Designer substrate library for quantitative, predictive modeling of reaction performance
Abstract
Product distributions of chemical reactions are dictated by a myriad of interactions between molecular species. Identifying which of these features affects reaction selectivity is a key facet for mechanistically understanding a transformation. Such insight often facilitates optimization as well as indicates which types of substrates (substrate scope) are well suited to the method. Unfortunately, the assessment of impactful features is frequently a qualitative endeavor that would significantly benefit from quantitation. We demonstrate a robust method for developing a varied substrate scope library of ketones, identifying quantitative descriptors of mechanistic significance, and applying these descriptors to mathematically elucidate trends in enantioselective reaction outcomes of rhodium-catalyzed asymmetric transfer hydrogenation. The developed mathematical relationships were used to predict future outcomes of new ketone substrates.
- Publication:
-
Proceedings of the National Academy of Science
- Pub Date:
- October 2014
- DOI:
- 10.1073/pnas.1409522111
- Bibcode:
- 2014PNAS..11114698B