Sekhar Y Nataraja, Nayana M Ravi Shashi, Ravikumar Muttineni, Mahmood S K
Bioinformatics Division, Department of Environmental Microbiology, Osmania University, Hyderabad, India.
Chem Biol Drug Des. 2007 Dec;70(6):511-9. doi: 10.1111/j.1747-0285.2007.00596.x. Epub 2007 Nov 13.
A 3D- QSAR model os Comparative Molecular Field Analysib (CoMFA) of 45 quinoline derivatives as metaborropic glutamate receptor subtype 1 (mGluR1) inhibitors wew investigated. The CoMFA analysis provided a model with q(2) value of 0.827 and r(2) value of 0.990, in which q(2) value of 0.827 and an r(2) value of 0.990, in which the good correlation between the inhibitory activities and the steric and electrostatic molecular field around the analoques was observed. The predictive ability of the models was validated using the set of 12 compounds that were not included in the training set of 33 compounds. These results provided further understanding of the relationship between the structural features of quinolone derivatives and its activities, which should be applicable to design and find new potential mGluR1 inhibitors.
研究了45种喹啉衍生物作为间位硼代谷氨酸受体亚型1（mGluR1）抑制剂的比较分子场分析（CoMFA）的三维定量构效关系（3D-QSAR）模型。CoMFA分析得到一个q(2)值为0.827、r(2)值为0.990的模型，其中观察到类似物周围的空间和静电分子场与抑制活性之间具有良好的相关性。使用未包含在33种化合物训练集中的12种化合物对模型的预测能力进行了验证。这些结果进一步加深了对喹啉衍生物结构特征与其活性之间关系的理解，这应适用于设计和寻找新的潜在mGluR1抑制剂。
