A mechanistic model of pure and lipidic α-synuclein aggregation for advancing Parkinson’s therapies

Alpha-synuclein (aSyn) plays a crucial role in Parkinson’s disease, with various aggregates proposed as pathogenic triggers and therapeutic targets. However, anti-aSyn aggregation compounds often fail due to limited knowledge of the underlying molecular basis. In particular, interactions with lipid membranes are central to both physiological and pathological roles of aSyn, yet their underlying mechanisms remain unclear. Disrupting this balance may drive Parkinson’s onset and progression, underscoring the need for a mechanistic understanding of pure and lipid-mediated aggregation. Building on well-established in vitro aggregation studies, we propose a mathematical model of aSyn accumulation incorporating both aggregation routes via a nucleation-conversion-polymerization process with self-amplifying loops and toxic oligomers. Model calibration uses data from in vitro assays mimicking physiologically relevant conditions, providing insights into transient and stable aSyn intermediates. Inc...

Alpha-synuclein (aSyn) plays a crucial role in Parkinson’s disease, with various aggregates proposed as pathogenic triggers and therapeutic targets. However, anti-aSyn aggregation compounds often fail due to limited knowledge of the underlying molecular basis. In particular, interactions with lipid membranes are central to both physiological and pathological roles of aSyn, yet their underlying mechanisms remain unclear. Disrupting this balance may drive Parkinson’s onset and progression, underscoring the need for a mechanistic understanding of pure and lipid-mediated aggregation. Building on well-established in vitro aggregation studies, we propose a mathematical model of aSyn accumulation incorporating both aggregation routes via a nucleation-conversion-polymerization process with self-amplifying loops and toxic oligomers. Model calibration uses data from in vitro assays mimicking physiologically relevant conditions, providing insights into transient and stable aSyn intermediates. Incorporating aSyn-lipid interactions enables in silico exploration of how lipid-to-aSyn ratio influences aggregation, with possible implications for neurodegeneration. Sensitivity analysis highlights secondary nucleation inhibition as a potential anti-aggregation strategy. Overall, our work contributes to a unified framework for investigating in vitro aSyn aggregation and evaluating Parkinson’s therapies by building on existing models. It can serve as a stand-alone tool and a modular component in multiscale models, with potential applications in quantitative systems pharmacology.