Insights into Alpha-Synuclein/S100B Interactions in Parkinson’s Disease by Molecular Modelling

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor dysfunction and cognitive decline, primarily attributed to the abnormal accumulation of alpha-synuclein (α-syn). This protein tends to misfold and aggregate, forming Lewy bodies, which are pathological hallmarks of PD. The aggregation of α-syn disrupts neuronal function and viability, leading to the clinical manifestations of the disease. Previous studies have explored interactions between amyloidogenic proteins and S100 family members, suggesting the involvement of S100 proteins, a family of calcium-binding proteins, in neurodegenerative processes. Notably, interactions between S100A9 and α-synuclein have been documented, where S100A9 influences the aggregation kinetics and fibril structure of α-syn, potentially worsening neurodegeneration. Similarly, the interaction between S100B and β-amyloid has been explored, revealing that S100B can inhibit β-amyloid aggregation, indicating a modulatory role in Alzheimer's disease. In the contest of Parkinson's disease (PD), elevated levels of the S100B protein have been observed in the substantia nigra of patients, suggesting its potential involvement in the disease's development. However, the direct interaction between S100B and α-synuclein remains underexplored. This work aims to investigate the interaction between S100B and α-synuclein through computational modeling and molecular dynamics simulations. Since no experimentally determined structure of the complex was available in the literature, its structure was predicted using two different approaches. The first method employed AlphaFold, an AI-based structure prediction tool, while the second approach utilized HADDOCK through molecular docking. In the second case, due to the lack of experimental data regarding the active residues of the two proteins, these were selected based on similarity hypotheses with other protein interactions and insights from previous studies. Molecular dynamics simulations were performed on both predicted models to explore the stability of the predicted complexes and assess potential binding regions. In conclusion, this study provides a computational characterization of the S100B and α-synuclein interaction offering a foundation for further sperimental investigations into its potential biological significance. Understanding this interaction could be relevant for determining whether S100B influences α-syn aggregation and toxicity, providing new insights into its role in neurodegenerative processes and its possible use as a therapeutic target.