Melagraki Georgia, Afantitis Antreas, Sarimveis Haralambos, Koutentis Panayiotis A, Markopoulos John, Igglessi-Markopoulou Olga
School of Chemical Engineering, National Technical University of Athens, Athens, Greece.
Bioorg Med Chem. 2007 Dec 1;15(23):7237-47. doi: 10.1016/j.bmc.2007.08.036. Epub 2007 Aug 25.
This paper presents the results of a ligand-based virtual screening optimized procedure on 98 compounds which have been recently evaluated as inhibitors of genotype 1 HCV polymerase. First, quantitative structure-activity patterns are investigated for the selected compounds and then structural modifications are proposed to afford novel active patterns. An accurate and reliable QSAR model involving five descriptors that is able to predict successfully the HCV inhibitory potency against genotype 1 HCV polymerase is presented. Furthermore, the effects of various structural modifications on biological activity are investigated and biological activities of novel structures are estimated using the developed QSAR model. More specifically a search for optimized pharmacophore patterns by insertions, substitutions, and ring fusions of pharmacophoric substituents of the main building block scaffolds is described. The detection of the domain of applicability defines compounds whose estimations can be accepted with confidence.
本文介绍了对98种最近被评估为1型丙型肝炎病毒（HCV）聚合酶抑制剂的化合物进行基于配体的虚拟筛选优化程序的结果。首先，对所选化合物的定量构效关系模式进行研究，然后提出结构修饰以提供新的活性模式。提出了一个准确可靠的涉及五个描述符的定量构效关系（QSAR）模型，该模型能够成功预测针对1型HCV聚合酶的HCV抑制效力。此外，研究了各种结构修饰对生物活性的影响，并使用所开发的QSAR模型估计新结构的生物活性。更具体地说，描述了通过主构建体支架的药效基团取代基的插入、取代和环融合来寻找优化的药效基团模式。适用域的检测定义了其估计值可被置信接受的化合物。
