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COMPUTATIONAL BIOPHYSICS

Kinetics of amyloid β from deep learning

Nature Computational Science volume 1, pages 20–21 (2021)Cite this article

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Characterizing the aggregation of the peptide amyloid β is essential to better understand Alzheimer’s disease and to find potential targets for drug development. Deep neural networks make it possible to describe the kinetics of this peptide, opening the way for achieving this goal.

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Fig. 1: Kinetics ensemble of Aβ42 monomer from MD simulation and deep learning.

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Authors and Affiliations

  1. Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA

    Fanjie Meng & Hoi Sung Chung

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  1. Fanjie Meng
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  2. Hoi Sung Chung
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Correspondence to Fanjie Meng or Hoi Sung Chung.

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Meng, F., Chung, H.S. Kinetics of amyloid β from deep learning. Nat Comput Sci 1, 20–21 (2021). https://doi.org/10.1038/s43588-020-00010-x

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