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.