Abstract
The support vector machine, as a novel type of learning machine, for the first time, was used to develop a QSAR model of 57 analogues of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl)pyrimidine-5-carb oxylate (EPC), an inhibitor of AP-1 and NF-/κB mediated gene expression, based on calculated quantum chemical parameters. The quantum chemical parameters involved in the model are Kier and Hall index (order3) (KHI3), Information content (order 0) (ICO), YZ Shadow (YZS) and Max partial charge for an N atom (MaxPCN), Min partial charge for an N atom (MinPCN). The mean relative error of the training set, the validation set, and the testing set is 1.35%, 1.52%, and 2.23%, respectively, and the maximum relative error is less than 5.00%.
| Original language | English |
|---|---|
| Pages (from-to) | 1288-1296 |
| Number of pages | 9 |
| Journal | Journal of Chemical Information and Computer Sciences |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jul 2003 |
| Externally published | Yes |
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