Nontraditional Fragment Couplings of Alcohols and Carboxylic Acids: C(sp³)–C(sp³) Cross-Coupling via Radical Sorting

Journal of the American Chemical Society, Journal Year: 2022, Volume and Issue: 144(14), P. 6185 - 6192

Published: March 30, 2022

Alcohols and carboxylic acids are among the most commercially abundant, synthetically versatile, operationally convenient functional groups in organic chemistry. Under visible light photoredox catalysis, these native synthetic handles readily undergo radical activation, resulting open-shell intermediates can subsequently participate transition metal catalysis. In this report, we describe C(sp3)–C(sp3) cross-coupling of alcohols through dual combination N-heterocyclic carbene (NHC)-mediated deoxygenation hypervalent iodine-mediated decarboxylation. This mild practical Ni-catalyzed radical-coupling protocol was employed to prepare a wide array alkyl–alkyl cross-coupled products, including highly congested quaternary carbon centers from corresponding tertiary or acids. We demonstrate applications methodology alcohol C1-alkylation formal homologation, as well late-stage functionalization drugs, natural biomolecules.

Language: Английский

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Metallaphotoredox catalysis for sp³C–H functionalizations through hydrogen atom transfer (HAT)

Chemical Society Reviews, Journal Year: 2023, Volume and Issue: 52(12), P. 4099 - 4120

Published: Jan. 1, 2023

sp 3 C–H functionalizations under the combination of photocatalytic HAT and transition metal catalysis.

Language: Английский

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Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

Chemical Science, Journal Year: 2022, Volume and Issue: 14(2), P. 226 - 244

Published: Nov. 28, 2022

This review outlines several organic chemistry tasks for which predictive machine learning models have been and can be applied.

Language: Английский

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On the use of real-world datasets for reaction yield prediction

Chemical Science, Journal Year: 2023, Volume and Issue: 14(19), P. 4997 - 5005

Published: Jan. 1, 2023

The lack of publicly available, large, and unbiased datasets is a key bottleneck for the application machine learning (ML) methods in synthetic chemistry. Data from electronic laboratory notebooks (ELNs) could provide less biased, large datasets, but no such have been made available. first real-world dataset ELNs pharmaceutical company disclosed its relationship to high-throughput experimentation (HTE) described. For chemical yield predictions, task synthesis, an attributed graph neural network (AGNN) performs as well or better than best previous models on two HTE Suzuki-Miyaura Buchwald-Hartwig reactions. However, training AGNN ELN does not lead predictive model. implications using data ML-based are discussed context predictions.

Language: Английский

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Synthetic Applications of Photocatalyzed Halogen‐Radical Mediated Hydrogen Atom Transfer for C−H Bond Functionalization

European Journal of Organic Chemistry, Journal Year: 2022, Volume and Issue: 2022(34)

Published: May 13, 2022

Abstract The opportunity to activate C(sp 3 )−H bonds via homolytic cleavage by means of halogen radicals has long been disregarded in synthetic endeavors due the unpredictable selectivity. Nowadays, photocatalysis established itself as a method choice for generation such reactive intermediates under mild conditions. This Minireview collects recent examples showcasing how photocatalytic manifolds have used tame aggressive Hydrogen Atom Transfer (HAT) purposes. In last section this work, we address site‐selectivity issues posed methodology and show it can be guided through judicious reaction

Language: Английский

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Site- and enantioselective cross-coupling of saturated N-heterocycles with carboxylic acids by cooperative Ni/photoredox catalysis

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Jan. 9, 2023

Abstract Site- and enantioselective cross-coupling of saturated N -heterocycles carboxylic acids—two the most abundant versatile functionalities—to form pharmaceutically relevant α-acylated amine derivatives remains a major challenge in organic synthesis. Here, we report general strategy for highly site- α-acylation with situ-activated acids. This modular approach exploits hydrogen-atom-transfer reactivity photocatalytically generated chlorine radicals combination asymmetric nickel catalysis to selectively functionalize cyclic α-amino C−H bonds presence benzylic, allylic, acyclic α-amino, α-oxy methylene groups. The mild scalable protocol requires no organometallic reagents, displays excellent chemo-, enantioselectivity, is amenable late-stage diversification, including synthesis previously inaccessible Taxol derivatives. Mechanistic studies highlight exceptional versatility chiral catalyst orchestrating (i) catalytic elimination, (ii) alkyl radical capture, (iii) cross-coupling, (iv) induction.

Language: Английский

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Strategies for Nucleophilic C(sp³)–(Radio)Fluorination

Journal of the American Chemical Society, Journal Year: 2023, Volume and Issue: 145(18), P. 9928 - 9950

Published: April 24, 2023

This Perspective surveys the progress and current limitations of nucleophilic fluorination methodologies. Despite long rich history C(sp3)–F bond construction in chemical research, inherent challenges associated with this transformation have largely constrained to a privileged reaction platform. In recent years, Doyle group─along many others─has pursued study development intent generating deeper mechanistic understanding, developing user-friendly reagents, contributing invention synthetic methods capable enabling radiofluorination. Studies from our laboratory are discussed along developments others field. Fluoride reagent implications identity highlighted. We also outline space inaccessible by technologies series future directions field that can potentially fill existing dark spaces.

Language: Английский

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Interrogating the Mechanistic Features of Ni(I)-Mediated Aryl Iodide Oxidative Addition Using Electroanalytical and Statistical Modeling Techniques

Journal of the American Chemical Society, Journal Year: 2023, Volume and Issue: 145(15), P. 8689 - 8699

Published: April 4, 2023

While the oxidative addition of Ni(I) to aryl iodides has been commonly proposed in catalytic methods, an in-depth mechanistic understanding this fundamental process is still lacking. Herein, we describe a detailed study using electroanalytical and statistical modeling techniques. Electroanalytical techniques allowed rapid measurement rates for diverse set iodide substrates four classes catalytically relevant complexes (Ni(MeBPy), Ni(MePhen), Ni(Terpy), Ni(BPP)). With >200 experimental rate measurements, were able identify essential electronic steric factors impacting through multivariate linear regression models. This led classification mechanisms, either three-center concerted or halogen-atom abstraction pathway based on ligand type. A global heat map predicted was created shown applicable better reaction outcome case Ni-catalyzed coupling reaction.

Language: Английский

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Generality-oriented optimization of enantioselective aminoxyl radical catalysis

Science, Journal Year: 2023, Volume and Issue: 380(6646), P. 706 - 712

Published: May 18, 2023

Catalytic enantioselective methods that are generally applicable to a broad range of substrates rare. We report strategy for the oxidative desymmetrization

Language: Английский

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Predicting success in Cu-catalyzed C–N coupling reactions using data science

Science Advances, Journal Year: 2024, Volume and Issue: 10(3)

Published: Jan. 17, 2024

Data science is assuming a pivotal role in guiding reaction optimization and streamlining experimental workloads the evolving landscape of synthetic chemistry. A discipline-wide goal development workflows that integrate computational chemistry data tools with high-throughput experimentation as it provides experimentalists ability to maximize success expensive campaigns. Here, we report an end-to-end data-driven process effectively predict how structural features coupling partners ligands affect Cu-catalyzed C–N reactions. The established workflow underscores limitations posed by substrates while also providing systematic ligand prediction tool uses probability assess when will be successful. This platform strategically designed confront intrinsic unpredictability frequently encountered deployment.

Language: Английский

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