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  Data-driven discovery of cardiolipin-selective small molecules by computational active learning

Mohr, B., Shmilovich, K., Kleinwächter, I. S., Schneider, D., Ferguson, A. L., & Bereau, T. (2022). Data-driven discovery of cardiolipin-selective small molecules by computational active learning. Chemical Science. doi:10.1039/d2sc00116k.

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d2sc00116k.pdf (Publisher version), 2MB
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2022
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The Author(s). Published by the Royal Society of Chemistry

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 Creators:
Mohr, Bernadette1, Author
Shmilovich, Kirill2, Author
Kleinwächter, Isabel S.3, Author
Schneider, Dirk3, Author
Ferguson, Andrew L.2, Author
Bereau, Tristan1, 4, Author              
Affiliations:
1Univ Amsterdam, Van 'T Hoff Institute for Molecular Sciences and Informatics, Amsterdam, Netherlands, ou_persistent22              
2Univ Chicago, Pritzker Sch Mol Engn, Chicago, IL, USA, ou_persistent22              
3Johannes Gutenberg Univ Mainz, Dept Chem Biochem, Mainz, Germany, ou_persistent22              
4Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society, ou_1800287              

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Language(s): eng - English
 Dates: 2022-03-02
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1039/d2sc00116k
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Title: Chemical Science
  Other : Chem. Sci.
Source Genre: Journal
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Publ. Info: Cambridge, UK : Royal Society of Chemistry
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 2041-6520
CoNE: https://pure.mpg.de/cone/journals/resource/2041-6520