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Cited by 276

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

A Library of Spirooxindoles Based on a Stereoselective Three-Component Coupling Reaction

Lo, Michael M.-C., Neumann, Christopher S., Nagayama, Satoshi, Perlstein, Ethan O., Schreiber, Stuart L.·2004·Journal of the American Chemical Society

Abstract

A collection of structurally complex and chemically diverse small molecules is a useful tool to explore cell circuitry. In this article, we report the split-pool synthesis of more than 3000 spirooxindoles on high capacity macrobeads. The key reaction to assemble the spirooxindole core stereoselectively is a Lewis acid variant of the Williams' three-component coupling. After formation, the skeleton was elaborated using Sonogashira couplings, amide forming reactions, and N-acylations of gamma-lactams. The final library was analyzed by sampling individual macrobeads and by using binomial confidence limits. It was determined that at least 82% of the library compounds should have better than 80% purity. To demonstrate the utility of our discovery process, a high-throughput chemical genetic modifier screen was performed using stock solutions of the resultant products. A number of positives were identified as enhancers of the cellular actions of latrunculin B, an actin polymerization inhibitor. Through resynthesis, we confirmed one of the positives and demonstrated that, in yeast cells, it has an EC50 in the sub-micromolar range.

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Metadata

Authors
Lo, M. M.-C., Neumann, C. S., Nagayama, S., Perlstein, E. O., & Schreiber, S. L.
Venue
Journal of the American Chemical Society
Published
2004-11-19
Volume
126
Issue
49
Pages
16077-16086
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W1968550772
Cited by
276
References
24
FWCI
2.73
Type
journal article
Language
en
Open access
closed

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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.