3D-pharmacophore analyses of transporter ligands for drug discovery studies in consideration of pharmacokinetics
3D-pharmacophore analyses of transporter ligands for drug discovery studies in consideration of pharmacokinetics
批准号:
18590037
负责人:
HIRONO Shuichi
金额:
$2.55万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
2006
资助国家:
日本
项目状态:
已结题
起止时间:
2006 至 2007
中文摘要
从药物开发的初始阶段就考虑药物动力学的优化,对于有效的药物设计和发现具有重要意义。由于转运蛋白在胃肠道、脑、肝、肾等组织细胞膜上表达,对药物的转运起着重要作用,因此,确定转运蛋白配体的三维药效团,分析转运蛋白与配体的相互作用,是当前合理药物设计和开发的关键。我们利用本实验室开发的基于配体的药物设计技术,对人有机阳离子转运蛋白1(organic Cation Transporter 1,hOCT 1)的配体进行了三维定量构效关系(3D-QSAR)分析,并与3D-QSAR进行了比较研究。其他方法生成的QSAR模型。结果表明,利用我们的方法可以得到具有良好统计量(q^2值)的3D-QSAR模型。本研究得到的hOCT 1配体的三维药效团由一个氢键供体和三个疏水原子团组成。该三维药效团与其他方法获得的药效团相似,但研究表明,对于数据集(测试集),我们的3D-QSAR模型在统计学上优于其他方法,以评估模型的质量。因此,我们认为我们的3D-QSAR模型是一个很好的模型,具有较高的预测性的生物活性的非同源化合物,具有不同的结构。
英文摘要
It is important for the effective drug design and discovery to consider the optimization of the pharmacokinetics from the initial stage of pharmaceutical developments. It is a key point in the current rational drug design and development to identify three-dimensional pharmacophores of the transporter ligands and analyze transporter-ligand interaction, because the transporter proteins express on various histionic cell membranes such as gastrointestinal, brain, liver, kidney to play an important role for the transport of drugs.In this study, we utilized the ligand-based drug design techniques developed in our laboratory to analyze three-dimensional quantitative structure-activity relationships (3D-QSAR) for the ligands of human Organic Cation Transporter 1 (hOCT1) and carry out the comparative study with a 3D-QSAR model generated from other methods. As a result, we were able to get the 3D-QSAR model with a good statistic (q^2 value) by analysis using our techniques. The three-dimensional pharmacophore of hOCT1 ligand obtained from this study consists of a hydrogen bond donor and three hydrophobic atomic groups. This three-dimensional pharmacophore is similar to one obtained from the other methods, but it is shown that our 3D-QSAR model is statistically better than one from other methods for the data set (test set) to evaluate the quality of the model. Thus it is thought that our 3D-QSAR model is a fine model with high predictivity of biological activity for non-homologous compounds which have various structures.
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