Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
Computational models that predict the selectivity of reactions are typically accurate for only a specific reaction type and a narrow range of reaction components. A more general model has now been reported.
Selectivity is a linchpin of chemical synthesis — if a synthetic reaction is not selective, it cannot give a good yield of the desired product, and will require tedious purification processes. Chemists have therefore long sought ways of predicting the selectivity of chemical reactions. Computational models can be constructed, but their development is laborious, and they are usually specific to a particular reaction type. Writing in Nature, Reid and Sigman1 now show that a selectivity model can be built in a semi-automated way and generalized over a range of reactions.