| dc.description.abstract | Vietnamese scientists are facing the urge to inventing the vaccine for African Swine
Fever Virus. According to that requirement, this research would be considered to
shorten the vaccine invention. By using bioinformatics, the selection of the potential
gene for the vaccine could help the scientist to skip many experiments and reduce
the explore time. This research aims to predict the most potential genes which could
use for vaccine production and the species of pigs that resist the African Swine Fever
Virus. This prediction focuses on combining the Major Histocompatibility Complex
(MHC) Class II of the pig and 11 peptides of African Swine Fever Virus, which are
from Outer, Inner, and Capsid of the viral structure.
The pig has 99 alleles of MHC Class II, in which the exon 2 plays a role as the structure
of β1 in the MHC Class II that combines directly with the peptides of the virus. The
combination ability of the peptide with exon 2 presents the immunogenicity of the
peptides. According to the Denmark Technology University's tool, "NetMHCIIpan 3.2
server" is one of the useful tools to build a database of the combination between MHC
Class II and the peptides. The peptides which combine powerfully with the exon 2
are the potential materials for the vaccine production. The result demonstrates B646L
is the most potential gene, which binds significantly up to 68 alleles of the MHC.
Furthermore, the alleles 06 of the pig's MHC Class II has the most robust resistant
with the African Swine Fever Virus. However, the previous research demonstrates
that a severe ASFV vaccine leads to a couple of clinical problems after the vaccination.
Further research is needed to launch in the wet lab to finish the vaccine invention or
continue predicting other viral genes. | en_US |
