Designing antibody against highly conserved region of dengue envelope protein by in silico screening of scFv mutant library

通过计算机筛选 scFv 突变体库设计针对登革热包膜蛋白高度保守区域的抗体

阅读:4
作者:Abhishek Singh Rathore, Animesh Sarker, Rinkoo Devi Gupta

Abstract

Dengue being one of the deadliest diseases of tropical regions, enforces to put continuous efforts for the development of vaccine and effective therapeutics. Most of the antibodies generated during dengue infection are non-neutralizing and cause antibody dependent enhancement. Hence, making a potent neutralizing antibody against all four dengue serotypes could be very effective for the treatment. However, designing a single antibody for all serotypes is difficult due to variation in protein sequences. Therefore, the objective is to identify conserved region of dengue envelope protein and then develop an antibody against that conserved region. Before advancing to the development of such an antibody, it is desirable to validate the interactions between antibody and dengue envelope protein. In silico analysis of such interactions provides a good platform to find out a suitable region to design and construct an antibody against it by analyzing antigen-antibody interaction before synthesizing the antibody. In this study, two highly conserved regions of dengue envelope protein were identified and an scFv was constructed against it. Both scFv and FuBc proteins were expressed in bacterial expression system and binding efficiency was analyzed by SPR analysis with KD value 2.3 μM. In order to improve binding efficiency, an in silico scFv mutant library was created which was virtually screened for higher binding efficiency. Six mutants with high binding efficiency were selected for further analysis. The binding ability of these mutants were predicted using simulation analysis which shows these mutations were stabilizing scFv-FuBc complex.

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。