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 |
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|---|---|---|---|---|---|---|---|---|---|
| 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%) |
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| Probabilistic Neural Network | 50.0% | 13(29.5%) | 4,386 (2.60%) | 1,184 (12.72%) | |||||