Computational property prediction, Pan-assay interference compounds (PAINS) and correlation analysis with anti-parasitic data. Physico-chemical descriptors and parameters related to ADMET were computed for all prepared compounds using QikProp (Schrödinger). Pearson correlations (R), R 2 values and two-tailed P-values for each property with the measured percentage of inhibition of T. brucei at 10 µM compound concentration were computed using SciPy and Python scripts written for the purpose. Only properties with a Pvalue equal to or below the statistical significance level α = 0.05 were considered further. To ensure robustness, a resampling analysis was performed by leaving every compound out once before recomputing the correlations. Properties with R > 0.40 or < -0.40 and P-value ≤ α in > 50% of the resampling correlation analyses were considered to be the most robust markers for the optimization for anti-parasitic effect. These properties were employed to prioritize compounds for synthesis as part of the Merged series, for details, see SI and Fig. .