text: 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