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A Turing Test for Molecular Generators
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    A Turing Test for Molecular Generators
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    • Jacob T. Bush
      Jacob T. Bush
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Peter Pogany
      Peter Pogany
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
      More by Peter Pogany
    • Stephen D. Pickett
      Stephen D. Pickett
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Mike Barker
      Mike Barker
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
      More by Mike Barker
    • Andrew Baxter
      Andrew Baxter
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Sebastien Campos
      Sebastien Campos
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Anthony W. J. Cooper
      Anthony W. J. Cooper
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • David Hirst
      David Hirst
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
      More by David Hirst
    • Graham Inglis
      Graham Inglis
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Alan Nadin
      Alan Nadin
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
      More by Alan Nadin
    • Vipulkumar K. Patel
      Vipulkumar K. Patel
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Darren Poole
      Darren Poole
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
      More by Darren Poole
    • John Pritchard
      John Pritchard
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Yoshiaki Washio
      Yoshiaki Washio
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
    • Gemma White
      Gemma White
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
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    • Darren V. S. Green*
      Darren V. S. Green
      GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, U.K.
      *Email: [email protected]
    Other Access OptionsSupporting Information (3)

    Journal of Medicinal Chemistry

    Cite this: J. Med. Chem. 2020, 63, 20, 11964–11971
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    https://doi.org/10.1021/acs.jmedchem.0c01148
    Published September 21, 2020
    Copyright © 2020 American Chemical Society

    Abstract

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    Machine learning approaches promise to accelerate and improve success rates in medicinal chemistry programs by more effectively leveraging available data to guide a molecular design. A key step of an automated computational design algorithm is molecule generation, where the machine is required to design high-quality, drug-like molecules within the appropriate chemical space. Many algorithms have been proposed for molecular generation; however, a challenge is how to assess the validity of the resulting molecules. Here, we report three Turing-inspired tests designed to evaluate the performance of molecular generators. Profound differences were observed between the performance of molecule generators in these tests, highlighting the importance of selection of the appropriate design algorithms for specific circumstances. One molecule generator, based on match molecular pairs, performed excellently against all tests and thus provides a valuable component for machine-driven medicinal chemistry design workflows.

    Copyright © 2020 American Chemical Society

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    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jmedchem.0c01148.

    • Experimental Details, Supplementary Figures (Figure S1-S4) and Supplementary Tables (Table S1-S4) (PDF)

    • Results of the Turing Test (CSV)

    • Full list of chemistry ideas (CSV)

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    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

    Cited By

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    Citation Statements
    Explore this article's citation statements on scite.ai

    This article is cited by 27 publications.

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    2. Ziyi Yang, Shaohua Shi, Li Fu, Aiping Lu, Tingjun Hou, Dongsheng Cao. Matched Molecular Pair Analysis in Drug Discovery: Methods and Recent Applications. Journal of Medicinal Chemistry 2023, 66 (7) , 4361-4377. https://doi.org/10.1021/acs.jmedchem.2c01787
    3. Brian Goldman, Steven Kearnes, Trevor Kramer, Patrick Riley, W. Patrick Walters. Defining Levels of Automated Chemical Design. Journal of Medicinal Chemistry 2022, 65 (10) , 7073-7087. https://doi.org/10.1021/acs.jmedchem.2c00334
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    15. . Useful Computational Chemistry Tools for Medicinal Chemistry. 2023https://doi.org/10.1039/9781788018982-00094
    16. Chong Lu, Shien Liu, Weihua Shi, Jun Yu, Zhou Zhou, Xiaoxiao Zhang, Xiaoli Lu, Faji Cai, Ning Xia, Yikai Wang. Systemic evolutionary chemical space exploration for drug discovery. Journal of Cheminformatics 2022, 14 (1) https://doi.org/10.1186/s13321-022-00598-4
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    18. Ferruccio Palazzesi, Alfonso Pozzan. Deep Learning Applied to Ligand-Based De Novo Drug Design. 2022, 273-299. https://doi.org/10.1007/978-1-0716-1787-8_12
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    20. Sandeep Pal, Peter Pogány, James Andrew Lumley. Molecule Ideation Using Matched Molecular Pairs. 2022, 503-521. https://doi.org/10.1007/978-1-0716-1787-8_23
    21. Atanas Patronov, Kostas Papadopoulos, Ola Engkvist. Has Artificial Intelligence Impacted Drug Discovery?. 2022, 153-176. https://doi.org/10.1007/978-1-0716-1787-8_6
    22. Giovanni Cincilla, Simone Masoni, Jascha Blobel. Individual and collective human intelligence in drug design: evaluating the search strategy. Journal of Cheminformatics 2021, 13 (1) https://doi.org/10.1186/s13321-021-00556-6
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    25. Lauren L. Grant, Clarissa S. Sit. De novo molecular drug design benchmarking. RSC Medicinal Chemistry 2021, 12 (8) , 1273-1280. https://doi.org/10.1039/D1MD00074H
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    27. José T. Moreira-Filho, Arthur C. Silva, Rafael F. Dantas, Barbara F. Gomes, Lauro R. Souza Neto, Jose Brandao-Neto, Raymond J. Owens, Nicholas Furnham, Bruno J. Neves, Floriano P. Silva-Junior, Carolina H. Andrade. Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence. Frontiers in Immunology 2021, 12 https://doi.org/10.3389/fimmu.2021.642383

    Journal of Medicinal Chemistry

    Cite this: J. Med. Chem. 2020, 63, 20, 11964–11971
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jmedchem.0c01148
    Published September 21, 2020
    Copyright © 2020 American Chemical Society

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