Design and structural bioinformatic analysis of polypeptide antigens useful for the SRLV serodiagnosis.
Antigen design
Circular dichroism
ELISA test
Modelling and structural analysis
Molecular dynamics
Protein clustering
SRLV serodiagnosis
Journal
Journal of virological methods
ISSN: 1879-0984
Titre abrégé: J Virol Methods
Pays: Netherlands
ID NLM: 8005839
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
received:
09
02
2021
revised:
30
06
2021
accepted:
18
08
2021
pubmed:
30
8
2021
medline:
22
3
2022
entrez:
29
8
2021
Statut:
ppublish
Résumé
Due to their intrinsic genetic, structural and phenotypic variability the Lentiviruses, and specifically small ruminant lentiviruses (SRLV), are considered viral quasispecies with a population structure that consists of extremely large numbers of variant genomes, termed mutant spectra or mutant cloud. Immunoenzymatic tests for SRLVs are available but the dynamic heterogeneity of the virus makes the development of a diagnostic "golden standard" extremely difficult. The ELISA reported in the literature have been obtained using proteins derived from a single strain or they are multi-strain based assay that may increase the sensitivity of the serological diagnosis. Hundreds of SRLV protein sequences derived from different viral strains are deposited in GenBank. The aim of this study is to verify if the database can be exploited with the help of bioinformatics in order to have a more systematic approach in the design of a set of representative protein antigens useful in the SRLV serodiagnosis. Clustering, molecular modelling, molecular dynamics, epitope predictions and aggregative/solubility predictions were the main bioinformatic tools used. This approach led to the design of SRLV antigenic proteins that were expressed by recombinant DNA technology using synthetic genes, analyzed by CD spectroscopy, tested by ELISA and preliminarily compared to currently commercially available detection kits.
Identifiants
pubmed: 34454989
pii: S0166-0934(21)00205-6
doi: 10.1016/j.jviromet.2021.114266
pii:
doi:
Substances chimiques
Peptides
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
114266Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.