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用于 SRLV 血清学诊断的多肽抗原的设计和结构生物信息学分析。

Design and structural bioinformatic analysis of polypeptide antigens useful for the SRLV serodiagnosis.

机构信息

Department of Sciences, University of Basilicata, viale Ateneo Lucano 10, 85100, Potenza, Italy.

Department of Sciences, University of Basilicata, viale Ateneo Lucano 10, 85100, Potenza, Italy.

出版信息

J Virol Methods. 2021 Nov;297:114266. doi: 10.1016/j.jviromet.2021.114266. Epub 2021 Aug 26.

DOI:10.1016/j.jviromet.2021.114266
PMID:34454989
Abstract

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.

摘要

由于其内在的遗传、结构和表型变异性,慢病毒,特别是小反刍动物慢病毒(SRLV),被认为是具有群体结构的病毒准种,其群体结构由数量极其庞大的变异基因组组成,称为突变谱或突变云。目前已有用于检测 SRLV 的免疫酶试验,但由于病毒的动态异质性,使得开发诊断“金标准”变得极其困难。文献中报道的 ELISA 是使用源自单一毒株的蛋白获得的,或者是基于多毒株的检测方法,这可能会提高血清学诊断的敏感性。数以百计源自不同病毒株的 SRLV 蛋白序列已被存入 GenBank。本研究旨在验证是否可以借助生物信息学技术利用数据库,以便在设计一套用于 SRLV 血清学诊断的有代表性的蛋白抗原时,采用更系统的方法。聚类、分子建模、分子动力学、表位预测和聚集/可溶性预测是主要使用的生物信息学工具。这种方法导致了使用合成基因通过重组 DNA 技术表达的 SRLV 抗原蛋白的设计,通过 CD 光谱分析、ELISA 测试,并初步与目前市售的检测试剂盒进行比较。

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