Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson's disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP(+). Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP(+) model. We hypothesised that analysis of protein-protein interaction networks modelling MPP(+) toxicity could identify proteins critical for mediating MPP(+) toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP(+) toxicity) enabled us to identify four proteins predicted to be key for MPP(+) toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP(+) toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP(+) toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.