Angela Ostuni, Magnus Monné, Maria Antonietta Crudele, Pier Luigi Cristinziano, Stefano Cecchini, Mario Amati, Jolanda De Vendel, Paolo Raimondi, Taxiarchis Chassalevris, Chrysostomos I Dovas, Alfonso Bavoso
Journal of virological methods 2021 NovDue 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. Copyright © 2021 Elsevier B.V. All rights reserved.
Angela Ostuni, Magnus Monné, Maria Antonietta Crudele, Pier Luigi Cristinziano, Stefano Cecchini, Mario Amati, Jolanda De Vendel, Paolo Raimondi, Taxiarchis Chassalevris, Chrysostomos I Dovas, Alfonso Bavoso. Design and structural bioinformatic analysis of polypeptide antigens useful for the SRLV serodiagnosis. Journal of virological methods. 2021 Nov;297:114266
PMID: 34454989
View Full Text