IMR Press / FBL / Volume 28 / Issue 4 / DOI: 10.31083/j.fbl2804067
Open Access Original Research
In Silico Optimization of SARS-CoV-2 Spike Specific Nanobodies
Xiaohong Zhu1,2,†Ke An1,2,†Junfang Yan1Peiyi Xu1Chen Bai1,3,*
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1 Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, 518172 Shenzhen, Guangdong, China
2 School of Chemistry and Materials Science, University of Science and Technology of China, 230026 Hefei, Anhui, China
3 Chenzhu Biotechnology Co., Ltd., 310005 Hangzhou, Zhejiang, China
*Correspondence: baichen@cuhk.edu.cn (Chen Bai)
These authors contributed equally.
Front. Biosci. (Landmark Ed) 2023, 28(4), 67; https://doi.org/10.31083/j.fbl2804067
Submitted: 24 September 2022 | Revised: 1 December 2022 | Accepted: 12 December 2022 | Published: 6 April 2023
Copyright: © 2023 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide, caused a global pandemic, and killed millions of people. The spike protein embedded in the viral membrane is essential for recognizing human receptors and invading host cells. Many nanobodies have been designed to block the interaction between spike and other proteins. However, the constantly emerging viral variants limit the effectiveness of these therapeutic nanobodies. Therefore, it is necessary to find a prospective antibody designing and optimization approach to deal with existing or future viral variants. Methods: We attempted to optimize nanobody sequences based on the understanding of molecular details by using computational approaches. First, we employed a coarse-grained (CG) model to learn the energetic mechanism of the spike protein activation. Next, we analyzed the binding modes of several representative nanobodies with the spike protein and identified the key residues on their interfaces. Then, we performed saturated mutagenesis of these key residue sites and employed the CG model to calculate the binding energies. Results: Based on analysis of the folding energy of the angiotensin-converting enzyme 2 (ACE2) -spike complex, we constructed a detailed free energy profile of the activation process of the spike protein which provided a clear mechanistic explanation. In addition, by analyzing the results of binding free energy changes following mutations, we determined how the mutations can improve the complementarity with the nanobodies on spike protein. Then we chose 7KSG nanobody as a template for further optimization and designed four potent nanobodies. Finally, based on the results of the single-site saturated mutagenesis in complementarity determining regions (CDRs), combinations of mutations were performed. We designed four novel, potent nanobodies, all exhibiting higher binding affinity to the spike protein than the original ones. Conclusions: These results provide a molecular basis for the interactions between spike protein and antibodies and promote the development of new specific neutralizing nanobodies.

Keywords
SARS-CoV-2 spike protein
nanobody
coarse-grained (CG) model
binding free energy
Funding
22103066/National Natural Science Foundation of Youth Fund Project
20210316202830001/the 2021 Basic Research General Project of Shenzhen, China
C10120180043/Warshel Institute for Computational Biology at the Chinese University of Hong Kong, Shenzhen
Figures
Fig. 1.
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