Integrated metabolomics and molecular dynamics simulation reveals moupinamide and echitoserpidine as promising neuroprotective scaffolds from Persea americana seed extract.

Neurodegenerative diseases represent a growing global health burden, largely driven by population ageing and the absence of disease-modifying therapies. Current treatment strategies remain largely symptomatic, highlighting the need for the identification of novel neuroprotective agents targeting key pathological mechanisms such as impaired proteostasis and dysregulated signalling pathways. In this study, an integrated in silico workflow was employed to investigate LC-MS-annotated metabolites from Persea americana (avocado) seed extract for their binding interactions with two neurodegeneration-related protein targets, GPR52 and UCHL1. Untargeted LC-MS profiling was followed by metabolite annotation, target prediction, molecular docking, molecular dynamics (MD) simulations (50 ns for GPR52 and 100 ns for UCHL1), and binding free energy calculations using MM/GBSA and MM/PBSA approaches. Among LC-MS-putatively identified metabolites, moupinamide and echitoserpidine showed stable binding across molecular dynamics simulations, supported by consistent structural stability and favourable binding free energies against GPR52 and UCHL1 respectively. In contrast, scoulerine and piperine exhibited less favourable MM/PBSA binding free energies despite their moderate docking scores, indicating weaker predicted binding affinity. ADMET analysis revealed generally acceptable drug-like properties, but limitations in pharmacokinetics and central nervous system accessibility, particularly blood-brain barrier permeability, cardiotoxicity and metabolic stability. Overall, the results suggest that LC-MS-annotated metabolites from Persea americana seed extract may represent potential candidates for further investigation as modulators of GPR52 and UCHL1, with moupinamide and echitoserpidine emerging as the most promising scaffolds among the evaluated metabolites based on integrated docking, molecular dynamics, and binding free-energy analyses. However, further structural optimization and experimental validation are required to confirm their biological relevance and assess their suitability for neurodegeneration-related drug discovery.