Bayesian models | MRP4inhib-ECFP_6 | MRP4inhib-FCFP_6 | BSEPinhib-ECFP_6 | BSEPinhib-FCFP_6 |
---|---|---|---|---|
Two-dimensional fingerprints | ECFP_6 | FCFP_6 | ECFP_6 | FCFP_6 |
10-fold XV ROC AUCa | 0.816 | 0.793 | 0.750 | 0.759 |
TP/FN/FP/TNa | 33/1/1/22 | 33/1/1/22 | 43/0/3/125 | 43/0/5/123 |
External validationb | 0.819 | 0.838 | 0.845 | 0.871 |
TP/FN/FP/TNb | 8/9/1/11 | 10/7/2/10 | 18/4/15/49 | 17/5/10/54 |
SE (%)b | 47.1 | 58.8 | 81.8 | 77.3 |
SP (%)b | 91.7 | 83.3 | 76.7 | 84.4 |
Q (%)b | 65.5 | 69.0 | 77.9 | 82.6 |
MCCb | 0.4123 | 0.4216 | 0.5238 | 0.5796 |
FN, false negative; FP, false positive; Q, overall prediction accuracy; SE, sensitivity; SP, specificity; TN; true negative; TP, true positive.
↵a XV ROC AUC based on training set compounds (green shaded region).
↵b Predictive performance validation by test set compounds (blue shaded region) (Ung et al., 2007; Khandelwal et al., 2008). SE = TP/(TP + FN); SP = TN/(TN + FP); Q = (TP + TN)/(TP + TN + FP + FN); MCC = [(TP * TN) – (FN * FP)]/[(TP + FP)(TP + FN)(TN +FN)(TN+FP)]1/2.