Using computer modeling to find new LRRK2 inhibitors for parkinson's disease.

ABSTRACT: Parkinson's disease (PD) is a complex neurodegenerative disorder that affects multiple neurotransmitters, and its exact cause is still unknown. Developing new drugs for PD is a lengthy and expensive process, making it difficult to find new treatments. This study aims to create a detailed dataset to build strong predictive models with various machine learning algorithms. An ensemble modeling approach was employed to screen the DrugBank database, aiming to repurpose approved medications as potential treatments for Parkinson's disease (PD). The dataset was constructed using pIC50 values of various compounds targeting the inhibition of leucine-rich repeat kinase 2 (LRRK2). The best ensemble model showed exceptional predictive performance, with five-fold cross-validation and external validation

SUBMITTER: Garcia MC 

PROVIDER: S-EPMC11790940 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature