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A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis

preprint
submitted on 28.04.2021, 15:31 and posted on 27.04.2021, 14:22 by Tobias Gensch, Gabriel dos Passos Gomes, Pascal Friederich, Ellyn Peters, Theophile Gaudin, Robert Pollice, Kjell Jorner, AkshatKumar Nigam, Michael Lindner D'Addario, Matthew S. Sigman, Alan Aspuru-Guzik
The design of molecular catalysts typically involves reconciling multiple conflicting property requirements, largely relying on human intuition and local structural searches. However, the vast number of potential catalysts requires pruning of the candidate space by efficient property prediction with quantitative structure-property relationships. Data-driven workflows embedded in a library of potential catalysts can be used to build predictive models for catalyst performance and serve as a blueprint for novel catalyst designs. Herein we introduce kraken, a discovery platform covering monodentate organophosphorus(III) ligands providing comprehensive physicochemical descriptors based on representative conformer ensembles. Using quantum-mechanical methods, we calculated descriptors for 1,558 ligands, including commercially available examples, and trained machine learning models to predict properties of over 300,000 new ligands. We demonstrate the application of kraken to systematically explore the property space of organophosphorus ligands and how existing datasets in catalysis can be used to accelerate ligand selection during reaction optimization.

Funding

Natural Sciences and Engineering Research Council of Canada for Banting Fellowship

Leopoldina Fellowship Programme of the German National Academy of Sciences Leopoldina (LPDS 2017−18)

Defense Advanced Research Projects Agency (DARPA) under the Accelerated Molecular Discovery Program under Cooperative Agreement No. HR00111920027 dated August 1, 2019

Natural Resources Canada

Canada 150 Research Chair

US National Science Foundation CCI Center for Computer Assisted Synthesis (CHE-1925607)

History

Email Address of Submitting Author

gabriel.gomes@utoronto.ca

Institution

University of Toronto, University of Utah, TU Berlin, KIT

Country

Canada

ORCID For Submitting Author

0000-0002-8235-5969

Declaration of Conflict of Interest

A.A.-G. is a co-founder and the Chief Visionary Officer at Kebotix Inc.

Version Notes

Version 1.0, pre-journal submission.

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