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中国生物工程杂志

China Biotechnology
China Biotechnology  2023, Vol. 43 Issue (7): 88-100    DOI: 10.13523/j.cb.2301022
    
Application of Immunoinformatics in Epitope Vaccine Development
Hong-sheng FENG1,2,Hang JIN1,2,Yong-yu GAO3,Yu-han XIAN1,2,Hai-yang LI1,2,Si-yu YANG1,2,Ai-ming JIA4,**(),Feng-shan GAO1,2,**()
1 College of Life and Health, Dalian University, Dalian 116622, China
2 The Dalian Gene and Protein Engineering for Drug Screening Key Laboratory, Dalian 116622, China
3 College of Veterinary Medicine, Jilin Agricultural University, Changchun 130118, China
4 The Second Hospital of Dalian Medical University, Dalian 116027, China
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Abstract  

Presently, to design epitope vaccines, the research and development process is generally to use computer-aided immunoinformatics tools and related technical methods to analyze acquired or known nucleotide and amino acid sequences to determine and pre-screen out possible dominant epitopes, and then prepare polypeptide vaccines with dominant epitopes through synthetic or genetic engineering techniques. The rapid development of immunoinformatics has been successfully applied to the field of vaccinology, and the immunoinformatics method is the most effective method to develop vaccines based on epitope polypeptide. Immunoinformatics, the general process of immunoinformatics in epitope vaccine design and validation, the immunoinformatics tools involved in the design of epitope vaccines, and the specific application of immunoinformatics in the design of epitope vaccines are reviewed, which will provide reference for reasonable design and development of effective epitope vaccines.



Key wordsImmunoinformatics      Epitope peptides      Epitope vaccines     
Received: 15 January 2023      Published: 03 August 2023
ZTFLH:  Q816  
Cite this article:

Hong-sheng FENG, Hang JIN, Yong-yu GAO, Yu-han XIAN, Hai-yang LI, Si-yu YANG, Ai-ming JIA, Feng-shan GAO. Application of Immunoinformatics in Epitope Vaccine Development. China Biotechnology, 2023, 43(7): 88-100.

URL:

https://manu60.magtech.com.cn/biotech/10.13523/j.cb.2301022     OR     https://manu60.magtech.com.cn/biotech/Y2023/V43/I7/88

