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Amyloid Fibrils

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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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Novel Atomic Force Microscopy Based Biopanning for Isolation of Morphology Specific Reagents against TDP-43 Variants in Amyotrophic Lateral Sclerosis

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AI-Guided Dual Strategy for Peptide Inhibitor Design Targeting Structural Polymorphs of α-Synuclein Fibrils.

Jinfang Duan, Haoyu Zhang, Chuanqi Sun

Biorxiv : the Preprint Server for Biology

|November 24, 2025

Summary

Researchers developed AI-designed peptides to inhibit alpha-synuclein (α-syn) fibril formation, a key process in Parkinson's disease. These peptides effectively reduce α-syn aggregation, offering a promising strategy for neurodegenerative disease treatment.

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Published on: May 30, 2021

Area of Science:

Neuroscience
Biochemistry
Computational Biology

Background:

Alpha-synuclein (α-syn) aggregation into β-sheet-rich fibrils is central to Parkinson's disease pathogenesis.
Distinct α-syn fibril polymorphs identified by Cryo-EM present challenges for inhibitor design.

Purpose of the Study:

To develop a structure-guided framework using AI for designing peptide inhibitors targeting conserved β-sheet motifs in α-syn fibrils.
To create short peptides capable of interfering with α-syn fibril formation across different polymorphs.

Main Methods:

Utilized AI tools including ProteinMPNN, AlphaFold-Multimer, and PepMLM for structure-guided peptide generation.
Employed a framework integrating Cryo-EM structural data with computational design.
Assessed peptide efficacy through ThT fluorescence assays and analysis of aggregate morphology.

Main Results:

Identified two candidate peptides, T1 and S1, demonstrating significant inhibition of α-syn fibrillation.
Observed reduced ThT fluorescence and formation of amorphous or fragmented aggregates upon peptide treatment.
Correlated peptide inhibitory potency with predicted interface energies.

Conclusions:

AI-assisted peptide design, guided by Cryo-EM structures, enables rapid discovery of broad-spectrum inhibitors for α-syn fibrils.
This integrated approach represents a promising strategy for precision treatment of neurodegenerative diseases like Parkinson's.
The developed peptides show potential for therapeutic intervention by disrupting pathological protein aggregation.