Diffusion-Model-Guided Identification of a Candidate α-Synuclein Aggregation Inhibitor under Secondary-Nucleation-Dominated Conditions

Abstract The process of α-synuclein aggregation results in the formation of amyloid deposits that accumulate in the brain of patients affected by Parkinson’s disease and related synucleinopathies. Among possible therapeutic strategies for these conditions, one approach is based on the development of compounds capable of inhibiting α-synuclein aggregation. An effective inhibition could be achieved by blocking the nucleation sites on the surface of the amyloid fibrils that are responsible for their autocatalytic proliferation. Here, we use an E(3)-equivariant conditional diffusion model to identify candidate inhibitors of this type. With this approach, we generated pocket-conditioned molecules, identified purchasable analogues, and experimentally tested selected compounds. We thus identified a compound that delays α-synuclein aggregation under conditions in which secondary nucleation is the dominant process. These results illustrate the use of conditional diffusion models to identify candidate aggregation inhibitors.

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Journal
The Journal of Physical Chemistry Letters
Published
2026-11-02
DOI
https://doi.org/10.1021/acs.jpclett.6c02433
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Diffusion-Model-Guided Identification of a Candidate α-Synuclein Aggregation Inhibitor under Secondary-Nucleation-Dominated Conditions

Z. Faidon Brotzakis, Michele Vendruscolo, Charles Bonner Harris, Robert I. Horne et al.
The Journal of Physical Chemistry Letters
Computational Drug Discovery Methods
article

Diffusion-Model-Guided Identification of a Candidate α-Synuclein Aggregation Inhibitor under Secondary-Nucleation-Dominated Conditions

Z. Faidon Brotzakis, Michele Vendruscolo, Charles Bonner Harris, Robert I. Horne, Píetro Lió, Hao Zhang
article en

Abstract

Abstract The process of α-synuclein aggregation results in the formation of amyloid deposits that accumulate in the brain of patients affected by Parkinson’s disease and related synucleinopathies. Among possible therapeutic strategies for these conditions, one approach is based on the development of compounds capable of inhibiting α-synuclein aggregation. An effective inhibition could be achieved by blocking the nucleation sites on the surface of the amyloid fibrils that are responsible for their autocatalytic proliferation. Here, we use an E(3)-equivariant conditional diffusion model to identify candidate inhibitors of this type. With this approach, we generated pocket-conditioned molecules, identified purchasable analogues, and experimentally tested selected compounds. We thus identified a compound that delays α-synuclein aggregation under conditions in which secondary nucleation is the dominant process. These results illustrate the use of conditional diffusion models to identify candidate aggregation inhibitors.

The Journal of Physical Chemistry Letters
University of Cambridge (GB)
Good health and well-being
Openalex Percentile: Top 98%
Computational Drug Discovery Methods
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Diffusion-Model-Guided Identification of a Candidate α-Synuclein Aggregation Inhibitor under Secondary-Nucleation-Dominated Conditions — Z. Faidon Brotzakis, Michele Vendruscolo, et al. · The Journal of Physical Chemistry Letters (2026) | TGRS Research Map | TGRS