To understand a protein’s function, it is necessary to visualize its structure, as well as the interactions that occur. There are many programs available to do so, such as Pymol, Chimera, and Coot, but these programs do have their shortcomings. Nevertheless, as scientific tasks become increasingly complex and interdisciplinary, there is a growing need to integrate visualization programs with other programming tools. Visualization tools play a key role in presenting results, especially if the results are data- driven and large. ALOKOMP [1] is a project that focuses on understanding the nature of allostery and allosteric communication. The project is specifically focused on oligomeric enzymes purine nucleoside phosphorylases [2] and has formed a database containing data from static molecular structures obtained from the Protein Data Bank (PDB), as well as dynamic data derived from molecular dynamics (MD) simulations. This database is ideal for discovering connections (pathways) between different enzyme regions, which are fundamental to allostery. To handle the extensive data contained in the database, we rely on programmatic methods and visualizations of the underlying data relationships. An integrated visual environment and relational data stored in the background will show us how we can deal with large amounts of data, but only if this data is suitably transformed and presented.