When it comes to prediction of chemical shifts in proteins the most widely used functional appears to be B3LYP \cite{Becke_1993}. For example, Zhu, He and Zhang \cite{Zhu_2012} used B3LYP/6-31G(d,p) to compute hydrogen and carbon chemical shifts for small proteins that correlate well with experimental measurements with \(r\) values typically ≥ 0.98 when solvent effects are taken into account. Exner, Möller, and co-workers \cite{Exner_2012} have obtained similar results using B3LYP/6-31G(d) and even observed a correlation of 0.81 for the notoriously difficult amide N by averaging over several snapshots. Finally, Vila, Baldoni and Scheraga \cite{Vila_2009} did a systematic study of the effect of 10 functionals on C\(\alpha\) chemical shifts in Ubiquitin and found very little difference in performance with all \(r\) and RMSD values in the range 0.902 – 0.908 and 2.12 – 2.30 ppm. Interestingly, this study included functionals such as OPBE that are computationally less demanding than B3LYP. Vila, Scheraga and co-workers \cite{19805131} subsequently observed that C\(\alpha\) chemical shifts computed using smaller basis sets such as 6-31G correlate extremely well the chemical shifts computed using lager basis set such as 6-311+G(2d,p). We therefore decided to use the 6-31G(d,p) basis for our calculations and use the computationally efficient OPBE functional.