Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.

Journal: Nature chemical biology
PMID: 38632492

Abstract

Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. To address this problem, we describe here a machine learning approach to identify small molecule inhibitors of α-synuclein aggregation, a process implicated in Parkinson's disease and other synucleinopathies. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation, we aim to identify compounds that bind the catalytic sites on the surface of the aggregates. To achieve this goal, we use structure-based machine learning in an iterative manner to first identify and then progressively optimize secondary nucleation inhibitors. Our results demonstrate that this approach leads to the facile identification of compounds two orders of magnitude more potent than previously reported ones.

Authors

  • Robert I Horne
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Ewa A Andrzejewska
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Parvez Alam
    Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA.
  • Z Faidon Brotzakis
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Ankit Srivastava
    Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA.
  • Alice Aubert
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Magdalena Nowinska
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Rebecca C Gregory
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Roxine Staats
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Andrea Possenti
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Sean Chia
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Pietro Sormanni
    Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
  • Bernardino Ghetti
    Indiana University, Bloomington, Indiana, USA.
  • Byron Caughey
    Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA.
  • Tuomas P J Knowles
    Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
  • Michele Vendruscolo
    Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, UK. Electronic address: mv245@cam.ac.uk.

Keywords

External Resources

Popular Topics
Recent Journals