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.

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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

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article

Design and Evaluation of Peptide Inhibitors Targeting the Dimerization of SARS‐CoV‐2 Main Protease

Aimin Yang, Zhiyi Zhao, Shaolin Zhang, Yi Yang et al.
2 citations
ChemBioChem
Computational Drug Discovery Methods
0.72
article

Design and Evaluation of Peptide Inhibitors Targeting the Dimerization of SARS‐CoV‐2 Main Protease

Aimin Yang, Zhiyi Zhao, Shaolin Zhang, Yi Yang, Xiaoying Li, Yi‐An Chen, Lu Liu
article en
2 citations

Abstract

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.

ChemBioChemVol. 26(1)
Chongqing University (CN)
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
Good health and well-being
Openalex Percentile: Top 25%
Computational Drug Discovery Methods
0.72
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