Immunoinformatics analysis of the proteins MPT83 and MPT51 to design a possible chimeric vaccine against Mycobacterium tuberculosis

利用免疫信息学分析蛋白质MPT83和MPT51,设计一种可能的抗结核分枝杆菌嵌合疫苗

阅读:1

Abstract

Mycobacterium tuberculosis (Mtb) is the pathogen that causes tuberculosis (TB). This disease affects one-third of the world's population, mainly in its latent form. The use of reverse vaccinology and immunoinformatics stands out for the production of vaccines based on peptides or proteins, since they are more specific, safe, effective and economical. The present study evaluated the immunological potential of the proteins MPT83 and MPT51 for vaccine production, comparing them with MPT64. To do this, the sequences of these proteins from MTB H37Rv were downloaded and analyzed. The prediction of T and B cell epitopes was performed, and the adjuvant (50 S L7/L12) was included in the fusion of MPT83 and MPT51 to enhance the immune response. The allergenicity, antigenicity, solubility and physicochemical properties of the fused protein fragments were evaluated. Through different programs, a variety of bioinformatics tools were used to predict, analyze and validate the tertiary structure. The results of the in silico immunological simulation of the chimeric protein demonstrated that the best region for use as an epitope is the initial part of MPT83, consisting of 100 amino acid residues, and the final portion of MPT51, consisting of 99 amino acid residues, with a significant immunological response, excellent antigenicity (1.02) and no allergenicity. The secondary structure revealed that the majority of alpha-helices are in the initial part of the proteins, and the chimeric vaccine has 3 beta strands along its length. Finally, the chimeric vaccine candidate and MPT64 were efficiently cloned into the bacterial vector and successfully expressed in Escherichia coli thereby facilitating future in vivo studies with potentially promising results.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。