Molecular dynamic simulations to explore the broad-spectrum activity of the inhibitor PF-07321332 against human coronavirus
The main protease (M<sup>pro</sup>) stands as a pivotal enzyme crucial for coronavirus replication, thus serving as a prime target for coronavirus drug discovery endeavors. Nirmatrelvir (PF-07321332), an antiviral compound developed by Pfizer, has been engineered to selectively inhibit the M<sup>pro</sup> of SARS-CoV-2 by directly binding to its catalytic cysteine residue (Cys145). In a bid to scrutinize the expansive inhibitory spectrum of PF-07321332 against a gamut of human pathogenic coronaviruses, we undertook an exhaustive investigation leveraging molecular dynamics (MD) simulations in conjunction with binding free energy (BFE) calculations. Molecular dockings of PF-07321332 with the M<sup>pro</sup>s of seven human coronaviruses yielded their optimal binding modes (complexes), subsequently subjected to rigorous MD simulations and BFE assessments. The results of MD simulations indicated that PF-07321332 can remain stable in the substrate-binding cavity of all the seven human coronaviruses M<sup>pro</sup>s. A detailed comparison of BFE components revealed that intermolecular van der Waals (vdW) interactions play a significantly more crucial role in maintaining association and determining the high binding affinity than intermolecular electrostatic interactions. Analyses of residue BFE decomposition reveals Cys145 as a pivotalt amino acid, positively influencing the stable binding between M<sup>pro</sup>s and inhibitor. These finding imply that PF-07321332 has the potential to be an effective anti-coronavirus inhibitor and also provide insights into inhibitor optimization and drug design strategies against human coronavirus.
Authors
- Meng-Ting Liu (ORCID: https://orcid.org/0009-0006-3420-0483)
- Peng Sang
- Yi Li (ORCID: https://orcid.org/0000-0002-2092-4505)
- Liquan Yang
- Yuting Wang (ORCID: https://orcid.org/0009-0000-6985-3114)
Institutions
- Innovation Team (China) (HK)
- Dali University (CN)
Publication Details
- Journal
- Journal of Biomolecular Structure and Dynamics
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1080/07391102.2024.2431661
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China