Table 3.
The performance of the predictive network models by three independent external validation network sets.
| Network sets | Substructure | P (L=20) | R (L=20) | eP (L=20) | eR (L=20) | AUC |
|---|---|---|---|---|---|---|
| Validation set A | FP4 | 0.021 | 0.126 | 3.62 | 4.73 | 0.671 |
| KR | 0.023 | 0.152 | 3.88 | 5.71 | 0.661 | |
| MACCS | 0.020 | 0.122 | 3.45 | 4.57 | 0.667 | |
| PubChem | 0.020 | 0.119 | 3.36 | 4.46 | 0.668 | |
| Validation set B | FP4 | 0.011 | 0.083 | 2.77 | 3.11 | 0.664 |
| KR | 0.014 | 0.128 | 3.35 | 4.82 | 0.654 | |
| MACCS | 0.010 | 0.069 | 2.35 | 2.60 | 0.659 | |
| PubChem | 0.010 | 0.071 | 2.45 | 2.68 | 0.668 | |
| Validation set C | FP4 | 0.043 | 0.119 | 3.37 | 4.45 | 0.669 |
| KR | 0.043 | 0.113 | 3.37 | 4.24 | 0.670 | |
| MACCS | 0.043 | 0.117 | 3.37 | 4.40 | 0.669 | |
| PubChem | 0.042 | 0.112 | 3.27 | 4.19 | 0.672 |
P: precision, R: recall, eP: precision enhancement, eR: recall enhancement, AUC: area under the receiver operating characteristic curve. L: the length of the newly predicted target list for each natural product.