Constructing a High-Affinity Nanobody Targeting the RSV pre-F Protein Based on AIDD and Site-Directed Mutagenesis: An Advanced <i>In-Silico</i> Drug Discovery Method
The respiratory syncytial virus (RSV) belongs to a highly contagious RNA virus that causes infants to suffer from serious respiratory infections and leads to extremely high levels of morbidity and mortality, which seriously threatens the health of infants. However, the drug currently used for preventing and treating infections of RSV shows limitations and side effects; thus, it is a long-term task to design and develop a new anti-RSV drug that has a better safety index and curative effect. The advantage of nanobody (NB) is that it has a smaller size, volume and molecular weight, lower immunogenicity and better stability, which can increase the neutralization efficiency with viruses; therefore, NB has the potential to accomplish the targeted treatment of RSV infections. In this study, the VHH sequence was filtered and acquired from the RSCB PDB database. Then, combined its 3D structure, which was constructed by homology modeling with the RSV pre-F protein. According to the docking results, we got the sequence of lead NB that will be further transformed through site-directed mutagenesis, and then obtained the engineered NB based on the condition of its binding energy score and docking pose. To improve the accuracy of engineered NB, its 3D model has been optimized, which was analyzed by different platforms. The molecular dynamics simulation was utilized to assess the stability between engineered NB with RSV pre-F protein, and the amino acid sequence of engineered NB has been translated in reverse to simulate the gene cloning, which can explore the possibility of biosynthesis with engineered NB.
Authors
- Haohuai He (ORCID: https://orcid.org/0000-0003-3831-3996)
- Chunchun Gan
- Weikai Jing
- Xiaopeng Wei (ORCID: https://orcid.org/0000-0002-5169-460X)
- Kailibinuer Abuduaini
- Areziguli Turupu
Institutions
- Quzhou College of Technology (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Journal of Computational Biophysics and Chemistry
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1142/s2737416525500942
- Primary Topic
- Respiratory viral infections research
- Type
- article
- Field-Weighted Citation Impact
- 0.00