A topological substructural approach for the prediction of P-glycoprotein substrates
A topological substructural approach for the prediction of P-glycoprotein substrates
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DOI：
10.1002/jps.20449
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发表时间：
2006-03-01
影响因子：
3.8
通讯作者：
Bermejo, M
中科院分区：
文献类型：
--
作者：
Cabrera, MA;González, I;Bermejo, M
一种拓扑子结构分子设计方法(TOPS-MODE)被用来预测一个给定的化合物是否为P-糖蛋白(P-gp)底物。建立了一个线性判别模型来将163个化合物的数据集分类为底物或非底物(91个底物和72个非底物)。最终模型对数据的拟合灵敏度为82.42%，特异度为79.17%，最终准确率为80.98%。通过使用外部验证集(40个化合物、22个底物和18个非底物)、5次完全交叉验证(每个周期去除40个化合物，良好预测率为80.50%)和上市药物外部测试集的预测(35个化合物，良好预测率为71.43%)对模型进行验证。这一方法证明了标准键距、极化率和Gasteiger-Marsilli原子电荷影响与P-gp的相互作用；暗示了TOPS模式描述符估计新药候选的P-gp底物的能力。用原始训练集(6-氟喹诺酮类)未涵盖的化合物家族来评估TOPS-MODE方法的潜力，最终预测的准确率为77.7%。最后，确定了对作为P-gp底物的6-氟喹诺酮类药物分类的正负亚结构贡献；证明了本方法在先导产生和优化过程中的可能性。(C)2006年Wiley-Liss，Inc.和美国药剂师协会。
A topological substructural molecular design approach (TOPS-MODE) has been used to predict whether a given compound is a P-glycoprotein (P-gp) substrate or not. A linear discriminant model was developed to classify a data set of 163 compounds as substrates or nonsubstrates (91 substrates and 72 nonsubstrates). The final model fit the data with sensitivity of 82.42% and specificity of 79.17%, for a final accuracy of 80.98%. The model was validated through the use of an external validation set (40 compounds, 22 substrates and 18 nonsubstrates) with a 77.50% of prediction accuracy; fivefold full cross-validation (removing 40 compounds in each cycle, 80.50% of good prediction) and the prediction of an external test set of marketed drugs (35 compounds, 71.43% of good prediction). This methodology evidenced that the standard bond distance, the polarizability and the Gasteiger-Marsilli atomic charge affect the interaction with the P-gp; suggesting the capacity of the TOPS-MODE descriptors to estimate the P-gp substrates for new drug candidates. The potentiality of the TOPS-MODE approach was assessed with a family of compounds not covered by the original training set (6-fluoroquinolones), and the final prediction had a 77.7% of accuracy. Finally, the positive and negative substructural contributions to the classification of 6-fluoroquinolones, as P-gp substrates, were identified; evidencing the possibilities of the present approach in the lead generation and optimization processes. (c) 2006 Wiley-Liss, Inc. and the American Pharmacists Association.