Design and Evaluation of Peptide Inhibitors Targeting the Dimerization of SARS‐CoV‐2 Main Protease
The severe acute respiratory syndrome virus 2 (SARS-CoV-2) seriously impacted public health. The evolutionarily conserved viral chymotrypsin-like main protease (M<sup>pro</sup>) is an important target for anti-SARS-CoV-2 drug development. Previous studies have shown that the eight N-terminal amino acids (N8) of SARS-CoV M<sup>pro</sup> are essential for its dimerization, and are used to design inhibitors against SARS-CoV M<sup>pro</sup> dimerization. Here, we established a simple readout assay using SDS-PAGE and Coomassie blue staining to measure inhibitory activity of N8 peptide derived from SARS-CoV-2 M<sup>pro</sup>. To optimize its inhibitory effect, we then modified the side-chain length, charge, and hydrophilicity of the N8 peptide, and introduced a mutated M<sup>pro</sup> recognition sequence. As a result, we obtained a series of potent peptide inhibitors against SARS-CoV-2 M<sup>pro</sup>, with N8-A24 being the most efficient with an IC<sub>50</sub> value of 1.44 mM. We observed that N8-A24 reduced M<sup>pro</sup> dimerization with an IC<sub>50</sub> value of 0.86 mM. Molecular docking revealed that N8-A24 formed hydrogen bond interactions with critical dimeric interface residues, thus inhibiting its dimerization and activity. In conclusion, our study not only discovers a series of peptide inhibitors targeting the SARS-CoV-2 M<sup>pro</sup> dimerization, but also provides a promising strategy for the rational design of new inhibitors against COVID-19.
Authors
- Aimin Yang (ORCID: https://orcid.org/0000-0002-2240-5549)
- Zhiyi Zhao (ORCID: https://orcid.org/0000-0001-7238-7580)
- Shaolin Zhang (ORCID: https://orcid.org/0000-0002-2259-7704)
- Yi Yang (ORCID: https://orcid.org/0000-0001-9044-0277)
- Xiaoying Li (ORCID: https://orcid.org/0000-0002-9932-6654)
- Yi‐An Chen (ORCID: https://orcid.org/0000-0002-5892-1801)
- Lu Liu (ORCID: https://orcid.org/0009-0008-4757-2862)
Institutions
- Chongqing University (CN)
Publication Details
- Journal
- ChemBioChem
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1002/cbic.202400688
- Citations
- 2
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.72
Funders
- National Natural Science Foundation of China
- Chongqing University
- Natural Science Foundation of Chongqing
- Centre Scientifique et Technique du Bâtiment
- ShanghaiTech University
- Venture and Innovation Support Program for Chongqing Overseas Returnees
- Fundamental Research Funds for the Central Universities