Toward in silico Catalyst Optimization

Authors

  • Matthew D. Wodrich Laboratory of Computational Molecular Design, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, https://orcid.org/0000-0002-6006-671X
  • Rubén Laplaza Laboratory of Computational Molecular Design, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, https://orcid.org/0000-0001-6315-4398
  • Nicolai Cramer Laboratory of Asymmetric Synthesis and Catalysis , Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne https://orcid.org/0000-0001-5740-8494
  • Markus Reiher Laboratorium für Physikalische Chemie, ETH Zürich, Vladimir-Prelog-Weg 2, CH-8093 Zürich https://orcid.org/0000-0002-9508-1565
  • Clemence Corminboeuf Laboratory of Computational Molecular Design, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne https://orcid.org/0000-0001-7993-2879

DOI:

https://doi.org/10.2533/chimia.2023.139

PMID:

38047817

Keywords:

Computational chemistry, Enantioselectivity, Homogeneous catalysis, Transition metals

Abstract

In this minireview, we overview a computational pipeline developed within the framework of NCCR Catalysis that can be used to successfully reproduce the enantiomeric ratios of homogeneous catalytic reactions. At the core of this pipeline is the SCINE Molassembler module, a graph-based software that provides algorithms for molecular construction of all periodic table elements. With this pipeline, we are able to simultaneously functionalizenand generate ensembles of transition state conformers, which permits facile exploration of the influencenof various substituents on the overall enantiomeric ratio. This allows preconceived back-of-the-envelope designnmodels to be tested and subsequently refined by providing quick and reliable access to energetically low-lyingntransition states, which represents a key step in undertaking in silico catalyst optimization.

Funding data

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Published

2023-03-29

How to Cite

[1]
M. D. Wodrich, R. Laplaza, N. Cramer, M. Reiher, C. Corminboeuf, Chimia 2023, 77, 139, DOI: 10.2533/chimia.2023.139.

Issue

Section

Scientific Articles