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Drug discovery

A multidimensional dataset for structure-based machine learning

Nature Computational Science volume 4, pages 318–319 (2024)Cite this article

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MISATO, a dataset for structure-based drug discovery combines quantum mechanics property data and molecular dynamics simulations on ~20,000 protein–ligand structures, substantially extends the amount of data available to the community and holds potential for advancing work in drug discovery.

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Fig. 1: Non-exhaustive comparison of MISATO to existing datasets, and pipeline for MISATO construction.

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Authors and Affiliations

  1. Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, USA

    Matthew Holcomb & Stefano Forli

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  1. Matthew Holcomb
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  2. Stefano Forli
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Correspondence to Matthew Holcomb or Stefano Forli.

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The authors declare no competing interests.

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Holcomb, M., Forli, S. A multidimensional dataset for structure-based machine learning. Nat Comput Sci 4, 318–319 (2024). https://doi.org/10.1038/s43588-024-00631-6

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