Kinetic models are important tools for guiding the design and optimization of lipase-catalyzed processes. These processes follow the Ping Pong bi bi mechanism, for which mechanistic kinetic equations can be derived. However, when there are several competing reactions, fully mechanistic models contain a large number of parameters, making it difficult to obtain reliable estimates, so simplified models are necessary. We present a two-step approach to developing semi-mechanistic models of such processes. The first step involves the estimation of the selectivities of the enzyme, using profiles for the reaction species plotted against the degree of reaction, while the second step involves empirical fitting to the same data, but plotted as a function of time. We demonstrate this two-step approach through four case studies based on the literature data for the lipase-catalyzed esterification of fatty acids with trimethylolpropane to produce biolubricants. The semi-mechanistic models were able to describe the data well. Our approach has the advantage of allowing selectivities to be estimated without confounding effects from phenomena such as enzyme denaturation and inhibition. It therefore provides a promising framework for developing models of enzyme-catalyzed processes that obey Ping Pong bi bi kinetics.
Nishimura et al. (2026) studied this question.