3D-QSAR Study of Indol-2-yl Ethanones Derivatives as Novel Indoleamine 2,3-Dioxygenase (IDO) Inhibitors
3D-QSAR approach using kNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report here k-nearest neighbor molecular fiel...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | E-Journal of Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2012/368617 |
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| Summary: | 3D-QSAR approach using kNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report here k-nearest neighbor molecular field analysis (kNN-MFA)-based 3D-QSAR model for Indol-2-yl ethanones derivatives as novel IDO inhibitors. Overall model classification accuracy was 76.27% (q2 = 0.7627, representing internal validation) in training set and 79.35% (pred_r2 = 0.7935, representing external validation) in test set using sphere exclusion and forward as a method of data selection and variable selection, respectively. Contour maps using this approach showed that hydrophobic and steric effects dominantly determine binding affinities. The information rendered by 3D-QSAR model may lead to a better understanding of structural requirements of IDO inhibitors and can help in the design of novel potent molecules. |
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| ISSN: | 0973-4945 2090-9810 |