Controlling Stereoselectivity with Noncovalent Interactions in Chiral Phosphoric Acid Organocatalysis
Bibliographic record
Abstract
Chiral phosphoric acids (CPAs) have emerged as highly effective Brønsted acid catalysts in an expanding range of asymmetric transformations, often through novel multifunctional substrate activation modes. Versatile and broadly appealing, these catalysts benefit from modular and tunable structures, and compatibility with additives. Given the unique types of noncovalent interactions (NCIs) that can be established between CPAs and various reactants─such as hydrogen bonding, aromatic interactions, and van der Waals forces─it is unsurprising that these catalyst systems have become a promising approach for accessing diverse chiral product outcomes. This review aims to provide an in-depth exploration of the mechanisms by which CPAs impart stereoselectivity, positioning NCIs as the central feature that connects a broad spectrum of catalytic reactions. Spanning literature from 2004 to 2024, it covers nucleophilic additions, radical transformations, and atroposelective bond formations, highlighting the applicability of CPA organocatalysis. Special emphasis is placed on the structural and mechanistic features that govern CPA-substrate interactions, as well as the tools and techniques developed to enhance our understanding of their catalytic behavior. In addition to emphasizing mechanistic details and stereocontrolling elements in individual reactions, we have carefully structured this review to provide a natural progression from these specifics to a broader, class-level perspective. Overall, these findings underscore the critical role of NCIs in CPA catalysis and their significant contributions to advancing asymmetric synthesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".