Screening for Generality in Asymmetric Catalysis

Abstract

Research in the field of asymmetric catalysis over the past half century has resulted in landmark advances, enabling the efficient synthesis of chiral building blocks, pharmaceuticals, and natural products. A small number of asymmetric catalytic reactions have been identified that display high selectivity across a broad scope of substrates; not coincidentally, these are the reactions that have the greatest impact on how enantioenriched compounds are synthesized. We postulate that substrate generality in asymmetric catalysis is rare not simply because it is intrinsically difficult to achieve, but also because of the way chiral catalysts are identified and optimized. Typical discovery campaigns rely on a single model substrate, and thus select for high performance in a narrow region of chemical space. Here, we put forth a practical approach for using multiple model substrates to select simultaneously for both enantioselectivity and generality in asymmetric catalysis from the outset. Multisubstrate screening is achieved by conducting high-throughput chiral analyses via supercritical fluid chromatography-mass spectrometry (SFC-MS) with pooled samples. When applied to Pictet–Spengler reactions, the multi-substrate screening approach revealed a promising and unexpected lead for the general enantioselective catalysis of this important transformation.

Generality-Oriented Optimization of Enantioselective Aminoxyl Radical Catalysis

“…1A). 4 To address the limited transferability frequently encountered in asymmetric catalysis, we envisioned an optimization strategy with generality as the primary target in catalyst development. This strategy requires parallel screening of a large, diverse catalyst library against a judiciously selected panel of model substrates that represent the chemical space of the target substrate class, rather than a singular substrate.…”

Rapid Planning and Analysis of High-Throughput Experiment Arrays for Reaction Discovery

“…Miniaturized high-throughput experimentation (HTE) has emerged as an accessible, reliable, economical, and environmentally friendly technique for the rapid discovery of new reactivities. Curated HTE data proves to be increasingly valuable for predictive models, [15][16][17][18][19][20] While in experimental practice, the community has gravitated towards liquid handling techniques in glass shell microvials with tumble stir dowels, or in plastic 384 or 1,536 wellplates 1,[4][5][6][7][8][9][10][11][12][13][14] , a standard for HTE data handling has yet to be established. The organizational load required to perform a simple 24-well reaction array is generally manageable by repetitive notebook entries or with spreadsheets, yet managing multiple reaction arrays in a single day, or running ultraHTE in 1,536 wellplates, 1 is challenging without information management software.…”

A Statistical Modeling Approach to Catalyst Generality Assessment in Enantioselective Synthesis

“…2 Hence, the ability to identify general enantioselective catalysts is both necessary and difficult. 3,4 Forecasting the suitability of an asymmetric catalyst for a particular reaction system is challenging as the optimal molecular features for one transformation do not always translate to another. 5 Furthermore, catalysts that are currently considered as the most "general" may be biased by the existing literature.…”