EpiBuilder: A Tool for Assembling, Searching, and Classifying B-Cell Epitopes

被引:4
作者
Moreira, Renato Simoes [1 ,2 ]
Benetti Filho, Vilmar [3 ]
Calomeno, Nathalia Anderson [1 ]
Wagner, Glauber [3 ]
Miletti, Luiz Claudio [1 ]
机构
[1] Univ Estado Santa Catarina UDESC, Ctr Ciencias Agrovet CAV, Dept Prod Anim & Alimentos, Lab Hemoparasitas & Vetores, Av Luiz Camoes,2090 Bairro Conta Dinheiro, BR-88520000 Lages, SC, Brazil
[2] Inst Fed Santa Catarina IFSC, Lages, SC, Brazil
[3] Univ Fed Santa Catarina, Lab Bioinformat, Campus Joao David Ferreira Lima,Setor F,Bloco A, BR-88040970 Florianopolis, SC, Brazil
关键词
Immunoinformatics; BepiPred-2.0; Galaxy; PREDICTION; ANTIBODY;
D O I
10.1177/11779322221095221
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Epitopes are portions of a protein that are recognized by antibodies. These small amino acid sequences represent a significant breakthrough in a branch of bioinformatics called immunoinformatics. Various software are available for linear B-cell epitope (BCE) prediction such as ABCPred, SVMTrip, EpiDope, and EpitopeVec; a well-known BCE predictor is BepiPred-2.0. However, despite the prediction. there are several essential steps, such as epitope assembly, evaluation, and searching for epitopes in other proteomes. Here, we present EpiBuilder (https://epibuilder.sourceforge.io ). a user friendly software that assists in epitope assembly, classifying and searching using input results of BepiPred-2.0. EpiBuilder generates several output results from these data and supports a proteome-wide processing approach. In addition. this software provides the following features: Chou & Fasman beta-turn prediction, Emini surface accessibility prediction, Karplus and Schulz flexibility prediction, Kolaskar and Tongaonkar antigenicity, Parker hydrophilicity prediction. N-glycosylation domains, and hydropathy. These information generate a unique topology for each epitope, visually demonstrating its characteristics. The software can search the entire epitope sequence in various FASTA files, and it allows to use BLASTP to identify epitopes that eventually have sequence variations. As an EpiBuilder application, we developed a epitope dataset from the protozoan Trypanosoma brucei gambiense, the gram-positive bacterium C/ostridioides difficile, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
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页数:11
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