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Photochemical Approaches to Complex Chemotypes: Applications in Natural Product Synthesis

Open access
Kärkäs, Markus D., Porco, John A., Stephenson, Corey R. J.·2016·Chemical Reviews

Abstract

The use of photochemical transformations is a powerful strategy that allows for the formation of a high degree of molecular complexity from relatively simple building blocks in a single step. A central feature of all light-promoted transformations is the involvement of electronically excited states, generated upon absorption of photons. This produces transient reactive intermediates and significantly alters the reactivity of a chemical compound. The input of energy provided by light thus offers a means to produce strained and unique target compounds that cannot be assembled using thermal protocols. This review aims at highlighting photochemical transformations as a tool for rapidly accessing structurally and stereochemically diverse scaffolds. Synthetic designs based on photochemical transformations have the potential to afford complex polycyclic carbon skeletons with impressive efficiency, which are of high value in total synthesis.

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Metadata

Authors
Kärkäs, M. D., Porco, J. A., & Stephenson, C. R. J.
Venue
Chemical Reviews
Published
2016-04-27
Volume
116
Issue
17
Pages
9683-9747
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2342892827
Cited by
1,017
References
5
FWCI
2.91
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Photochemical Approaches to Complex Chemotypes: Applications in Natural Product Synthesis. https://app.cochat.ai/papers/10.1021/acs.chemrev.5b00760
The paper
Kärkäs, M. D., Porco, J. A., & Stephenson, C. R. J. (2016). Photochemical Approaches to Complex Chemotypes: Applications in Natural Product Synthesis. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.5b00760

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.