Immobilized Receptors In Drug Discovery

建立了一种新的高通量筛选方法，该方法基于在流动色谱系统中包含目标受体。在这种方法中，受体被固定在一个固体支架上，支架被包装成一个小柱。测试化学物质通过柱，通过固定的靶标，化合物从柱的开始到柱的结束所花费的时间与靶标和化合物之间相互作用的强度直接相关，即配体-受体复合物的结合亲和力。使用这种方法，复杂的化学和生物混合物可以在与疾病相关靶标相互作用和不相互作用的化合物之间快速分类。与此同时，与靶标结合的化合物本身在低、中、高亲和力的结合剂之间迅速分类。因此，该方法可以快速提供信息量大、信息量高的数据。我们已经开发了基于g蛋白偶联受体的筛选原型，使用阿片受体的kappa， mu和delta亚型，β -肾上腺素能受体和烟碱受体的各种亚型。基于烟碱受体的色谱柱已被用于筛选复杂的化学混合物，并已确定混合物中的竞争性激动剂和拮抗剂以及非竞争性抑制剂。采用非竞争性抑制剂和非线性色谱法进行了研究，结果表明该方法可用于非竞争性抑制剂的鉴定和表征。利用化学计量学分析建立定量构效关系（QSAR），所得方程可用于预测化合物的药理活性。分子模型研究已被用于描述和预测烟碱受体和非竞争性抑制剂之间的相互作用。基于计算机的研究已被用作专利申请的基础，题为“烟碱乙酰胆碱受体和相关配体门控离子通道受体的非竞争性抑制剂的识别和表征的基于计算机的模型”（参考编号：E-158-2003/0-US-01）。

A new method for high throughput screening has been developed based upon the inclusion of the target receptor in a flowing chromatographic system. In this approach, the receptor is immobilized on a solid support and the support packed into a small column. The test chemicals are passed through the column, over the immobilized target, and the time that it takes for the compounds to pass from the beginning of the column to its end is directly related to the strength of interaction between the target and the compound, i.e. the binding affinity of the ligand-receptor complex. Using this method, complex chemical and biological mixtures can be rapidly sorted between compounds that interact and do not interact with the disease-related target. At the same time, the compounds that bind to the target are themselves rapidly sorted between low, medium and high affinity binders. Thus, the method quickly provides a large amount of data with high information content. We have developed prototypes for the G-protein coupled receptor-based screening using the kappa, mu and delta subtypes of the opioid recpetor, beta-adrenergic receptors and various subtypes of the nicotinic receptor. The nicotinic receptor-based columns have been used to screen complex chemical mixtures and have identified competitive agonists and antagonists in the mixture as well as non-competitive inhibitors. A study using non-competitive inhibitors and non-linear chromatography was conducted and demonstrated that the method can be used to identify and characterize the non-competitive inhibitors. Chemometric analysis was used to develop quantitative structure-activity relationships (QSAR) and the resulting equations can be used to predict the pharmacological activity of a compound. Molecular modeling studies have been undertaken and used to describe and predict the interactions between the nicotinic receptors and non-competitive inhibitors. The computer-based studies have been used as the basis for a patent application entitled "Computer-based model for identification and characterization for non-competitive inhibitors of nicotinic acetylcholine receptors and related ligand-gated ion channel receptors" (ref number: E-158-2003/0-US-01).