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Overlay databank unlocks data-driven analyses of biomolecules for all

Author

Listed:
  • Anne M. Kiirikki

    (University of Helsinki, Institute of Biotechnology)

  • Hanne S. Antila

    (Max Planck Institute of Colloids and Interfaces
    University of Bergen)

  • Lara S. Bort

    (Max Planck Institute of Colloids and Interfaces
    University of Potsdam, Institute of Physics and Astronomy)

  • Pavel Buslaev

    (University of Jyväskylä)

  • Fernando Favela-Rosales

    (Tecnológico Nacional de México - ITS Zacatecas Occidente)

  • Tiago Mendes Ferreira

    (Martin Luther University Halle-Wittenberg)

  • Patrick F. J. Fuchs

    (PSL University, CNRS, Laboratoire des Biomolécules (LBM)
    Université Paris Cité)

  • Rebeca Garcia-Fandino

    (Universidade de Santiago de Compostela)

  • Ivan Gushchin
  • Batuhan Kav

    (Institute of Biological Information Processing: Structural Biochemistry (IBI-7), Forschungszentrum Jülich
    ariadne.ai GmbH (Germany))

  • Norbert Kučerka

    (Comenius University Bratislava)

  • Patrik Kula

    (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences)

  • Milla Kurki

    (University of Eastern Finland)

  • Alexander Kuzmin
  • Anusha Lalitha

    (Université Montpellier)

  • Fabio Lolicato

    (Heidelberg University Biochemistry Center
    University of Helsinki)

  • Jesper J. Madsen

    (University of South Florida
    University of South Florida)

  • Markus S. Miettinen

    (Max Planck Institute of Colloids and Interfaces
    University of Bergen
    University of Bergen)

  • Cedric Mingham

    (University of Applied Sciences)

  • Luca Monticelli

    (University of Lyon, CNRS, Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086)
    Institut National de la Santé et de la Recherche Médicale (INSERM))

  • Ricky Nencini

    (University of Helsinki, Institute of Biotechnology
    University of Helsinki)

  • Alexey M. Nesterenko

    (University of Bergen
    University of Bergen)

  • Thomas J. Piggot

    (University of Southampton)

  • Ángel Piñeiro

    (University of Santiago de Compostela)

  • Nathalie Reuter

    (University of Bergen
    University of Bergen)

  • Suman Samantray

    (Institute of Biological Information Processing: Structural Biochemistry (IBI-7), Forschungszentrum Jülich
    RWTH Aachen University)

  • Fabián Suárez-Lestón

    (Universidade de Santiago de Compostela
    University of Santiago de Compostela
    MD.USE Innovations S.L.)

  • Reza Talandashti

    (University of Bergen
    University of Bergen)

  • O. H. Samuli Ollila

    (University of Helsinki, Institute of Biotechnology
    VTT Technical Research Centre of Finland)

Abstract

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank—a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

Suggested Citation

  • Anne M. Kiirikki & Hanne S. Antila & Lara S. Bort & Pavel Buslaev & Fernando Favela-Rosales & Tiago Mendes Ferreira & Patrick F. J. Fuchs & Rebeca Garcia-Fandino & Ivan Gushchin & Batuhan Kav & Norber, 2024. "Overlay databank unlocks data-driven analyses of biomolecules for all," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45189-z
    DOI: 10.1038/s41467-024-45189-z
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    References listed on IDEAS

    as
    1. Rob Phillips & Tristan Ursell & Paul Wiggins & Pierre Sens, 2009. "Emerging roles for lipids in shaping membrane-protein function," Nature, Nature, vol. 459(7245), pages 379-385, May.
    2. Kathryn Tunyasuvunakool & Jonas Adler & Zachary Wu & Tim Green & Michal Zielinski & Augustin Žídek & Alex Bridgland & Andrew Cowie & Clemens Meyer & Agata Laydon & Sameer Velankar & Gerard J. Kleywegt, 2021. "Highly accurate protein structure prediction for the human proteome," Nature, Nature, vol. 596(7873), pages 590-596, August.
    3. Jacopo Frallicciardi & Josef Melcr & Pareskevi Siginou & Siewert J. Marrink & Bert Poolman, 2022. "Membrane thickness, lipid phase and sterol type are determining factors in the permeability of membranes to small solutes," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Piotr Klukowski & Roland Riek & Peter Güntert, 2022. "Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    5. John Jumper & Richard Evans & Alexander Pritzel & Tim Green & Michael Figurnov & Olaf Ronneberger & Kathryn Tunyasuvunakool & Russ Bates & Augustin Žídek & Anna Potapenko & Alex Bridgland & Clemens Me, 2021. "Highly accurate protein structure prediction with AlphaFold," Nature, Nature, vol. 596(7873), pages 583-589, August.
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