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Conformational Changes in SARS-CoV-2 Main Protease Induced by Ligand Binding: A Comprehensive Analysis by Elastic Network Models
- The SARS-CoV-2 main protease (Mpro) is the Achilles' heel of the virus, playing a critical role in its replication and making it a prime target for new antiviral therapies. My project investigated a fundamental question: how does a drug candidate (ligand) influence the structural flexibility of this essential enzyme?
- To this end, we utilized Elastic Network Models (ENMs) alongside extensive literature analysis to capture Mpro's dynamic "dance" in motion. This powerful computational approach allowed us to gain a deeper understanding of its behavior.
Specifically, we were able to:
- Map the enzyme's structural flexibility and identify the precise amino acid residues that act as hinge points, allowing the protein to change shape.
- Uncover crucial clues about allosteric regulation, where binding at one distant site can dramatically influence the enzyme's activity at its active center.
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 models (GNM) and anisotropic network models (ANM).