I’ve got an email from My NCBI about new BioAssay – Limit: Protein 3D Structure. AID: 2158 has Compounds Active: 287; Tested: 572; it’s exaclty that I was looking for. Based on this data, I’ve implemented new features that will available in upcoming 0.5 release. Interested users can check it out right away. The new feature allows you to plot Binding Energies to provide a bird’s-eye view of docking results. In addition, if you have corresponding BioAssay available, you can also plot ROC Curve next to Docking Results. ROC curves appear in many recent publications that prompted me to add this feature to PyRx. Google search on ROC Curve brought me to Receiver operating characteristic – Wikipedia. This page confused me more than it helped me, so I started searching for ROC curve further. I came across Let’s ROC that had the following article mentioned in the comments: Triballeau, N. et al. J Med Chem. 2005, 48, 2534-2547. This article is very well written and it helped me to better understand the use of ROC curves in Virtual Screenings.

This plot shows Docking Results and ROC Curve generated for AID: 2158 BioAssay. Note that results with lowest Binding Energy, as predicted by AutoDock, are active compounds. It might seem that overall AutoDock doesn’t do well because some of the points on ROC curve are below the diagonal. However, this all depends on the dataset chosen. If the dataset had only a few active compounds, then chances are, that it would have produced an ideal ROC curve. In that sence, ROC curve, by itself, is not informative, unless you have a plot of Docking Results like the way PyRx does.