Statistical crystallography reveals an allosteric network in SARS-CoV-2 M^pro

Area of Science:

• Biochemistry
• Structural Biology
• Crystallography

Background:

• Proteins utilize correlated motions to interpret and transmit biological signals.
• Experimental determination of protein dynamics and their resulting structural distributions is challenging.
• The SARS-CoV-2 main protease (Mpro) is a key enzyme regulated by dimerization for activity.

Purpose of the Study:

• To model the structural fluctuations of SARS-CoV-2 Mpro.
• To understand the structural changes linking Mpro dimerization to catalytic activation.
• To identify regions critical for Mpro catalytic function through correlation analysis.

Main Methods:

• Statistical crystallography analyzing 1146 crystal structures of SARS-CoV-2 Mpro.
• Computational modeling to infer enzyme structural fluctuations and correlations.
• Site-directed mutagenesis and biophysical experiments to validate predictions.

Main Results:

• A model of Mpro structural fluctuations was inferred from extensive crystallographic data.
• Specific regions in the dimerization domain were found to be structurally correlated with the active site.
• Mutations at correlated positions differentially affected Mpro catalytic activity, validating the model.

Conclusions:

• Statistical crystallography is a powerful approach to study protein dynamics in native states.
• Understanding Mpro structural dynamics provides insights into its regulation and function.
• This method can uncover the biological function of proteins by revealing their inherent structural fluctuations.