Skip to content
#protein folding Open access

Peptide-based inhibitors of tau aggregation as a potential therapeutic for Alzheimer's disease

Oct 2026 · University of Southampton
Alzheimer's disease research and treatments

Abstract

Tauopathies are a group of neurodegenerative diseases characterized by the deposition of misfolded and aggregated Tau protein in patients’ brains. Alzheimer's disease (AD), the most common tauopathy and leading cause of dementia, affects over 55 million people worldwide, with prevalence projected to double every two years. Despite this enormous socioeconomic burden, there is still limited availability of disease-modifying therapies for AD. In 2022, our group developed RI-AG03, a peptide-based inhibitor targeting Tau aggregation-a key pathological hallmark of AD and demonstrated its inhibitory effect against truncated Tau aggregation in vitro. However, the necessity of assessing Tau aggregation inhibitors using physiologically relevant models is highlighted by observations that certain compounds, such as D-tlkivw, inhibit truncated Tau aggregation but fail against aggregation of 2N4R Tau. In this project, using heparin-induced aggregation of physiologically relevant 2N4R Tau, I confirmed that RI-AG03 inhibits this aggregation in a dose-dependent manner with an IC50 of 4.64 μM, comparable to its activity against truncated TauΔ1-250. The inhibition mechanism of RI-AG03 under the same condition was also evaluated in this project. The previous study employing heparin-induced aggregation of TauΔ1-250 indicated that RI-AG03 may inhibit Tau aggregation by redirecting the canonical aggregation pathway and promoting the formation of off-pathway species. The inhibition mechanism assessment performed in this project using heparin-induced aggregation of 2N4R Tau supported this hypothesis. The result of this assessment revealed that an off-pathway Tau species, RITA2N4R, was formed at the endpoint of RI-AG03 redirected, heparin-induced aggregation of 2N4R Tau. This species exhibited a morphology resembling nascent canonical 2N4R Tau filaments, but with much reduced cross β-sheet contents. Moreover, differential centrifugation and propagation competence test performed in this project also demonstrated that RITA2N4R has similar density but significantly reduced competence to seed new aggregation compared to canonical 2N4R Tau filaments. In this project, the in vitro inhibitory effect of RI-AG03 was also assessed using 0N3R PAD12, a pseudo phosphorylated 3R Tau construct that recapitulates the effects of Tau hyperphosphorylation. Notably, 0N3R PAD12 spontaneously forms filaments adopting AD fold in the absence of artificial inducers such as heparin, allowing the assessment to be performed under more tauopathy relevant conditions. RI-AG03 exhibited a significant inhibitory effect in this assessment, further confirming its potential as a therapeutic candidate. The previous study also confirmed that RI-AG03 alleviates Tau toxicity in vivo, as shown by extended lifespan and rescued eye degeneration in Drosophila models expressing 2N4R Tau pan-neuronally or specifically in the eyes. In this project, I provided direct evidence linking this attenuation of Tau toxicity to the inhibition of Tau aggregation. When RI-AG03 was administered to Drosophila models expressing either 2N4R Tau or the pseudo phosphorylated Tau construct 2N4R E14, which recapitulates the effects of Tau hyperphosphorylation, a significant inhibition or a clear trend toward inhibition of aggregation was observed in the two models, respectively.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.