Table 5 The reported classification models for BCRP inhibitors and non-inhibitors
Year | Data size | Data set | Method | Descriptors | Model validation | Statistical results | Refs. | |
|---|---|---|---|---|---|---|---|---|
Training | Test | |||||||
2007 | 123 | 80 | 43 | OPLS-DA | Descriptors from SELMA software package | Y-rand | GATE = 0.79 | Matsson et al. [16] |
2009 | 122 | 83 | 39 | PLS-DA | Descriptors from DragonX version 3.0 | Y-rand | aNA | Matsson et al. [115] |
2013 | 109 | 30 | 79 | Pharmacophore modeling | NA | NA | MCCTE = 0.29, GATE = 0.66 | Pan et al. [11] |
2013 | 203 | 124 | 79 | NB | ECFP_6, FCFP_6 fingerprints | LOO CV | AUCTR(LOO CV) = 0.795, MCCTE = 0.69 | Pan et al. [11] |
2013 | 382 | 382 | NA | SVM, k-NN, RF, and consensus modeling | Dragon, MOE descriptors | Fivefold CV, Y-rand | BATR(fivefold cv) = 0.83 ± 0.04 (Consensus) | Sedykh et al. [121] |
2014 | 275 | 96 | Test: 32, external set: 147 | ensembles of ANN, ensembles of SVM | Descriptors from ADMET Modeler | NA | GATE = 0.87, GAExternal = 0.67 (ensembles of ANN) | Eric et al. [122] |
2014 | 780 | 780 | NA | NB | ECFP_6 fingerprints | Tenfold CV | GATR(tenfold CV) = 0.919, AUCTR(tenfold cv) = 0.854 | Montanari et al. [20] |
2015 | 394 | 197 | Test: 99, external set: 98 | SVM, k-NN, ANN, and Consensus Modeling | Dragon descriptors | NA | GATE = 0.878, MCCTE = 0.73; GAExternal = 0.745, MCCExternal = 0.46 (ANN) | Belekar et al. [21] |
2016 | aNA | NA | NA | GTM-kNNd, GTM-Bayes, RF, SVM, and k-NN | MOE descriptors | Fivefold CV with five repetitions | NA | Gimadiev et al. [123] |
2017 | 978 | 978 | NA | NB, LR, SVM, and RF | MACCS, Morgan, ECFP8 fingerprints, VolSurf descriptors | Tenfold CV, leave-sources-out validation | MCCTR(tenfold CV) = 0.65, AUCTR(tenfold CV) = 0.90 (LR) | Montanari et al. [22] |
2019 | 2799 | 2240 | 559 | NB, LR, SVM, k-NN, XGBoost, SGB, DNN and consensus modeling | MOE descriptors and Pubchem fingerprints | Fivefold CV | MCCTE = 0.812, AUCTE = 0.958, GATE = 0.911, BATE = 0.905 (SVM) | This study |