Significant progress in chemical shift prediction has been made through continuous improvements in our understanding of the key physico-chemical factors contributing to chemical shift changes.  These improvements have also been helped along through significant computational advancements 
 and the rapid expansion of biomolecular chemical shift databases 
.  Over the past four decades, at least three different methods for calculating or predicting protein chemical shifts have emerged. The first is based on using sequence/structure alignment against protein chemical shift databases, the second is based on directly calculating shifts from atomic coordinates, and the third is based on using a combination of the two approaches. 
*Predicting shifts via sequence homology: these are based on the simple observation that similar protein sequences share similar structures and similar chemical shifts
*Predicting shifts from coordinate data / structure: 
**Semi-classical methods: employ empirical equations derived from classical physics and experimental data
**Quantum mechanical (QM) methods:  employ density functional theory (DFT)
**Empirical methods: rely on using chemical shift ‘‘hypersurfaces" or related "structure/shift" tables
*Hybrid Methods: combining the above two methods