Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors:: Pharmacological characterization, computational modeling, and pharmacophore development
Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors:: Pharmacological characterization, computational modeling, and pharmacophore development
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DOI：
10.1124/mol.106.033233
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发表时间：
2007-05-01
影响因子：
3.6
通讯作者：
Bergmeier, Stephen C.
中科院分区：
文献类型：
--
作者：
McKay, Dennis B.;Chang, Cheng;Bergmeier, Stephen C.
作为一种涉及神经元尼古丁乙酰胆碱受体（nAChRs）的药物发现的新方法，我们的实验室针对nAChRs上的非激动剂结合位点（即非竞争性结合位点，负变容结合位点）。以培养的牛肾上腺细胞为神经元模型，研究67种甲基莱卡乌碱（MLA）类似物与天然α 3 β 4* nachr的相互作用。大量结构相关分子的可用性为非竞争性结合位点的药效团模型的发展提供了独特的机会。我们的MLA类似物抑制尼古丁介导的天然和重组α 3 β 4* nachr的功能激活，IC50值范围很广（0.9 - 115 μ M）。这些类似物对激动剂与天然或重组nachr结合的抑制作用很小或没有抑制作用，支持非竞争性抑制活性。基于这些数据，建立了两个具有较高预测能力的三维定量构效关系模型（比较分子场分析和比较分子相似指数分析）。这些计算模型被成功验证，并为MLA类似物与nachr的分子相互作用提供了见解。此外，还构建了药效团模型来分析和可视化对模拟结合位点的结合要求。药效团模型随后被应用于搜索结构多样的分子数据库，以前瞻性地识别新的抑制剂。从数据库挖掘中快速识别出8种分子，并成功地证明了体外抑制活性，这支持了这些计算模型作为有效检索抑制剂的新工具的实用性。这些结果证明了计算建模和药效团开发的有效性，这可能导致鉴定针对nachr上新位点的新治疗药物。
As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha 3 beta 4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha 3 beta 4* nAChRs with a wide range of IC50 values (0.9 - 115 mu M). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship ( comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.