Can AlphaFold3 predict unseen amyloid polymorphs?

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Abstract

Amyloid fibrils are highly ordered, aggregation-prone protein assemblies implicated in numerous neurodegenerative diseases. Their formation arises from protein misfolding, producing structurally distinct polymorphs that have historically been difficult to predict computationally. While AlphaFold2 excels at predicting monomeric globular proteins, it struggles with protein complexes. Here, we show that AlphaFold3 provides a new opportunity to model amyloid structure and capture polymorph heterogeneity. Using TM-score based clustering of known α-synuclein fibril structures, we establish a polymorph nomenclature and demonstrate that AlphaFold3 can reproduce known fibril architectures and predict alternative conformations. These results highlight AlphaFold3’s potential for studying amyloid proteins, enabling systematic investigation of amyloid polymorphism.
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Abstract Amyloid fibrils are highly ordered, aggregation-prone protein assemblies implicated in numerous neurodegenerative diseases. Their formation arises from protein misfolding, producing structurally distinct polymorphs that have historically been difficult to predict computationally. While AlphaFold2 excels at predicting monomeric globular proteins, it struggles with protein complexes. Here, we show that AlphaFold3 provides a new opportunity to model amyloid structure and capture polymorph heterogeneity. Using TM-score based clustering of known α-synuclein fibril structures, we establish a polymorph nomenclature and demonstrate that AlphaFold3 can reproduce known fibril architectures and predict alternative conformations. These results highlight AlphaFold3’s potential for studying amyloid proteins, enabling systematic investigation of amyloid polymorphism. Competing Interest Statement The authors have declared no competing interest.

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europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
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License: CC-BY-NC-4.0