AMI-CryoML
HORIZON EUROPE · ERA FELLOWSHIPS
How do small molecules reshape amyloid fibrils?
Connecting aggregation experiments, cryo-electron microscopy and machine learning to understand amyloid polymorphism.
Amyloids · Structural biology · Machine learning
- Programme
- Horizon Europe · ERA Fellowships
- Grant ID
- 101244706
- Start date
- 1 Feb 2026
- Duration
- 24 months
- Budget
- €181,136.16
The research question
Amyloid fibrils can adopt different structures, and those differences matter for their biological effects. AMI-CryoML investigates how small aggregation modulators affect both aggregation kinetics and the structures that form. Linking experiments with structural data provides the basis for learning relationships that can be tested in predictive models.
What the project sets out to do
01 / RESEARCH AIM
Map the modulators
Collect aggregation modulators and characterise their chemical and mechanistic properties.
02 / RESEARCH AIM
Measure and resolve
Use thioflavin-T assays to measure kinetic effects across prions, CsgA and α-synuclein, and cryo-EM to resolve fibril polymorphs.
03 / RESEARCH AIM
Connect data with prediction
Extend AmyloGraph with modulator–kinetics–structure records and train models to predict modulator effects.
People & support
Project lead: Jarosław Chilimoniuk.
European Commission | European Research Executive Agency
Full project title
Cracking the code of amyloid polymorphism: integrating cryoEM and machine learning to unravel impact of small aggregation modulators on amyloid fibril polymorphism
Explore further
Related research: amyloids & aggregation · Group publications · Group news