The similarity scores computed in Section 2.3.1 and ML models developed in Section 2.3.3 were used to establish a ranking for the three newly generated datasets: INDDS, DIADS and PYRDS. We calculated ppIC50 values for compounds derived from transformation rules using multiple ML regressors (SVM, Ridge and RF). For each compound, the mean and standard deviation of ppIC50 were then calculated across all regressors to establish a consensus metric between SVM, Ridge, and RF models. The mean ppIC50 values along with the similarity scores from Section 2.3.1, were then used to rank potential inhibitors based on both predicted biological potency and structural similarity. This process yielded the three focused libraries targeting S. aureus FabI inhibitors: INDDS, DIADS and PYRDS (Figure ).