Is density functional theory accurate for lytic polysaccharide monooxygenase enzymes?

TL;DR

This study evaluates the accuracy of density functional theory (DFT) in predicting spin-state splittings in key intermediates of LPMO enzymes, comparing DFT results with more accurate CASPT2 calculations to address known limitations.

Contribution

The paper provides a systematic assessment of DFT's reliability for modeling spin states in LPMO enzyme intermediates, highlighting its limitations and the need for careful functional selection.

Findings

DFT shows large variations in spin-state predictions.

CASPT2 serves as a reliable reference for spin states.

Results suggest caution when using DFT for transition-metal enzyme studies.

Abstract

The lytic polysaccharide monooxygenase (LPMO) enzymes boost polysaccharide depolymerization through oxidative chemistry, which has fueled the hope for more energy-efficient production of biofuel. We have recently proposed a mechanism for the oxidation of the polysaccharide substrate (Hedeg{\aa}rd & Ryde, Chem. Sci. 2018, 9, 3866). In this mechanism, complexes with superoxide, oxyl, as well as hydroxyl (i.e. [CuO2]+, [CuO]+ and [CuOH]2+) cores were involved. These complexes can have both singlet and triplet spin states, and both spin-states may be important for how LPMOs function during catalytic turnover. Previous calculations on LPMOs have exclusively been based on density functional theory (DFT). However, different DFT functionals are known to display large differences for spin-state splittings in transition-metal complexes, and this has also been an issue for LPMOs. In this paper, we study the accuracy of DFT for spin-state splittings in superoxide, oxyl, and hydroxyl intermediates involved in LPMO turnover. As reference we employ multiconfigurational perturbation theory (CASPT2).