Fig.1 The general flow chart for designing epitope vaccines using immunoinformatics
验证方法 验证内容
酶联免疫吸附测定(enzyme-linked immunosorbent assay,ELISA) 免疫模型体内抗体滴度测定;细胞免疫原性检测,如IgA、IgG、IgE等抗体检测
酶联免疫斑点技术(enzyme-linked immunospot assay,ELISPOT) 评估抗原特异的T细胞功效,即IFN-γ释放检测
聚丙烯酰胺凝胶电泳(sodium dodecyl sulfate polyacrylamide gel electrophoresis,SDS-PAGE) 抗体纯度鉴定
MTT比色法 细胞增殖检测,如脾淋巴细胞增殖测定
病毒TCID50测定 免疫动物目的器官内的病毒滴度测定
组织病理学评估 分析免疫模型受病原攻击后其靶器官的病理损伤
Table 1 Common validation methods used after vaccine development
工具 网址 功能(MHC类型)
Propred-1 http://www.imtech.res.in/raghava/propred1/ I
Propred http://www.imtech.res.in/raghava/propred/ II
IEDB-MHCI http://tools.immuneepitope.org/mhci/ I
IEDB-MHCII http://tools.immuneepitope.org/mhcii/ II
NetMHC http://www.cbs.dtu.dk/services/NetMHC/ I
NetMHCII http://www.cbs.dtu.dk/services/NetMHCII/ II
NetMHCpan http://www.cbs.dtu.dk/services/NetMHCpan/ I
NetMHCIIpan http://www.cbs.dtu.dk/services/NetMHCIIpan/ II
SVMHC http://abi.inf.uni-tuebingen.de/Services/SVMHC/ I and II
SVRMHC http://us.accurascience.com/SVRMHCdb/ I and II
EPISOPT http://bio.med.ucm.es/episopt.html I
EpiTOP http://www.pharmfac.net/EpiTOP II
EpiJen http://www.ddg-pharmfac.net/epijen/EpiJen/EpiJen.htm I
Vaxign http://www.violinet.org/vaxign/ I and II
MHCPred http://www.ddg-pharmfac.net/mhcpred/MHCPred/ I and II
Table 2 Part of the online tools for T-cell epitope prediction
工具 网址 特点
ABCPred[8] http://www.imtech.res.in/raghava/abcpred/ 使用人工神经网络预测
BCPred[9] http://ailab.ist.psu.edu/bcpred/ 使用亚序列核预测
ElliPro[10] http://tools.iedb.org/ellipro/ 基于蛋白质结构的几何特性运行
DiscoTope[11] http://www.cbs.dtu.dk/services/DiscoTope-2.0 获取蛋白质三维结构数据,通过表面测量进行预测
PEPITO[12] http://pepito.proteomics.ics.uci.edu/ 使用氨基酸倾向得分和多距离的半球形暴露值组合预测
SEPPA[13] http://lifecenter.sgst.cn/seppa/ 利用残基和相邻残基的空间紧凑性预测
EPSVR[14] http://sysbio.unl.edu/EPSVR/ 预测涉及向量回归方法
DRREP[15] https://github.com/gsher1/DRREP 泛化能力在所有测试数据集中稳定且具有不同水平的表位密度
PEPITOPE[16] http://pepitope.tau.ac.il/ 基于一组针对目标单克隆抗体亲和选择的肽进行预测
Table 3 Part of the online tools for B-cell epitope prediction
工具 网址 功能
VaxiJen v.2.0[18] http://ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html 蛋白/表位抗原性鉴定
AllerTOP v.2.0[19] http://ddg-pharmfac.net/AllerTOP/ 致敏性分析
ProtParam[20] http://expasy.org/tools/protparam.html 蛋白理化性质分析
ToxinPred[21] http://crdd.osdd.net/raghava/toxinpred/ 毒性分析
Innovagen https://pepcalc.com/peptide-solubility-calculator.php 蛋白水溶性分析
Protein Sol https://protein-sol.manchester.ac.uk/ 疫苗溶解度分析
Prosa Web https://prosa.services.came.sbg.ac.at/prosa.php 疫苗Z-score分析
NCBI BLAST https://blast.ncbi.nlm.nih.gov/Blast.cgi 宿主同源性分析
Table 4 Part of the online tools for epitope analysis
工具 网址 功能
SOPMA[22] https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html 二级结构分析与预测
PSIPRED 4.0[23] http://bioinf.cs.ucl.ac.uk/psipred/ 预测二级结构、跨膜拓扑结构、跨膜螺旋、折叠和结构域识别
AlphaFold2[24] https://alphafold.ebi.ac.uk/ 预测蛋白质的3D结构
PEP-FOLD3[25] http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD3 线性肽从头结构3D预测
I-TASSER[26] http://zhanglab.ccmb.med.umich.edu/I-TASSER/ 蛋白质3D结构预测的最佳服务器
RaptorX[27] http://raptorx.uchicago.edu/ 预测蛋白质的3D结构
3Drefine[28] http://sysbio.rnet.missouri.edu/3Drefine/ 完善蛋白质的3D结构
GalaxyRefine[29] http://galaxy.seoklab.org 完善蛋白质的3D结构
RAMPage [30] http://mordred.bioc.cam.ac.uk/~rapper/rampage.php 分析预测模型的拉马钱德兰图,验证预测模型的质量和准确性
Pymol[31] https://pymol.org/ 用于进行可视化的3D结构建模
SignalP 4.1[32] https://services.healthtech.dtu.dk/service.php?SignalP-4.1 发现疫苗中的任何潜在信号肽
TMHMM 2.0[33] https://services.healthtech.dtu.dk/service.php?TMHMM-2.0 搜索最终疫苗构建体中潜在的跨膜螺旋
Table 5 Online tool for structural prediction of vaccine constructs
工具 网址 功能
UCSF ChimeraX[34] https://www.rbvi.ucsf.edu/chimerax 分子结构制备
ClusPro 2.0[35] https://cluspro.org/help.php 对接目的模拟
HADDOCK 2.4[36] https://wenmr.science.uu.nl/haddock2.4/ 对接目的模拟
PDBePISA https://www.ebi.ac.uk/msd-srv/prot_int/pistart.html 分析结合能、界面面积和氢键
PDBsum http://www.ebi.ac.uk/thornton-srv/databases/pdbsum/ 分析结合能、界面面积和氢键
Table 6 Molecular docking online access tools
Fig.2 The flow chart for the design of a multi-epitope peptide vaccine against DENV
Fig.3 The flow chart for design of a multi-epitopes candidate vaccine against Brucella
Fig.4 The flow chart for design of a multi-epitope candidate vaccine against Toxoplasma gondii infection
Fig.5 The flow chart for design of a novel PD-1 B-cell peptide epitope vaccine
Fig.6 The flow chart for design of a multi-epitope vaccine design for Amb a 11
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