Prospects for the structure‒function evolution of SARS-CoV-2 main protease inhibitors

Area of Science:

• Virology and Drug Discovery
• Computational Chemistry and Molecular Modeling

Background:

• The COVID-19 pandemic, caused by SARS-CoV-2, highlights the need for effective antiviral therapies.
• Coronaviruses, including SARS-CoV-2, frequently mutate, necessitating adaptable treatment strategies.
• The viral main protease (Mpro) is a critical target for direct-acting antiviral drugs, but current options like nirmatrelvir have limitations.

Purpose of the Study:

• To identify essential criteria for potent SARS-CoV-2 Mpro inhibitors.
• To computationally design novel Mpro inhibitors with improved efficacy, selectivity, and pharmacokinetic properties.
• To address the ongoing need for effective, orally available antiviral medications against SARS-CoV-2.

Main Methods:

• Comprehensive literature review of existing Mpro inhibitor studies.
• Extensive molecular dynamics simulations of Mpro-inhibitor complexes.
• Computational prediction of binding affinity and ADME properties for novel inhibitor candidates.

Main Results:

• Established a set of criteria for effective Mpro inhibitors based on literature analysis.
• Designed potential new inhibitors and their constituent fragments.
• Predicted favorable binding affinity, selectivity, bioavailability, and solubility for the designed compounds.

Conclusions:

• The study provides a framework for designing next-generation SARS-CoV-2 Mpro inhibitors.
• Computational methods are effective in predicting drug-like properties for antiviral candidates.
• The designed compounds show promise for developing orally administered COVID-19 therapeutics.