The COVID-19 pandemic, caused by SARS-CoV-2, has had a major global impact. The virus’s main protease (Mpro) is a key enzyme in its life cycle, playing a critical role in viral replication and transcription, which makes it a promising target for therapeutic intervention. To better understand how ligand binding affects the function of SARS-CoV-2 Mpro, I applied elastic network models to investigate its conformational flexibility and gain insights into the underlying protein dynamics.
Elastic Network Models (ENMs) represent proteins as particles connected by springs based on a reference structure. Coarse-grained ENMs typically use one particle per amino acid (α-carbon), with connections determined by a distance cutoff. There are two ways in which ENMs are commonly represented and analyzed: Gaussian Network Model and Anisotropic Network Model.
The Gaussian Network Model (GNM) examines protein flexibility by measuring the magnitude of atomic fluctuations, giving an overall view of how the molecule moves. In contrast, the Anisotropic Network Model (ANM) considers both the magnitude and direction of movements, providing a more detailed picture of protein dynamics. While GNM shows how much parts of the protein move, ANM shows how they move.
Elastic network models help identify hinge regions, which are flexible areas around which protein domains rotate, and rigid parts that remain stable. These rotations are important during molecular binding, activation, or deactivation, making hinge regions structurally significant for coordinated protein motions and their functional roles.