Mechanistic Insight into the Binding Profile of DCVJ and α-Synuclein Fibril Revealed by Multiscale Simulations.

Parkinson's disease (PD) is a serious neurodegenerative disease and is characterized by abnormal α-synuclein (α-syn) accumulation in Lewy bodies (LB) and Lewy neurites (LN), which makes α-syn an important imaging target for PD. An imaging probe that quantifies fibrillar α-syn can enhance the clinical diagnosis of PD and can also be used to evaluate the efficacy of therapeutics aimed at reducing the abnormal aggregation of the α-syn fibril in the brain. In this paper, we study the binding profile of fibrillar α-syn with a fluorescent probe 4-(dicyanovinyl)julolidine (DCVJ), which is being explored for identifying α-syn imaging agents. A multiscale simulation workflow including molecular docking, molecular dynamics, metadynamics, and QM/MM calculations was implemented. We find that DCVJ can bind to multiple sites of α-syn which are located either at the surface or in the core. Free energy calculations using implicit solvent models reveal that the most favorable binding mode for DCVJ is associated with the core binding site and is further confirmed by metadyamics simulation. Besides, a dynamic binding pathway is discovered, which reveals that DCVJ binds gradually into the core of the fibril passing through several intermediate states. The conformational arrest of the dicyano vinyl group in the fibrillar environment could explain the reason behind the fibril-specific fluorescence of DCVJ. Furthermore, based on hybrid QM/MM calculations, the molecular geometry of the dicyano vinyl group is found to be environment specific which explains why DCVJ serves as a staining agent for such fibrillar-like environments. Our results could be helpful for elucidating the binding mechanism of imaging tracers with the fibrillar form of α-syn and explain their fibrillar-specific optical properties, a knowledge that in turn can be used to guide the design and development of compounds with higher affinity and selectivity for α-syn using structure-based strategies.