Parkinson’s disease (PD) is a rapidly growing neurodegenerative disorder with significant global impact, both medically and economically. While environmental factors like age and pesticide exposure contribute to sporadic cases, genetic mutations also play a role. Among these, mutations in the PRKN gene, which encodes the Parkin protein, are the most common cause of autosomal recessive PD. Parkin is a RING-in-between-RING (RBR) E3 ubiquitin ligase that regulates mitochondrial homeostasis via mitophagy. Its function depends on complex conformational changes across six domains. Loss-of-function mutations in any of these domains can impair Parkin activity and contribute to PD pathogenesis. Therapeutic strategies targeting Parkin activation—such as small molecules or molecular glues—require a detailed understanding of its structural dynamics. Despite progress in structural characterization, gaps remain, including missing domain data and limited thermodynamic and dynamic insights, which are crucial for rational drug design. We propose the use of computational tools to elucidate this missing information. First, we showed that AlphaFold 3 is sensitive enough to distinguish between post-translational modifications that are important in Parkin’s conformational mechanism, reproducing experimentally known structures. After benchmarking, we ran predictions for an unknown conformation, where Parkin interacts with the ubiquitin-bound-E2 conjugating enzyme. The resulting RING domain/E2 complex recapitulates the interface observed in other distant homolog RBR E3 ubiquitin ligase, supporting the validity of the model. Future work includes reweighting AlphaFold predictions using hydrogen-deuterium exchange mass spectrometry data and thermodynamics analysis of reweighted models. These refined models will be used in molecular dynamics simulations to gain a deeper insight into Parkin’s conformational mechanism and dynamics.
Herrada et al. (Sun,) studied this question.