The development of new drugs is traditionally focused on a single target protein. Only recently has it been recognized that drugs, i.e., small molecules, usually bind to several target proteins and thus have a wider spectrum of different effects. Natural substances are very interesting in this respect, as more than 32% of all drugs on the market today are derived from natural sources. However, natural substances are largely unexplored as their exact mechanisms of action are often unknown. In order to determine their actions, we can resort to computational methods. Computational screening enables the identification of potential target proteins, the explanation of observed effects and the prediction of novel effects of natural compounds. Computer algorithms enable targeted investigations, such as focused experimental tests on a specific target protein or a family of potential target proteins. Recently, we used computational screening to identify new potential target proteins for two natural compounds, curcumin and resveratrol, components of turmeric and grape, respectively. These two compounds have been shown to have anti-neuroinflammatory activity and therapeutic effects in the treatment of neurodegenerative diseases. We identified new  potential target proteins of these two compounds, the modulation of which with resveratrol and curcumin might help to explain their therapeutic effects in neurodegenerative diseases, in particular in the Alzheimer’s disease. We have discovered some already known target proteins and also new potential target proteins involved in neurodegeneration. Consisting of two complementary methods, inverse molecular docking and comparison of protein binding sites, our computational approach is general and can be applied to any natural or synthetic compound. Our results confirm the usefulness of this approach for the determination of new target proteins of natural compounds and for the investigation of their potential effects in the treatment of neurological diseases.