Skip to content

Targeting protein misfolding and aggregation in neurodegenerative diseases: challenges for the identification and validation of targets for small molecules.

Oct 2026 · Expert opinion on therapeutic targets · 0 citations · 96 references
Medicine

TL;DR

The mechanisms of protein folding, misfolding, aggregation, and prion-like propagation in major neurodegenerative proteinopathies, including amyloid-beta and tau in Alzheimer's disease, alpha-synuclein in synucleinopathies, TDP-43 and FUS in ALS/FTLD, polyglutamine-expanded proteins, prion proteins, and rare hereditary amyloidosis are summarized.

Abstract

INTRODUCTION Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and related proteinopathies are characterized by the misfolding, aggregation, and accumulation of specific proteins that disrupt neuronal homeostasis, leading to neuronal death. Despite major advances in structural biology and molecular neuroscience, identifying and validating druggable targets in neurodegenerative diseases remains challenging. Many involved proteins are intrinsically disordered, exhibit conformational heterogeneity, and form highly dynamic toxic species. AREAS COVERED This review summarizes the mechanisms of protein folding, misfolding, aggregation, and prion-like propagation in major neurodegenerative proteinopathies, including amyloid-beta and tau in Alzheimer's disease, alpha-synuclein in synucleinopathies, TDP-43 and FUS in ALS/FTLD, polyglutamine-expanded proteins, prion proteins, and rare hereditary amyloidosis. We also discuss major barriers to target identification and validation, including conformational flexibility, oligomer toxicity, blood-brain barrier penetration, and target engagement complexity. Finally, we highlight emerging strategies integrating structural biology, computational methods, and improved experimental models to discover small-molecule inhibitors for neurodegenerative diseases. EXPERT OPINION Effective therapeutic discovery will require moving beyond single-target models toward ensemble-based validation strategies. Integrating structural biology, advanced imaging, biomarkers, and computational approaches may improve the identification of druggable targets and support precision-medicine-based interventions for neurodegenerative diseases.

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.