Method is described to produce the protein semantic networks based on the information from PubMed/MEDLINE. In this work we used semantic score to assess the connectivity between two proteins based on the number of shared relevant or related articles. Using such score we created the semantic network for 150 human proteins belonging to different metabolic pathways. Analysis of the network has shown that proteins involved into the same molecular processes were separated into distinct subgraphs.