Assessing the Accuracy of Across-the-Scale Methods for Predicting Carbohydrate Conformational Energies for the Examples of Glucose and α‑Maltose

A big
hurdle when entering the field of carbohydrate research stems
from the complications in the analytical and computational treatment.
In effect, this extremely important class of biomolecules remains
underinvestigated when compared, for example, with the maturity of
genomics and proteomics research. On the theory side, the commonly
used empirical methods suffer from an insufficient amount of high-quality
experimental data against which they can be thoroughly validated.
In order to provide a pivotal point for an ascent of accurate carbohydrate
simulations, we present here a structure/energy benchmark set of diverse
glucose (in three isomeric forms) and α-maltose conformations
at the coupled-cluster level as well as an assessment of commonly
used energy functions. We observe that empirical force fields and
semiempirical approaches, on average, do not reproduce accurately
the reference energy hierarchies. While the force fields maintain
accuracy for the low-energy structures, the semiempirical methods
perform unsatisfactory for the entire range. On the contrary, density-functional
approximations reproduce the reference energy hierarchies with better
than chemical accuracy already at the generalized gradient approximation
level (GGA). Particularly, the novel meta-GGA functional SCAN provides
the accuracy of more expensive hybrid functionals at fraction of their
computational cost. In conclusion, we advocate for electronic-structure
theory methods to become the routine tool for simulations of carbohydrates.