Discovery of Potent Inhibitors of α-Synuclein Aggregation Using Structure-Based Iterative Learning
Discovery of Potent Inhibitors of α-Synuclein Aggregation Using Structure-Based Iterative Learning
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.
Horne Robert I.、Srivastava Ankit、Gregory Rebecca C.、Possenti Andrea、Chia Sean、Caughey Byron、Staats Roxine、Aubert Alice、Ghetti Bernardino、Andrzejewska Ewa、Sormanni Pietro、Nowinska Magdalena、Alam Parvez、Brotzakis Z. Faidon、Knowles Tuomas P. J.、Vendruscolo Michele
Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeLaboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, National Institutes of HealthCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge||Bioprocessing Technology Institute, Agency of Science, Technology and Research (A*STAR)Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, National Institutes of HealthCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeDepartment of Pathology and Laboratory Medicine, Indiana University School of MedicineCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeLaboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, National Institutes of HealthCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of CambridgeCentre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge
医药卫生理论医学研究方法神经病学、精神病学药学生物科学研究方法、生物科学研究技术生物化学分子生物学
Parkinson’s diseaseα-synucleinprotein aggregationmachine learningcomputational dockingstructure-based drug discoverykinetic-based drug discoveryRT-QuICsingle molecule analysis
Horne Robert I.,Srivastava Ankit,Gregory Rebecca C.,Possenti Andrea,Chia Sean,Caughey Byron,Staats Roxine,Aubert Alice,Ghetti Bernardino,Andrzejewska Ewa,Sormanni Pietro,Nowinska Magdalena,Alam Parvez,Brotzakis Z. Faidon,Knowles Tuomas P. J.,Vendruscolo Michele.Discovery of Potent Inhibitors of α-Synuclein Aggregation Using Structure-Based Iterative Learning[EB/OL].(2025-03-28)[2025-05-09].https://www.biorxiv.org/content/10.1101/2021.11.10.468009.点此复制
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