Optimal kinetics for catalytic cycles from a single path-sampling simulation

Area of Science:

• Computational Chemistry
• Catalysis Science
• Chemical Kinetics

Background:

• Catalyst efficiency is dictated by molecular structure and substrate interactions.
• Optimizing catalytic cycles for desired kinetics is computationally intensive, especially in solvated systems.

Purpose of the Study:

• To develop an efficient computational method for optimizing catalytic cycles.
• To demonstrate the capability of path reweighting for tuning catalyst parameters and understanding rate optimization mechanisms.

Main Methods:

• Application of a maximum caliber based path reweighting method.
• Performing a single path-sampling simulation to generate a path ensemble.
• Expanding the kinetic landscape around a single parameter setting.

Main Results:

• Achieved orders of magnitude improvement in catalytic turnover and efficiency.
• Identified optimal parameters that induce strain in the system.
• Revealed mechanistic origins of rate optimization.

Conclusions:

• Path-reweighting based optimization offers a cost-effective approach for designing efficient catalysts.
• The methodology is versatile and applicable to complex systems, such as kinase signaling.
• This approach promises efficient computational design of catalysts using realistic molecular models.