In Silico Prediction of Cytochrome P450 2D6 and 3A4 Inhibition Using Gaussian Kernel Weighted k-Nearest Neighbor and Extended Connectivity Fingerprints, Including Structural Fragment Analysis of Inhibitors versus Noninhibitors
Inhibition of cytochrome P450 (CYP) enzymes is unwanted because of the risk of severe side effects due to drug−drug interactions. We present two in silico Gaussian kernel weighted k-nearest neighbor models based on extended connectivity fingerprints that classify CYP2D6 and CYP3A4 inhibition. Data u...
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Veröffentlicht in: | Journal of medicinal chemistry 2007-02, Vol.50 (3), p.501-511 |
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Sprache: | eng |
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