Table 7 Comparison of virtual screening performance of SVM with those of other methods
Method | Inhibitors in training set | Inhibitors in testing set | Virtual screening performance | ||||||
|---|---|---|---|---|---|---|---|---|---|
No of inhibitors | No of chemical families covered by inhibitors | No of inhibitors | No of chemical families covered by inhibitors | Percent of inhibitors in chemical families covered by inhibitors in training set | Yield | No and Percent of identified true inhibitors outside training chemical families | No and Percent of the 168K MDDR compounds identified as inhibitors | No and Percent of the 9,305 MDDR compounds similar to the known inhibitors identified as virtual inhibitors | |
Support Vector Machines | 1703 | 493 | 44 | 35 | 51.43% | 70.45% | 15(34.1%) | 1,496 (0.89%) | 719 (7.73%) |
Tanimoto Similarity | 36.84% | 9(20.5%) | 9,305 (5.54%) | 9,305 (100%) | |||||
K Nearest Neighbour | 38.64% | 10(22.7%) | 4,182 (2.49%) | 1,169 (12.57%) | |||||
Probabilistic Neural Network | Â | Â | Â | Â | Â | 50.0% | 13(29.5%) | 4,386 (2.60%) | 1,184 (12.72%) |