Predicting and improving lignin depolymerization processes with coupled graph modeling and kinetic Monte Carlo simulation

Lignin depolymerization offers a promising route to renewable aromatics, but our understanding of this process is limited by the large mismatch between model compound kinetics and the behavior of the real polymer. Here, we use computationally generated lignin populations and a kinetic Monte Carlo framework to capture the hydrogenolysis of real lignin using model compound kinetic parameters. Our simulations show that model compounds can reflect real lignin behavior, but only when the stochastic nature of lignin is accurately captured. We confirm the importance of free phenolic structures, which largely control depolymerization rates and favour an unzipping mechanism. Specific interunit C C linkages, although not cleaved, appeared to significantly accelerate depolymerization because of their free phenolic nature, as confirmed with an Arabidopsis thaliana mutant enriched in C–C-associated free phenolic linkages that depolymerized faster than the wildtype. This approach offers a foundation for better controlled lignin depolymerization and rational lignin design.