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Van 't Hoff Institute for Molecular Sciences Van 't Hoff Institute for Molecular Sciences

Efficient computational optimisation of catalysis kinetics

12 August 2025

A novel approach in computational chemistry allows for the efficient determination of optimal kinetics for catalytic cycles. In a recent paper in PNAS, Prof. Peter Bolhuis of the Van ‘t Hoff Institute for Molecular Sciences describes how a single path-sampling simulation can establish optimal interaction parameters for catalytic conversion. Focussing on simple models for minimal catalytic cycles, the research opens up future avenues for addressing catalyst optimization and design.

Catalysis plays an important role in many fields, from industrial chemistry to the molecular biology of the cell. The efficiency of a catalyst for accelerating a reaction strongly depends on its molecular structure and interactions with the substrate. In principle, given a particular molecular interaction model, one could predict kinetics of a catalytic cycle and, by extension, provide optimal interaction parameters.

However, this is usually considered computationally prohibitively expensive, in particular for solvated catalytic systems such as enzymes and DNA-decorated colloidal particles. While for gas phase reactions quantum chemistry provides accurate predictions, condensed-phase (solvated) reactions, and in general reactions in high-dimensional systems, require a dynamical approach. This renders computation exceptionally expensive, even when considering simplified classical molecular models.

Improving the catalytic turnover by orders of magnitude

In the PNAS paper, Bolhuis describes how an inverse design approach (see figure) employing a novel path reweighting method offers a way out of this computational conundrum.

Pipeline of inverse kinetic design. Traditionally, forward design operates from right to left, predicting the properties of the catalytic cycle from the interactions. Instead, the new approach turns this around by looking for the interactions that give the desired efficiency, symbolically indicated by the blue arrows. At the heart of the approach is a reweighting method of the ensemble of dynamical trajectories, which hugely speeds up the computations. Image: HIMS

The approach features computing the ensemble of trajectories using molecular dynamics for a single parameter setting of the molecular interactions and then expanding the kinetic landscape around these parameters. As a result, it becomes possible to improve the optimal catalytic turnover by orders of magnitude in one single simulation.

Efficient computational design

The versatility of the methodology was showcased on minimal models for dimerization and kinase signalling, highlighting its potential for efficient computational design of complex catalysts using more realistic models. Since the methodology is capable of identifying the effect of each model parameter, the approach can be used to improve on such molecular models, e. g. by suggesting mutations or substitution of functional groups. For instance, in the kinase model the location of the binding site might be altered through protein engineering. Bolhuis envisions that path reweighting techniques will become part of the molecular simulation toolbox in the near future.

Paper details

Peter G. Bolhuis: Optimal kinetics for catalytic cycles from a single path-sampling simulation. Proc. Natl. Acad. Sci. U.S.A. 122 (30) e2500934122 (2025). DOI: 10.1073/pnas.2500934122

See also

Research Peter Bolhuis