A rapid in vivo pipeline to identify small molecule inhibitors of amyloid aggregation
Abstract
Amyloids are associated with over 50 human diseases and have inspired significant effort to identify small molecule remedies. Here, we present an in vivo platform that efficiently yields small molecule inhibitors of amyloid formation. We previously identified small molecules that kill the nematode C. elegans by forming membrane-piercing crystals in the pharynx cuticle, which is rich in amyloid-like material. We show here that many of these molecules are known amyloid-binders whose crystal-formation in the pharynx can be blocked by amyloid-binding dyes. We asked whether this phenomenon could be exploited to identify molecules that interfere with the ability of amyloids to seed higher-order structures. We therefore screened 2560 compounds and found 85 crystal suppressors, 47% of which inhibit amyloid formation. This hit rate far exceeds other screening methodologies. Hence, in vivo screens for suppressors of crystal formation in C. elegans can efficiently reveal small molecules with amyloid-inhibiting potential. In this work, Kamal, Knox et al develop a high-throughput system to identify small molecules that disrupt amyloid formation by pre-selecting compounds that suppress molecular interactions within the cuticle of the C. elegans pharynx.
Read the paper
Related studies
- Improving sleep quality leads to better mental health: A meta-analysis of randomised controlled trials
- Tocilizumab in patients with severe COVID-19: a retrospective cohort study
- A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study
- Fruit, vegetable, and legume intake, and cardiovascular disease and deaths in 18 countries (PURE): a prospective cohort study
- Are noise and air pollution related to the incidence of dementia? A cohort study in London, England
- Long COVID symptoms and duration in SARS-CoV-2 positive children — a nationwide cohort study
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.