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Amyloid Fibrils

Amyloid Fibrils

Amyloid fibrils are aggregates of misfolded proteins. Under most circumstances, misfolded proteins are either refolded by chaperone proteins or degraded by the proteasome. However, in the case of a mutation or a disease, these proteins can accumulate to form large clusters and often further assemble to form elongated fibers, called fibrils.
Amyloid deposits were observed as early as 1639 in the liver and the spleen. In 1854, Rudolph Virchow performed iodine staining,...

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Updated: Jan 17, 2026

In Vitro Aggregation Assays Using Hyperphosphorylated Tau Protein

In Vitro Aggregation Assays Using Hyperphosphorylated Tau Protein

Published on: January 2, 2015

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

Alessia Santambrogio¹, Robert I Horne¹, Michael A Metrick^1,2,3

¹Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K.

Journal of the American Chemical Society

|September 18, 2025

Summary

This summary is machine-generated.

Researchers developed a new assay to study tau aggregation in Alzheimer's disease (AD). This method identified small molecules that inhibit specific tau fibril formations, showing promise in a fruit fly model of tauopathy.

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Area of Science:

Neuroscience
Biochemistry
Pharmacology

Background:

Tau aggregation into amyloid fibrils is a hallmark of Alzheimer's disease (AD) and other tauopathies.
Distinct tau fibril morphologies characterize different tauopathies, necessitating assays that mimic in-brain aggregation.
Developing in vitro assays that recapitulate brain-like tau aggregation is crucial for identifying effective inhibitors.

Purpose of the Study:

To develop an in vitro tau aggregation assay that replicates polymorph-specific fibril formation using AD brain homogenates.
To establish a method for generating tau fibril seed libraries for kinetic assays.
To identify small molecules that specifically inhibit the in vitro formation of tau fibrils using machine learning.

Main Methods:

Utilized AD brain homogenates to seed the generation of first-generation tau fibrils under quiescent conditions.
Created amyloid seed libraries from these fibrils for subsequent kinetic assays.
Employed an iterative machine learning approach to screen for small molecule inhibitors targeting specific tau fibril polymorphs.

Main Results:

Successfully developed a polymorph-specific in vitro tau aggregation assay.
Generated tau fibril seed libraries enabling second-generation kinetic assays.
Identified small molecules that potently inhibit in vitro tau fibril formation in a polymorph-specific manner.
Validated the efficacy of selected small molecules in a Drosophila tauopathy model.

Conclusions:

The developed assay effectively recapitulates polymorph-specific tau aggregation.
The machine learning strategy efficiently identifies inhibitors of specific tau fibril morphologies.
The identified small molecules demonstrate therapeutic potential for tauopathies, including Alzheimer's disease.