PMID- 37258930
OWN - NLM
STAT- MEDLINE
DCOM- 20230602
LR  - 20230606
IS  - 1940-6029 (Electronic)
IS  - 1064-3745 (Linking)
VI  - 2673
DP  - 2023
TI  - Immunoinformatics Vaccine Design for Zika Virus.
PG  - 411-429
LID - 10.1007/978-1-0716-3239-0_28 [doi]
AB  - Zika virus (ZIKV) is an emerging virus from the Flaviviridae family and 
      Flavivirus genus that has caused important outbreaks around the world. ZIKV 
      infection is associated with severe neuropathology in newborns and adults. Until 
      now, there is no licensed vaccine available for ZIKV infection. Therefore, the 
      development of a safe and effective vaccine against ZIKV is an urgent need. 
      Recently, we designed an in silico multi-epitope vaccine for ZIKV based on 
      immunoinformatics tools. To construct this in silico ZIKV vaccine, we used a 
      consensus sequence generated from ZIKV sequences available in databank. Then, we 
      selected CD4+ and CD8+ T cell epitopes from all ZIKV proteins based on the 
      binding prediction to class II and class I human leukocyte antigen (HLA) 
      molecules, promiscuity, and immunogenicity. ZIKV Envelope protein domain III 
      (EDIII) was added to the construct and B cell epitopes were identified. Adjuvants 
      were associated to increase immunogenicity. Distinct linkers were used for 
      connecting the CD4+ and CD8+ T cell epitopes, EDIII, and adjuvants. Several 
      analyses, such as antigenicity, population coverage, allergenicity, autoimmunity, 
      and secondary and tertiary structures of the vaccine, were evaluated using 
      various immunoinformatics tools and online web servers. In this chapter, we 
      present the protocols with the rationale and detailed steps needed for this in 
      silico multi-epitope ZIKV vaccine design.
CI  - (c) 2023. The Author(s), under exclusive license to Springer Science+Business 
      Media, LLC, part of Springer Nature.
FAU - Antonelli, Ana Clara
AU  - Antonelli AC
AD  - Department of Bioscience and Technology, Institute of Tropical Pathology and 
      Public Health, Federal University of Goias, Goiania, Goias, Brazil.
FAU - Almeida, Vinnycius Pereira
AU  - Almeida VP
AD  - Department of Bioscience and Technology, Institute of Tropical Pathology and 
      Public Health, Federal University of Goias, Goiania, Goias, Brazil.
FAU - da Fonseca, Simone Goncalves
AU  - da Fonseca SG
AD  - Department of Bioscience and Technology, Institute of Tropical Pathology and 
      Public Health, Federal University of Goias, Goiania, Goias, Brazil. 
      sfonseca@ufg.br.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Methods Mol Biol
JT  - Methods in molecular biology (Clifton, N.J.)
JID - 9214969
RN  - 0 (Epitopes, T-Lymphocyte)
RN  - 0 (Epitopes, B-Lymphocyte)
RN  - 0 (Viral Envelope Proteins)
SB  - IM
MH  - Infant, Newborn
MH  - Humans
MH  - *Zika Virus/genetics
MH  - *Zika Virus Infection/prevention & control
MH  - Epitopes, T-Lymphocyte
MH  - Epitopes, B-Lymphocyte
MH  - Viral Envelope Proteins
MH  - Computational Biology/methods
MH  - Molecular Docking Simulation
OTO - NOTNLM
OT  - B cell epitopes
OT  - CD4 epitopes
OT  - CD8 epitopes
OT  - Epitope prediction
OT  - Immunogenicity
OT  - Immunoinformatics tools
OT  - Multi-epitope
OT  - Vaccine
OT  - ZIKV
EDAT- 2023/06/01 01:08
MHDA- 2023/06/02 06:42
CRDT- 2023/05/31 23:32
PHST- 2023/06/02 06:42 [medline]
PHST- 2023/06/01 01:08 [pubmed]
PHST- 2023/05/31 23:32 [entrez]
AID - 10.1007/978-1-0716-3239-0_28 [doi]
PST - ppublish
SO  - Methods Mol Biol. 2023;2673:411-429. doi: 10.1007/978-1-0716-3239-0_28.