Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with Application to Chemical Shift Predictions

Full-protein
nuclear magnetic resonance (NMR) shielding constants
based on ab initio calculations are desirable, because
they can assist in elucidating protein structures from NMR experiments.
In this work, we present NMR shielding constants computed using a
new automated fragmentation (J. Phys. Chem. B 2009, 113, 10380–10388) approach in
the framework of polarizable embedding density functional theory.
We extend our previous work to give both basis set recommendations
and comment on how large the quantum mechanical region should be to
successfully compute 13C NMR shielding constants that are
comparable with experiment. The introduction of a probabilistic linear
regression model allows us to substantially reduce the number of snapshots
that are needed to make comparisons with experiment. This approach
is further improved by augmenting snapshot selection with chemical
shift predictions by which we can obtain a representative subset of
snapshots that gives the smallest predicted error, compared to experiment.
Finally, we use this subset of snapshots to calculate the NMR shielding
constants at the PE-KT3/pcSseg-2 level of theory for all atoms in
the protein GB3.