Molecular docking simulations and free energy perturbation methods (e.g., MM/PBSA, MM/GBSA) are employed to estimate G_bind across sequence variants.
Within our CAS-based framework, these values are dynamically assigned to nodes in the mutation network as evolving scalar fields.
Mutants with similar folding topologies may exhibit nonlinear binding shifts, especially when conformational entropy changes or cryptic binding pockets emerge---reflecting bifurcation events in structure-function space.
Network-Integrated Representation:
The graph node associated with each variant is annotated with its G_bind.
Clusters of low-binding-energy nodes indicate functional basins---regions of mutational space with high affinity potential.
Gradient descent or reinforcement strategies in this landscape can then be used to guide synthetic evolution toward high-affinity variants.
2. Catalytic Efficiency (k_cat/K_m)
Catalytic efficiency integrates two kinetic parameters:
Turnover number (k_cat): How fast the enzyme converts substrate to product.
Michaelis constant (K_m): The substrate concentration at which the reaction rate is half-maximal.
