra","year":"2023","journal-title":"Elife"},{"key":"pntd.0012985.ref055","article-title":"Leveraging transformers-based language models in proteome bioinformatics","volume":"23","author":"NQK Le","year":"2023","journal-title":"Proteomics"},{"issue":"20","key":"pntd.0012985.ref056","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e39038","article-title":"Transformer-based models for chemical SMILES representation: A comprehensive literature review","volume":"10","author":"ME Mswahili","year":"2024","journal-title":"Heliyon"},{"issue":"1","key":"pntd.0012985.ref057","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.molbiopara.2007.11.011","article-title":"Fasciola hepatica leucine aminopeptidase, a promising candidate for vaccination against ruminant fasciolosis","volume":"158","author":"D Acosta","year":"2008","journal-title":"Mol Biochem Parasitol"},{"key":"pntd.0012985.ref058","doi-asserted-by":"crossref","first-page":"109959","DOI":"10.1016\/j.vetpar.2023.109959","article-title":"A promising new target to control fasciolosis: Fasciola hepatica leucine aminopeptidase 2","volume":"320","author":"J Checa","year":"2023","journal-title":"Vet Parasitol"},{"issue":"1","key":"pntd.0012985.ref059","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1017\/S0022149X14000686","article-title":"Construction and evaluation of a chimeric protein made from Fasciola hepatica leucine aminopeptidase and cathepsin L1","volume":"90","author":"K Hern\u00e1ndez-Guzm\u00e1n","year":"2016","journal-title":"J Helminthol"},{"issue":"24","key":"pntd.0012985.ref060","doi-asserted-by":"crossref","first-page":"3234","DOI":"10.1016\/j.vaccine.2019.04.067","article-title":"Moderate protection is induced by a chimeric protein composed of leucine aminopeptidase and cathepsin L1 against Fasciola hepatica challenge in sheep","volume":"37","author":"S Ortega-Vargas","year":"2019","journal-title":"Vaccine"},{"key":"pntd.0012985.ref061","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1007\/978-1-0716-0475-5_14","article-title":"Design of a peptide-carrier vaccine based on the highly immunogenic Fasciola hepatica leucine aminopeptidase","volume":"2137","author":"C Salazar","year":"2020","journal-title":"Methods Mol Biol"},{"issue":"12","key":"pntd.0012985.ref062","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.ijpara.2014.07.011","article-title":"Liver fluke vaccines in ruminants: strategies, progress and future opportunities","volume":"44","author":"H Toet","year":"2014","journal-title":"Int J Parasitol"},{"issue":"3","key":"pntd.0012985.ref063","doi-asserted-by":"crossref","first-page":"555","DOI":"10.3390\/vaccines8030555","article-title":"Advances in the development of anti-Haemonchus contortus vaccines: challenges, opportunities, and perspectives","volume":"8","author":"M Ehsan","year":"2020","journal-title":"Vaccines (Basel)"},{"issue":"6","key":"pntd.0012985.ref064","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1080\/08830185.2019.1657426","article-title":"Immunoinformatics: in silico approaches and computational design of a multi-epitope, immunogenic protein","volume":"38","author":"AA Bahrami","year":"2019","journal-title":"Int Rev Immunol"},{"issue":"2","key":"pntd.0012985.ref065","doi-asserted-by":"crossref","first-page":"446","DOI":"10.3390\/vaccines11020446","article-title":"B-cell epitope mapping of the Plasmodium falciparum malaria vaccine candidate GMZ2.6c in a naturally exposed population of the brazilian amazon","volume":"11","author":"O Baptista B de","year":"2023","journal-title":"Vaccines (Basel)"},{"issue":"9","key":"pntd.0012985.ref066","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pntd.0005986","article-title":"High-resolution profiling of linear B-cell epitopes from mucin-associated surface proteins (MASPs) of Trypanosoma cruzi during human infections","volume":"11","author":"IM Durante","year":"2017","journal-title":"PLoS Negl Trop Dis"},{"issue":"3","key":"pntd.0012985.ref067","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1016\/j.ygeno.2018.02.017","article-title":"A comparative in silico linear B-cell epitope prediction and characterization for South American and African Trypanosoma vivax strains","volume":"111","author":"RLM Guedes","year":"2019","journal-title":"Genomics"},{"key":"pntd.0012985.ref068","doi-asserted-by":"crossref","first-page":"103788","DOI":"10.1016\/j.micpath.2019.103788","article-title":"Candidate antigenic epitopes for vaccination and diagnosis strategies of Toxoplasma gondii infection: A review","volume":"137","author":"A Javadi Mamaghani","year":"2019","journal-title":"Microb Pathog"},{"issue":"10","key":"pntd.0012985.ref069","article-title":"Identification of strain-specific B-cell epitopes in Trypanosoma cruzi using genome-scale epitope prediction and high-throughput immunoscreening with peptide arrays","volume":"7","author":"O Mendes TA de","year":"2013","journal-title":"PLoS Negl Trop Dis"},{"issue":"1","key":"pntd.0012985.ref070","doi-asserted-by":"crossref","first-page":"23","DOI":"10.3390\/antib8010023","article-title":"Peptides for infectious diseases: from probe design to diagnostic microarrays","volume":"8","author":"M Cretich","year":"2019","journal-title":"Antibodies (Basel)"},{"issue":"14","key":"pntd.0012985.ref071","doi-asserted-by":"crossref","first-page":"11685","DOI":"10.3390\/ijms241411685","article-title":"Impact of semiochemicals binding to Fel d 1 on Its 3D conformation and predicted B-cell epitopes using computational approaches","volume":"24","author":"R Durairaj","year":"2023","journal-title":"Int J Mol Sci"},{"key":"pntd.0012985.ref072","doi-asserted-by":"crossref","first-page":"302","DOI":"10.3389\/fimmu.2013.00302","article-title":"The structural basis of antibody-antigen recognition","volume":"4","author":"I Sela-Culang","year":"2013","journal-title":"Front Immunol"},{"key":"pntd.0012985.ref073","doi-asserted-by":"crossref","first-page":"1204157","DOI":"10.3389\/fmolb.2023.1204157","article-title":"Understanding structure-guided variant effect predictions using 3D convolutional neural networks","volume":"10","author":"G Ramakrishnan","year":"2023","journal-title":"Front Mol Biosci"},{"issue":"4","key":"pntd.0012985.ref074","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.cels.2020.08.016","article-title":"Fast and flexible protein design using deep graph neural networks","volume":"11","author":"A Strokach","year":"2020","journal-title":"Cell Syst"}],"updated-by":[{"DOI":"10.1371\/journal.pntd.0012985","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T00:00:00Z","timestamp":1746748800000}}],"container-title":["PLOS Neglected Tropical Diseases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pntd.0012985","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T18:12:02Z","timestamp":1746814322000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pntd.0012985"}},"subtitle":[],"editor":[{"given":"Aysegul","family":"Taylan Ozkan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,4,29]]},"references-count":74,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,4,29]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pntd.0012985","relation":{"new_version":[{"id-type":"doi","id":"10.1371\/journal.pntd.0012985","asserted-by":"object"}]},"ISSN":["1935-2735"],"issn-type":[{"value":"1935-2735","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,29]]}}}