Abstract

AbstractThis invited Team Profile was created by the List and Varnek groups at the Institute of Chemical Reaction Design and Discovery (ICReDD), Hokkaido University (Japan), Max‐Planck‐Institut für Kohlenforschung (Germany), and University of Strasbourg (France). They recently published an article on fast and robust predictive models using tunable 2D fragment descriptors, particularly suited for asymmetric catalysis. From training data with only moderate selectivities, highly enantioselective catalysts were predicted and validated, enabling a catalytic asymmetric construction of 2,2‐disubstituted tetrahydropyrans. “Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors”, N. Tsuji, P. Sidorov, C. Zhu, Y. Nagata, T. Gimadiev, A. Varnek, B. List, Angew. Chem. Int. Ed. 2023, e202218659.

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