Since new predictions from a unique algorithm such as DW could be limited by their restricted docking-cavity, wider grid-dependent ADV docking together with LELP normalization specificity were employed to improve prediction accuracies. Ranks rather than absolute docking-score comparisons were selected to derive consensus among DW, ADV and LELP leads 53, 69-72 . To our knowledge, the VENN diagrams used here for the first time, required trial-and-error attempts to optimize the numbers of leads from each program to identify common ranked leads. In this particular case, selecting 24-48 % of the top-ranks were required to propose 6 top-leads. The 6 DW, ADV and LELP top-leads predicted a similar chemotype, despite the high number of possibilities explored as discussed above, while the best top-lead was the 4040-child. Thus, the 4040-child reduced the LELP value (increased specificity) from 4.2 to 1.6 compared to its TTT-parent, despite increasing its molecular weight (363 to 554 Dalton). Additionally, the 4040child, lowered the cLogP increasing water solubility (from 3.1 to 0.5), increased the DW affinity (-92 to -139), and maintained the ADV affinity (0.7 to 0.8 nM) (Table ). Maximal numbers of Hydrogen and hydrophobic ADV interactions with the amino acids of the Omicron inner-cavity were also among the improvements of the 4040-child (Table ).