ArticleJournal of the American Chemical Society2019
Predictive Multivariate Linear Regression Analysis Guides Successful Catalytic Enantioselective Minisci Reactions of Diazines.
Article in Journal of the American Chemical Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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Who cites it
23 citing papers in PubMed.
- A machine learning-based workflow for transaminase selection.Chemical science · 2026Article
- Hepatotoxicity Evaluation of Levornidazole and Its Three Main Impurities: Based on Structure-Toxicity Classification Prediction Combined with Zebrafish Toxicity Assessment.Molecules (Basel, Switzerland) · 2025Article
- Article
- Photocatalytic Enantioselective Radical Cascade Multicomponent Minisci Reaction of β-Carbolines Using Diazo Compounds as Radical Precursors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Catalysing (organo-)catalysis: Trends in the application of machine learning to enantioselective organocatalysis.Beilstein journal of organic chemistry · 2024Review
- Fragment contribution models for predicting skin permeability using HuskinDB.Scientific data · 2023Article
- Discovery and Development of the Enantioselective Minisci Reaction.Accounts of chemical research · 2023Article
- Electrocatalyzed direct arene alkenylations without directing groups for selective late-stage drug diversification.Nature communications · 2023Article
- Photocatalytic enantioselective Minisci reaction of β-carbolines and application to natural product synthesis.Chemical science · 2023Article
- Enantioselective Giese Additions of Prochiral α-Amino Radicals.Journal of the American Chemical Society · 2022Article
- Noncovalent Stabilization of Radical Intermediates in the Enantioselective Hydroamination of Alkenes with Sulfonamides.Journal of the American Chemical Society · 2022Article
- Strategies That Utilize Ion Pairing Interactions to Exert Selectivity Control in the Functionalization of C-H Bonds.Journal of the American Chemical Society · 2022Review
- Hydrogen Atom Transfer Driven Enantioselective Minisci Reaction of Alcohols.Angewandte Chemie (International ed. in English) · 2022Article
- Evaluation guidelines for machine learning tools in the chemical sciences.Nature reviews. Chemistry · 2022Review
- Article
- Photons or Electrons? A Critical Comparison of Electrochemistry and Photoredox Catalysis for Organic Synthesis.Chemical reviews · 2022Review
- Identifying the true origins of selectivity in chiral phosphoric acid catalyzedChemical science · 2021Article
- Hydrogen Atom Transfer-Driven Enantioselective Minisci Reaction of Amides.Journal of the American Chemical Society · 2021Article
- Organic reactivity from mechanism to machine learning.Nature reviews. Chemistry · 2021Review
- Radical-Based Synthesis and Modification of Amino Acids.Angewandte Chemie (International ed. in English) · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The Minisci reaction is one of the most direct and versatile methods for forging new carbon-carbon bonds onto basic heteroarenes: a broad subset of compounds ubiquitous in medicinal chemistry. While many Minisci-type reactions result in new stereocenters, control of the absolute stereochemistry has proved challenging. An asymmetric variant was recently realized using chiral phosphoric acid catalysis, although in that study the substrates were limited to quinolines and pyridines. Mechanistic uncertainties and nonobvious enantioselectivity trends made the task of extending the reaction to important new substrate classes challenging and time-intensive. Herein, we describe an approach to address this problem through rigorous analysis of the reaction landscape guided by a carefully designed reaction data set and facilitated through multivariate linear regression (MLR) analysis. These techniques permitted the development of mechanistically informative correlations providing the basis to transfer enantioselectivity outcomes to new reaction components, ultimately predicting pyrimidines to be particularly amenable to the protocol. The predictions of enantioselectivity outcomes for these valuable, pharmaceutically relevant motifs were remarkably accurate in most cases and resulted in a comprehensive exploration of scope, significantly expanding the utility and versatility of this methodology. This successful outcome is a powerful demonstration of the benefits of utilizing MLR analysis as a predictive platform for effective and efficient reaction scope exploration across substrate classes.
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Registered trials
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