非加性取代基对THPB多巴胺受体亲和力的free - wilson型人工神经网络分析

K. Schaper
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引用次数: 55

摘要

用两种不同的QSAR技术分析了最近发表的15种作为多巴胺受体拮抗剂的四氢原小檗碱(THPB)衍生物的脑多巴胺D2受体亲和力数据。与失败的Free-Wilson/Fujita-Ban分析相比,所研究的受体结合数据可以通过仅使用二元子结构指示变量的神经网络方法来描述。人工/计算神经网络能够识别亲和关系显著取决于同时存在或不存在两个或多个取代基。4-D图显示取代基对D2受体亲和力的非加性/变异性影响。
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FREE-WILSON-TYPE ANALYSIS OF NON-ADDITIVE SUBSTITUENT EFFECTS ON THPB DOPAMINE RECEPTOR AFFINITY USING ARTIFICIAL NEURAL NETWORKS
Recently published brain dopamine D2 receptor affinity data of 15 tetrahydroprotoberberine (THPB) derivatives acting as dopamine receptor antagonists have been analyzed by two different QSAR techniques. The following main results were obtained by this analysis: In contrast to an unsuccessful Free-Wilson/Fujita-Ban analysis the investigated receptor binding data could be described by a neural network approach using only binary substructural indicator variables. The artificial/computational neural network was able to recognize that the affinity depends significantly on the simultaneous presence or absence of two or more substituents. A 4-D plot demonstrates the non-additivity/-variability of substituent effects on D2 receptor affinity.
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