Principal Component Analysis (PCA) was used to facilitate understanding of the data resulting from the CaverDock calculations. The data matrix consisted of 4358 ligands (objects) docked into six different protein states obtained from the CaverDock trajectories. The data for each ligand consisted of its minimum binding energy along the CaverDock trajectory and three percentage values representing the proportion of the trajectory during which the ligand was in contact with one, two, or all three individual units of the s-glycoprotein trimer. The data were autoscaled to unit variance and centred before analysis.