Estrogen compounds are suspected of disrupting endocrine functions by mimicking natural hormones, and such compounds may pose a serious threat to the health of humans and wildlife. Close attention has been paid to the...Estrogen compounds are suspected of disrupting endocrine functions by mimicking natural hormones, and such compounds may pose a serious threat to the health of humans and wildlife. Close attention has been paid to the prediction and molecular mechanisms of estrogen activity for estrogen compounds. In this article, estrogen receptor α subtype (ERα)–based comparative molecular similarity indices analysis (COMSIA) was performed on 44 estrogen compounds with structural diversity to find out the structural relationship with the activity and to predict the activity. The model with the significant correlation and the best predictive power (R2 = 0.965, Q2LOO = 0.599, R2pred = 0.825) was achieved. The COMSIA and docking results revealed the structural features for estrogen activity and key amino acid residues in binding pocket, and provided an insight into the interaction between the ligands and these amino acid residues.展开更多
AIM: Inhibitors of catechol-O-methyltransferase (COMT) have always been administered to improve the bioavailability of L-Dopa in the treatment of Parkinson disease (PD). A new three-dimensional quantitative structure-...AIM: Inhibitors of catechol-O-methyltransferase (COMT) have always been administered to improve the bioavailability of L-Dopa in the treatment of Parkinson disease (PD). A new three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis is performed to correlate the molecular fields with percent inhibition values. METHODS: Three predictive models were derived based on 36 previously reported COMT inhibitors employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodologies. RESULTS: The CoMFA model and CoMSIA model with steric and electrostatic field yielded cross-validated rcv2 0.585 and 0.528 respectively, whereas the conventional rncv2 were 0.979 and 0.891. The CoMSIA model with hydrophobic field exhibited rcv2 0.544 and rncv2 0.930. CONCLUSION: The derived models from CoMFA and CoMSIA all exhibit good prediction for both internal and external validations. The individual inspection of 3D contours generated from these models helps in understanding the possible region for structural modification of molecules to improve the inhibitory bioactivity. The 3D-QSAR models may be useful in designing and predicting novel COMT inhibitors.展开更多
采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA),对27个新型双酰基脲类化合物的杀蚊幼虫(Aedes aegypti L.)活性进行三维定量构效关系(3D-QSAR)研究.在CoMFA研究中,考察了网格点步长对统计结果的影响.在CoMSIA研究中...采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA),对27个新型双酰基脲类化合物的杀蚊幼虫(Aedes aegypti L.)活性进行三维定量构效关系(3D-QSAR)研究.在CoMFA研究中,考察了网格点步长对统计结果的影响.在CoMSIA研究中,系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响,发现立体场和氢键供体场的组合得到最佳模型.所建立的CoMFA和CoMSIA模型的非交叉验证相关系数r2值分别为0.828和0.841,并都具有较强的预测能力.CoMFA和CoMSIA模型的三维等值图不仅直观地解释了结构与活性的关系,而且为后续优化该系列化合物提供了理论依据.展开更多
基金National Natural Science Foundation of China (Grant No. 20507008)
文摘Estrogen compounds are suspected of disrupting endocrine functions by mimicking natural hormones, and such compounds may pose a serious threat to the health of humans and wildlife. Close attention has been paid to the prediction and molecular mechanisms of estrogen activity for estrogen compounds. In this article, estrogen receptor α subtype (ERα)–based comparative molecular similarity indices analysis (COMSIA) was performed on 44 estrogen compounds with structural diversity to find out the structural relationship with the activity and to predict the activity. The model with the significant correlation and the best predictive power (R2 = 0.965, Q2LOO = 0.599, R2pred = 0.825) was achieved. The COMSIA and docking results revealed the structural features for estrogen activity and key amino acid residues in binding pocket, and provided an insight into the interaction between the ligands and these amino acid residues.
文摘AIM: Inhibitors of catechol-O-methyltransferase (COMT) have always been administered to improve the bioavailability of L-Dopa in the treatment of Parkinson disease (PD). A new three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis is performed to correlate the molecular fields with percent inhibition values. METHODS: Three predictive models were derived based on 36 previously reported COMT inhibitors employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodologies. RESULTS: The CoMFA model and CoMSIA model with steric and electrostatic field yielded cross-validated rcv2 0.585 and 0.528 respectively, whereas the conventional rncv2 were 0.979 and 0.891. The CoMSIA model with hydrophobic field exhibited rcv2 0.544 and rncv2 0.930. CONCLUSION: The derived models from CoMFA and CoMSIA all exhibit good prediction for both internal and external validations. The individual inspection of 3D contours generated from these models helps in understanding the possible region for structural modification of molecules to improve the inhibitory bioactivity. The 3D-QSAR models may be useful in designing and predicting novel COMT inhibitors.
文摘采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA),对27个新型双酰基脲类化合物的杀蚊幼虫(Aedes aegypti L.)活性进行三维定量构效关系(3D-QSAR)研究.在CoMFA研究中,考察了网格点步长对统计结果的影响.在CoMSIA研究中,系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响,发现立体场和氢键供体场的组合得到最佳模型.所建立的CoMFA和CoMSIA模型的非交叉验证相关系数r2值分别为0.828和0.841,并都具有较强的预测能力.CoMFA和CoMSIA模型的三维等值图不仅直观地解释了结构与活性的关系,而且为后续优化该系列化合物提供了理论依据.
