To better understand the systemic impact that an active ligand can have Alzheimer's disease, we took the 85 proteins studied in this work and built a protein-protein interaction network (PPIn-AD). Protein-protein interactions in the PPIn-AD were mapped using the STRING database . To ensure data robustness, interactions with scores of ≥ 0.7 were filtered based on their experimental and/or database STRING scores. Then, the PPIn-AD was expanded using NetworkX () by finding the first neighbors (1st shell) in the network constructed from the initial proteins. With this extended PPIn-AD users can expand the Ligand-Protein interaction network using the Expended LPIn button (Figure ). As a result, proteins that interact with selected AD targets (Figure ) will be added to the LPIn (orange nodes -Figure ). This extension is highly relevant, as for the first time a web-based tool such as AlzyFinder employs machine learning to perform ligand-based virtual screening together with network pharmacology analysis to obtain information on the potential therapeutic impact of a hit molecule.