Department of Pharmaceutical Sciences, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.
J Chem Inf Model. 2011 Oct 24;51(10):2482-95. doi: 10.1021/ci200317s. Epub 2011 Sep 14.
Cytochrome P450 inhibitory promiscuity of a drug has potential effects on the occurrence of clinical drug-drug interactions. Understanding how a molecular property is related to the P450 inhibitory promiscuity could help to avoid such adverse effects. In this study, an entropy-based index was defined to quantify the P450 inhibitory promiscuity of a compound based on a comprehensive data set, containing more than 11,500 drug-like compounds with inhibition against five major P450 isoforms, 1A2, 2C9, 2C19, 2D6, and 3A4. The results indicated that the P450 inhibitory promiscuity of a compound would have a moderate correlation with molecular aromaticity, a minor correlation with molecular lipophilicity, and no relations with molecular complexity, hydrogen bonding ability, and TopoPSA. We also applied an index to quantify the susceptibilities of different P450 isoforms to inhibition based on the same data set. The results showed that there was a surprising level of P450 inhibitory promiscuity even for substrate specific P450, susceptibility to inhibition follows the rank-order: 1A2 > 2C19 > 3A4 > 2C9 > 2D6. There was essentially no correlation between P450 inhibitory potency and specificity and minor negative trade-offs between P450 inhibitory promiscuity and catalytic promiscuity. In addition, classification models were built to predict the P450 inhibitory promiscuity of new chemicals using support vector machine algorithm with different fingerprints. The area under the receiver operating characteristic curve of the best model was about 0.9, evaluated by 5-fold cross-validation. These findings would be helpful for understanding the mechanism of P450 inhibitory promiscuity and improving the P450 inhibitory selectivity of new chemicals in drug discovery.
细胞色素 P450 抑制混杂性对临床药物相互作用的发生有潜在影响。了解分子性质如何与 P450 抑制混杂性相关，有助于避免此类不良反应。在这项研究中，基于包含超过 11500 种具有抑制五种主要 P450 同工型（1A2、2C9、2C19、2D6 和 3A4）能力的类药性化合物的综合数据集，定义了一个基于熵的指数来量化化合物的 P450 抑制混杂性。结果表明，化合物的 P450 抑制混杂性与分子芳香性中度相关，与分子脂溶性轻微相关，与分子复杂性、氢键供体能力和 TopoPSA 无关。我们还应用该指数基于相同数据集量化了不同 P450 同工型对抑制的敏感性。结果表明，即使对于底物特异性的 P450，也存在惊人的 P450 抑制混杂性，抑制敏感性的顺序为：1A2>2C19>3A4>2C9>2D6。P450 抑制效力和特异性之间没有相关性，P450 抑制混杂性和催化混杂性之间存在轻微的负相关性。此外，还使用支持向量机算法和不同指纹构建了分类模型，以预测新化学物质的 P450 抑制混杂性。通过 5 折交叉验证评估，最佳模型的接收者操作特征曲线下面积约为 0.9。这些发现有助于理解 P450 抑制混杂性的机制，并在药物发现中提高新化学物质的 P450 抑制选择性。
