In Silico Substrate-Binding Profiling for SARS-CoV-2 Main Protease (M^pro) Using Hexapeptide Substrates

Area of Science:

• Biochemistry
• Structural Biology
• Computational Chemistry

Background:

• The SARS-CoV-2 main protease (Mpro) is a critical enzyme for viral replication.
• Mpro facilitates viral maturation by cleaving polyproteins at specific sites, such as Leu-Gln↓(Ser/Ala/Gly).
• Understanding Mpro-substrate interactions is key to developing antiviral therapies.

Purpose of the Study:

• To investigate the binding and dynamics of hexapeptide substrates with the SARS-CoV-2 Mpro.
• To analyze substrate-induced conformational changes in Mpro using molecular dynamics simulations.
• To identify patterns in protein motion that can inform the design of Mpro inhibitors.

Main Methods:

• Construction of hexapeptide analogs using RDKit libraries.
• Molecular docking of peptides to the Mpro crystal structure (PDB ID 6XHM).
• Extensive molecular dynamics (MD) simulations (20 ns) of selected Lys-Leu-Gln*** (KLQ***) complexes.
• Analysis of MD trajectories using Principal Component Analysis (PCA) and a novel PCA comparison method.

Main Results:

• Hexapeptides formed stable complexes with Mpro, confirmed by reproducible docking.
• MD simulations and PCA revealed four distinct classifications of protein motions within KLQ*** complexes.
• Substrate variations significantly impacted Mpro's active site dynamics.
• A method for comparing PCA plots across different simulations was developed.

Conclusions:

• The study provides insights into substrate recognition mechanisms of SARS-CoV-2 Mpro.
• Observed protein dynamics highlight the influence of substrate sequence on Mpro active site behavior.
• Findings support the rational design of small molecule inhibitors targeting Mpro for COVID-19 treatment.