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Design of Tau Aggregation Inhibitors Using Iterative Machine Learning and a Polymorph-Specific Brain-Seeded Fibril Amplification Assay

Santambrogio, Alessia ; Horne, Robert I. ; Metrick, Michael A. ; Gallagher, Nicholas C.T. ; Brotzakis, Z. Faidon ; Rinauro, Dillon ; Vourkou, Ergina ; Papanikolopoulou, Katerina ; Skoulakis, Efthimios M.C. and Linse, Sara LU , et al. (2025) In Journal of the American Chemical Society 147(39). p.35942-35952
Abstract

The aggregation of tau into amyloid fibrils is associated with Alzheimer’s disease (AD) and related tauopathies. Since different tauopathies are characterized by the formation of distinct tau fibril morphologies, it is important to combine the search of tau aggregation inhibitors with the development of in vitro tau aggregation assays that recapitulate aggregation as it may occur in the brain. Here we address this problem by reporting an in vitro tau aggregation assay in which AD brain homogenates are used to seed the generation of first-generation tau fibrils in a polymorph-specific manner under quiescent conditions. These fibrils are then used to create amyloid seed libraries from which second-generation kinetic assays can be readily... (More)

The aggregation of tau into amyloid fibrils is associated with Alzheimer’s disease (AD) and related tauopathies. Since different tauopathies are characterized by the formation of distinct tau fibril morphologies, it is important to combine the search of tau aggregation inhibitors with the development of in vitro tau aggregation assays that recapitulate aggregation as it may occur in the brain. Here we address this problem by reporting an in vitro tau aggregation assay in which AD brain homogenates are used to seed the generation of first-generation tau fibrils in a polymorph-specific manner under quiescent conditions. These fibrils are then used to create amyloid seed libraries from which second-generation kinetic assays can be readily performed. Using this strategy, we illustrate an iterative machine learning method for the identification of small molecules for the polymorph-specific inhibition of the in vitro formation of tau fibrils. We further show that the small molecules selected by this procedure are potent inhibitors in a Drosophila tauopathy model.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of the American Chemical Society
volume
147
issue
39
pages
11 pages
publisher
The American Chemical Society (ACS)
external identifiers
  • scopus:105017465823
  • pmid:40964862
ISSN
0002-7863
DOI
10.1021/jacs.5c12812
language
English
LU publication?
yes
id
81cd56e3-32eb-45cc-9ad4-dbb0035154c4
date added to LUP
2025-12-08 12:00:33
date last changed
2025-12-09 03:00:14
@article{81cd56e3-32eb-45cc-9ad4-dbb0035154c4,
  abstract     = {{<p>The aggregation of tau into amyloid fibrils is associated with Alzheimer’s disease (AD) and related tauopathies. Since different tauopathies are characterized by the formation of distinct tau fibril morphologies, it is important to combine the search of tau aggregation inhibitors with the development of in vitro tau aggregation assays that recapitulate aggregation as it may occur in the brain. Here we address this problem by reporting an in vitro tau aggregation assay in which AD brain homogenates are used to seed the generation of first-generation tau fibrils in a polymorph-specific manner under quiescent conditions. These fibrils are then used to create amyloid seed libraries from which second-generation kinetic assays can be readily performed. Using this strategy, we illustrate an iterative machine learning method for the identification of small molecules for the polymorph-specific inhibition of the in vitro formation of tau fibrils. We further show that the small molecules selected by this procedure are potent inhibitors in a Drosophila tauopathy model.</p>}},
  author       = {{Santambrogio, Alessia and Horne, Robert I. and Metrick, Michael A. and Gallagher, Nicholas C.T. and Brotzakis, Z. Faidon and Rinauro, Dillon and Vourkou, Ergina and Papanikolopoulou, Katerina and Skoulakis, Efthimios M.C. and Linse, Sara and Caughey, Byron and Vendruscolo, Michele}},
  issn         = {{0002-7863}},
  language     = {{eng}},
  number       = {{39}},
  pages        = {{35942--35952}},
  publisher    = {{The American Chemical Society (ACS)}},
  series       = {{Journal of the American Chemical Society}},
  title        = {{Design of Tau Aggregation Inhibitors Using Iterative Machine Learning and a Polymorph-Specific Brain-Seeded Fibril Amplification Assay}},
  url          = {{http://dx.doi.org/10.1021/jacs.5c12812}},
  doi          = {{10.1021/jacs.5c12812}},
  volume       = {{147}},
  year         = {{2025}},
}