QSAR Studies on the COX-2 Inhibition by 3,4-Diarylcycloxazolones Based on MEDV Descriptor

Selective inhibition of cyclooxygenase-2 (COX-2) might avoid the side effects of current available nonsteroidal antiinflammatory drugs while retaining their therapeutic efficacy. A novel variable selection and modeling method based on prediction is developed to construct the quantitative structure-activity relationships (QSAR) between the molecular electronegativity distance vector (MEDV) based on 13 atomic types and the biological activities of a set of selective cyclooxygenase-2 inhibitory molecules, 3,4-diarylcycloxazolones (DAA) plus indomethacin,naproxen, and celecoxib. Using multiple linear regression, a 5-variable linear model is developed with the calibrated correlation coefficient of 0.9271 and root mean square error of 0.17 in modeling stage and the validated correlation coefficient of 0.9030 and root mean square error of 0.20 in leave-one-out validation step, respectively. To further test the predictive ability of the model, 20 DAA compounds are picked up to construct a training set which is used to build a QSAR model and then the model is employed to predict the biological activities of the balance compounds. The predicted correlation coefficient and root mean square error are 0.9332 and 0.19, respectively.     

MEDV—13 for QSRR of 62 Polychlorinated Naphthalenes

A molecular electronegativity distance vector based on 13 atomic types (MEDV-13) is used to describe the structures of 62 polychlorinated naphthalene (PCN) congeners and related to the gas chromatographic relative retention indices (RIs) of PCNs. Using multiple linear regression,a 4-variable quantitative structure-retention relationship (QSRR) with the correlation coefficient of estimations(r) being 0.9912 and the root mean square error of estimations (RMSEE) being 31.4 and the correlation coefficient of prediction (q) and the root mean square error of predictions (RMSEP) in the leave-one-out procedure are 0.9898 and 33.76,respectively.     

分子电性距离矢量用于多溴联苯醚分子结构表达及色谱保留时间预测

应用分子电性距离矢量(MEDV)对多溴联苯醚(PBDEs)的209种同系物进行结构表征.通过多元线性回归的方法,建立了PBDEs定量结构-色谱保留(QSRR)关系的6个变量和5个变量的两种模型.两种模型的建模计算值复相关系数R均为0.995;用留一法(LOO)进行了交互检验,其复相关系数(R2cv)分别为0.987和0...     

无环醇~(13)C NMR化学位移与其结构参数的定量关系

用新颖的原子拓扑矢量Y_C、原子平衡电负性q_e、结构信息参数[N_H~i(i=α,β)]和γ校正参数对63个无环饱和脂肪醇的局部化学微环境进行了结构表征,并对化合物~(13)C NMR化学位移进行了QSSR研究.采用偏最小二乘回归得到模型的复相关系数R和标准偏差S分别为0.9915和2.4827;对353个碳原子~(13)C NMR化学位移的实验值与计算值的平均绝对误差仅为2.01×10~(-6).同时,采用留分法(Leave-molecule-out)和外检验方法测试模型的内部稳定性和外部预测能力.与文献结果比较,本研究所用参数少,且计算简便.     

Application of genetic algorithm‐support vector regression (GA‐SVR) for quantitative analysis of herbal medicines

In this paper, a genetic algorithm‐support vector regression (GA‐SVR) coupled approach was proposed for investigating the relationship between fingerprints and properties of herbal medicines. GA was used to select variables so as to improve the predictive ability of the models. Two other widely used approaches, Random Forests (RF) and partial least squares regression (PLSR) combined with GA (namely GA‐RF and GA‐PLSR, respectively), were also employed and compared with the GA‐SVR method. The models were evaluated in terms of the correlation coefficient between the measured and predicted values (Rp), root mean square error of prediction, and root mean square error of leave‐one‐out cross‐validation. The performance has been tested on a simulated system, a chromatographic data set, and a near‐infrared spectroscopic data set. The obtained results indicate that the GA‐SVR model provides a more accurate answer, with higher Rp and lower root mean square error. The proposed method is suitable for the quantitative analysis and quality control of herbal medicines. Copyright © 2012 John Wiley & Sons, Ltd.     

分子距边矢量研究链烃与醛酮的定量构效关系

按碳原子及键合特性分类定义并计算了链烃包括烷、烯,炔,双烯,烯炔烃的分子距离－边数矢量（ＭＤＥ）,将１５３个链烃的ＭＤＥ矢量与相应的沸点相关联,得到良好的线性模型,复相关系数Ｒ＝０．９９７６,均方根误差０．９９７５、ＲＭＳ＝４．７２Ｋ和Ｒ＝０．９９７２、ＲＭＳ＝５．１３Ｋ。结果表明模型具有良好的稳定性和预测能力。进一步对杂原用染色因子进行标识,提出了一种适用于含杂原子体系分子结构描述的ＭＤＥ矢量,