Neural Networks for the Prediction of Organic Chemistry Reactions

Wei, Jennifer N.Duvenaud, DavidAspuru-Guzik, Alan2016-11-182016Wei, Jennifer N., David Duvenaud, and Alán Aspuru-Guzik. 2016. “Neural Networks for the Prediction of Organic Chemistry Reactions.” ACS Central Science 2 (10): 725-732. doi:10.1021/acscentsci.6b00219. http://dx.doi.org/10.1021/acscentsci.6b00219.2374-7943http://nrs.harvard.edu/urn-3:HUL.InstRepos:29408397Reaction prediction remains one of the major challenges for organic chemistry and is a prerequisite for efficient synthetic planning. It is desirable to develop algorithms that, like humans, “learn” from being exposed to examples of the application of the rules of organic chemistry. We explore the use of neural networks for predicting reaction types, using a new reaction fingerprinting method. We combine this predictor with SMARTS transformations to build a system which, given a set of reagents and reactants, predicts the likely products. We test this method on problems from a popular organic chemistry textbook.en-USNeural Networks for the Prediction of Organic Chemistry ReactionsJournal Article2016-11-1810.1021/acscentsci.6b00219