New approach to the evaluation of lignocellulose derived by-products impact on lytic-polysaccharide monooxygenase activity by using molecular descriptor structural causality model

Lytic-polysaccharide monooxygenase (LPMO) is one of the most important enzyme involved in biocatalytic lignocellulose degradation, and therefore inhibition of LPMO has significant effects on all related processes. Structural causality model (SCM) were established to evaluate impact of phenolic by-products in lignocellulose hydrolysates on LPMO activity. The molecular descriptors GATS4c, ATS2m, BIC3 and VR2_Dzs were found to be significant in describing inhibition. The causalities of the molecular descriptors and LPMO activity are determined by evaluating the directed acyclic graph (DAG) and the d-separation algorithm. The maximum causality for LPMO activation is beta = 0.79 by BIC3 and the maximum causality of inhibition is beta = -0.56 for the GATS4c descriptor. The model has the potential to predict the inhibition of LPMO and its application could be useful in selecting an appropriate lignocellulose pretreatment method to minimise the production of a potent inhibitor. This will subsequently lead to more efficient lignocellulose degradation process.

Automated summary

The study established a structural causality model to evaluate the impact of phenolic by-products in lignocellulose hydrolysates on LPMO activity, with key molecular descriptors helping to describe inhibition and determine causality through directed acyclic graph and d-separation algorithm. The maximum causality for LPMO activation is beta = 0.79, while the maximum causality for inhibition is beta = -0.56, indicating the potential of the model in predicting LPMO inhibition and guiding the selection of suitable pretreatment methods.