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MLQM_selectivity_preprint_manuscript.pdf (2.44 MB)

Regio-Selectivity Prediction with a Machine-Learned Reaction Representation and On-the-Fly Quantum Mechanical Descriptors

submitted on 02.09.2020 and posted on 03.09.2020 by Yanfei Guan, Connor Coley, Haoyang wu, Duminda Ranasinghe, esther heid, Thomas J. Struble, Lagnajit Pattanaik, William H. Green, Klavs F. Jensen

We introduce a new method that combines machine-learned reaction representation with selected quantum mechanical descriptors to predict regio-selectivity in general substitution reactions. We construct a reactivity descriptor database based on ab initio calculations of 130k organic molecules, and train a multi-task constrained model to calculate demanded descriptors on-the-fly.


Email Address of Submitting Author


Massachusetts Institute of Technology


United States

ORCID For Submitting Author


Declaration of Conflict of Interest

There are no conflicts to declare