Back

Distinct Mechanisms for Inhibition of SARS-CoV-2 Main Protease: Dimerization Promoted by Peptidomimetic Inhibitors and Disrupted by Ebselen

Liu, C.; Jia, Q.; Zhao, C.; Zhongping, Y.

2025-12-16 molecular biology
10.1101/2025.11.16.688752 bioRxiv
Show abstract

The SARS-CoV-2 main protease (Mpro) is a key target for antiviral drugs. Given its conserved sequence across coronaviruses and its essential role in viral replication, numerous inhibitors have been developed to target its active site. Mpro exists in equilibrium between the active dimer and inactive monomer, rendering the targeting of dimerization as a promising alternative strategy for drug development. This study addresses knowledge gaps regarding the monomer-dimer equilibrium and conformational changes of Mpro induced by inhibitor binding. We utilized 13C labeling combined with native mass spectrometry to assess how different types of inhibitors (including peptidomimetic inhibitors PF-07321332, PF-00835231, GC376, boceprevir; non-peptidomimetic inhibitors carmofur, ebselen and its analog MR6-31-2; and allosteric inhibitors AT7519 and pelitinib) influence the monomer-dimer equilibrium and subunit exchange of Mpro. Additionally, we employed hydrogen/deuterium exchange mass spectrometry (HDX-MS) to investigate the conformational dynamics of Mpro and its interactions with these inhibitors. Key findings revealed divergent mechanisms: peptidomimetic inhibitors significantly shifted the equilibrium towards the dimeric state, suppressing subunit exchange dynamics and rigidifying the dimer interface. In contrast, ebselen impaired the dimer form and increased the flexibility of the dimer interface. Notably, we identified a novel covalent binding site for ebselen at C300 by tandem mass spectrometry, with molecular dynamics simulations further indicating that this modification allosterically altered the hydrogen bond network of the Mpro dimer interface. Overall, this study reveals distinct inhibitory modes between peptidomimetic inhibitors and ebselen, highlighting the potential of targeting allosteric sites at the dimer interface for the design of next-generation Mpro inhibitors.

Matching journals

The top 14 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.