We created a network showing how proteins that are important in a model of Parkinson’s disease talk to (interact with) each other. We then mathematically analysed this network to determine which proteins were the most important for linking important cellular processes in Parkinson’s. Based on these mathematical predictions, we then tested if we could rescue cells by altering the levels of these proteins in cells. We found that raising levels of these proteins protected cells from toxicity as predicted by the network analysis. This study suggests that modelling and analysing networks may provide a novel way of identifying therapeutic targets in Parkinson’s disease.