Meurice Nathalie, Maggiora Gerald M, Vercauteren Daniel P
Department of Pharmacology and Toxicology, University of Arizona, College of Pharmacy, 1703 E. Mable, Tucson, AZ 85721, USA.
J Mol Model. 2005 Jun;11(3):237-47. doi: 10.1007/s00894-005-0264-7. Epub 2005 May 12.
A model system of four benzodiazepine-like ligands for the central benzodiazepine receptors (CBRs) and peripheral benzodiazepine receptors (PBRs)is examined using a genetic algorithm procedure (GAGS) designed for evaluating molecular similarity. The method is based on the alignment of reduced representations generated from the critical points of the electron density computed at medium crystallographic resolution. The results are further characterized by a comparison with alignments produced by MIMIC, a field-based superimposition method that matches both steric and electrostatic molecular fields. The alignments produced by the two methods are generally seen to be consistent. The relationships of the compounds' binding affinities for both CBRs and PBRs to the alignments determined by GAGS yield a set of structural features required for significant binding to benzodiazepine receptors. Benefits of using reduced representations for evaluating molecular similarities and for constructing pharmacophore models are discussed.
利用一种为评估分子相似性而设计的遗传算法程序(GAGS),研究了用于中枢苯二氮䓬受体(CBRs)和外周苯二氮䓬受体(PBRs)的四种苯二氮䓬样配体的模型系统。该方法基于在中等晶体学分辨率下计算的电子密度临界点生成的简化表示的比对。通过与MIMIC(一种基于场的叠加方法,可匹配空间和静电分子场)产生的比对进行比较,进一步表征了结果。两种方法产生的比对通常被认为是一致的。化合物对CBRs和PBRs的结合亲和力与由GAGS确定的比对之间的关系,产生了一组与苯二氮䓬受体显著结合所需的结构特征。讨论了使用简化表示来评估分子相似性和构建药效团模型的好处。