3. Select the atoms of the query. Remember, these should be minimally distorted and be only those of the main fragment, with the appropriate symmetry (e.g. the aromatic fragment of something like pyrene) 4. Unclick 'number of hydrogens' but keep 'number of bonds' for non-metal-coordinated atoms. Next, Next -5. Select the entire CCDC database (full geometric search, slow) or a previously identified subset from ConQuest, and any additional structures you've loaded, and move those to the right-hand screen. Next. 6. Select '3D coordinates determined' and any other parameters you'd like to narrow the search. 7. Hit "search" 8. When finished "save results" as "Overlaid hit fragments (.sd)" Note: a .sd file can be generated similarly from the protein data bank using their online interface; this data can be imported using this same procedure, or through passing a list of coordinates directly to scsd_collection from a compatible API. Your scsd_collection object is now set up properly to do your data science study-the available methods are gen_web_df and write_df which cache the database for later comparison through a webserver, and plot_pca to look at the principal component analysis results. Data are most easily accessed in the "complex_df" object, which is a Pandas DataFrame; plotting these variables with plotly.express can be performed easily.