Computational Evaluation of Oleuropein Interactions with Alzheimer's Disease-Related Proteins Using Molecular Docking and Molecular Dynamics.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder associated with amyloid aggregation, tau pathology, and neuroinflammation. In this study, an integrated computational workflow combining ADMET prediction, PASS-based activity screening, molecular docking, and molecular dynamics (MD) simulations was employed to evaluate the interactions of oleuropein with five AD-related protein targets, including β-amyloid, tau, apolipoprotein E4 (ApoE4), triggering receptor expressed on myeloid cells 2 (TREM2), and complement protein C1q. ADMET and PASS analyses predicted pharmacokinetic properties and potential biological activities associated with neurodegenerative disease-related pathways. Docking analysis predicted favorable binding affinities across the investigated targets, with the strongest predicted interaction observed for the C1q protein (-7.5 kcal/mol). Molecular dynamics (MD) trajectory analyses, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), dynamic cross-correlation matrix (DCCM), principal component analysis (PCA), and distance-based metrics, were used to evaluate the dynamic behavior of the protein-ligand complexes during the simulations. The computational analyses suggested relatively stable interactions for tau, C1q, and TREM2 complexes, whereas β-amyloid and ApoE4 exhibited comparatively higher conformational variability during portions of the simulations. These findings provide a preliminary computational assessment of oleuropein interactions with AD-related proteins and may support future experimental studies investigating its potential biological relevance in neurodegenerative disease models.