De novo identification of potent ingredients for proteasome activation in MT101-5 using an AI-driven approach

Background and Purpose The complex composition of botanical drugs, with their multiple active constituents, poses a challenge to elucidating their pharmacological mechanisms of action (MoA). The development of computational methods for assessing MoA within a systems pharmacology framework has the potential to accelerate and improve the efficiency of botanical drug discovery and development. Methods Network analysis, incorporating prior knowledge such as biological pathways and gene expression data from patients with PD, was used to identify the pharmaceutically active ingredients of MT101-5 and elucidate their mechanisms of action related to proteasome activation in PD. To validate the artificial intelligence (AI) model's prediction that the active compound-mediated α-syn aggregate clearance occurs through enhanced proteasome activity, we employed a reporter-based screening to assess proteasome function within the ubiquitin-proteasome system. Diterpene components were assessed for their efficacy on motor function and dopaminergic neuron survival in an in vivo mouse model of MPTP-induced parkinsonism. Results Our findings demonstrated that diterpenes derived from Daphne Genkwa in MT101-5 inhibited α-syn fibril formation by restoring proteasome activation through Nurr1 activity. Two diterpenoids mitigated behavioural deficits and dopaminergic neuron loss in mice subjected to subacute MPTP administration (30 mg/kg/day for 5 days). Conclusion These results provide preliminary evidence supporting the therapeutic potential of the active ingredients in MT101-5 for the prevention or treatment of PD.