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首页> 外文期刊>Journal of Medicinal Chemistry >A refined 3-dimensional QSAR of cytochrome P450 2C9: computational predictions of drug interactions.
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A refined 3-dimensional QSAR of cytochrome P450 2C9: computational predictions of drug interactions.

机译:细胞色素P450 2C9的精细3维QSAR:药物相互作用的计算预测。

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A ligand-based model is reported that predicts the Ki values for cytochrome P450 2C9 (CYP2C9) inhibitors. This CoMFA model was used to predict the affinity of 14 structurally diverse compounds not in the training set and appears to be robust. The mean error of the predictions is 6 microM. The experimentally measured Ki values of the 14 compounds range from 0.1 to 48 microM. Leave-one-out cross-validated partial least-squares gives a q2 value of between 0.6 and 0.8 for the various models which indicates internal consistency. Random assignment of biological data to structure leads to negative q2 values. These models are useful in that they establish a pharmacophore for binding to CYP2C9 that can be tested with site-directed mutagenesis. These models can also be used to screen for potential drug interactions and to design compounds that will not bind to this enzyme with high affinity.
机译:据报道,基于配体的模型可预测细胞色素P450 2C9(CYP2C9)抑制剂的Ki值。此CoMFA模型用于预测不在训练集中的14种结构多样的化合物的亲和力,并且看起来很可靠。预测的平均误差为6 microM。实验测量的14种化合物的Ki值在0.1到48 microM之间。留出一个交叉验证的局部最小二乘可得出各种模型的q2值在0.6和0.8之间,这表明内部一致性。生物数据对结构的随机分配导致负q2值。这些模型之所以有用,是因为它们建立了一种与CYP2C9结合的药效基团,可以通过定点诱变进行测试。这些模型还可用于筛选潜在的药物相互作用,并设计不会以高亲和力与该酶结合的化合物。

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