Computational approach for ranking mutant enzymes according to catalytic reaction rates.

A computationally efficient approach for ranking mutant enzymes according to the catalytic reaction rates is presented. This procedure requires the generation and equilibration of the mutant structures, followed by the calculation of partial free energy curves using an empirical valence bond potential in conjunction with biased molecular dynamics simulations and umbrella integration. The individual steps are automated and optimized for computational efficiency. This approach is used to rank a series of 15 dihydrofolate reductase mutants according to the hydride transfer reaction rate. The agreement between the calculated and experimental changes in the free energy barrier upon mutation is encouraging. The computational approach predicts the correct direction of the change in free energy barrier for all mutants, and the correlation coefficient between the calculated and experimental data is 0.82. This general approach for ranking protein designs has implications for protein engineering and drug design.