Amelioration of Alzheimer's disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow.

ABSTRACT: A reduced removal of dysfunctional mitochondria is common to aging and age-related neurodegenerative pathologies such as Alzheimer's disease (AD). Strategies for treating such impaired mitophagy would benefit from the identification of mitophagy modulators. Here we report the combined use of unsupervised machine learning (involving vector representations of molecular structures, pharmacophore fingerprinting and conformer fingerprinting) and a cross-species approach for the screening and experimental validation of new mitophagy-inducing compounds. From a library of naturally occurring compounds, the workflow allowed us to identify 18 small molecules, and among them two potent mitophagy inducers (Kaempferol and Rhapontigenin). In nematode and rodent models of AD, we show that both mitophagy

SUBMITTER: Xie C 

PROVIDER: S-EPMC8782726 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature