Jiang Yu-Ren, Yang Yan-Yan, Chen Yu-Ling, Liang Zhong-Jie
College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China.
Curr Comput Aided Drug Des. 2013 Sep;9(3):385-95. doi: 10.2174/15734099113099990015.
A quantitative structure-activity relationship (QSAR) study has been carried out on acetylcholinesterase (AChE) inhibitors with comparative field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR). In order to investigate the effect of alignment on modeling and find out the best alignment strategy, three different alignment rules were applied to generate CoMFA and CoMSIA models. Statistical results of the highly significant models (CoMFA q² = 0.748, r² =0.996, predicted r² =0.789; CoMSIA q² =0.755, r² =0.973, predicted r² = 0.706; HQSAR q² = 0.884, r² = 0.973, predicted r² = 0.734) reveal considerable predictive ability. Analysis of the contour maps of CoMFA and CoMSIA models and the atomic contribution maps of HQSAR model may contribute to develop novel and potential AChE inhibitors.
利用比较分子力场分析（CoMFA）、比较分子相似性指数分析（CoMSIA）和全息定量构效关系（HQSAR）对乙酰胆碱酯酶（AChE）抑制剂进行了定量构效关系（QSAR）研究。为了研究比对方式对模型构建的影响并找出最佳比对策略，应用了三种不同的比对规则来生成CoMFA和CoMSIA模型。高度显著模型（CoMFA的q² = 0.748，r² = 0.996，预测r² = 0.789；CoMSIA的q² = 0.755，r² = 0.973，预测r² = 0.706；HQSAR的q² = 0.884，r² = 0.973，预测r² = 0.734）的统计结果显示出相当强的预测能力。对CoMFA和CoMSIA模型的等高线图以及HQSAR模型的原子贡献图进行分析，可能有助于开发新型潜在的AChE抑制剂。
