Receptor binding affinity based comparative QSAR study of testosterone derivatives

The quantitative structure activity relationship models of 22 testosterone derivatives have been made with the help of topological and quantum chemical parameters. The molecular modeling and geometry optimization have been carried out with CAChe Pro software. The calculations of topological and quantum chemical parameters have been done by MOPAC 2007. The statistical parameters are calculated by STATISTICA and SSP software. The study indicates that the topological parameters better predict the receptor binding affinity of testosterone derivatives, whereas quantum chemical parameters better predict androgenic potency of testosterone derivatives as indicated by correlation coefficient, standard error, standard error of estimation, p value, t value, and degree of freedom of the quantitative structure activity relationship (QSAR) models. The predicted activity values obtained by these QSAR models are close to observed activity. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012     

甲状腺激素受体配体化合物的定量构效关系(QSAR)研究

研究了68个TR（Thyroid Hormone Receptor,甲状腺激素受体）配体化合物的化学结构与活性的定量构效关系．采用实验室新近提出的三维原子场全息相互作用矢量,对化合物进行了结构参数化表达,采用逐步回归对变量进行筛选后,建立了定量构效关系模型．复相关系数和交互检验复相关系数R^2=0．767,Q^2=0．625（TRα）,R^2=0．734,Q^2=0．61（TRβ）．模型具有良好的稳定性和预测能力,证明了该三维原子场全息相互作用矢量在分子结构表征和生物活性预测上的适用性,并可应用于潜在和新型的TR配体化合物的设计和开发．     

三维原子场作用全息矢量用于二氢叶酸还原酶抑制剂及苦味二肽QSAR研究

将三维原子场作用全息矢量用于表征68个二氢叶酸还原酶抑制剂和48个苦味二肽结构, 分别以多元线性回归和偏最小二乘建模, 取得优良结果. 对前者建模得复相关系数Rmm2=0.893, 交互检验相关系数RCV2=0.853, 对后者建模得Rmm2=0.936, RCV2=0.849. 结果表明3D-HoVAIF能够较好表征两类分子结构, 具有物化意义明确及结果易解释特点, 值得进一步应用推广.     

三维全息原子场作用矢量用于吡咯类抗艾滋病药物QSAR研究

采用三维全息原子场作用矢量(3D-HoVAIF)对32个吡咯类抗艾滋病药物进行结构参数化表征,并与其活性建立定量构效关系。分别采用多元线性回归(MLR)和偏最小二乘(PLS)进行建模,建模的复相关系数(R2cum)、交互校验复相关系数(Q2cum)和模型的标准偏差(SD)分别为R2cum=0.914、Q2cum=0.812、SD=0.236(MLR);R2cum=0.836、Q2cum=0.719、SD=0.314(PLS),结果均优于文献值(R2cum=0.667,Q2cum=0.581,SD=0.420)。所建模型具有良好的稳定性和预测能力,表明3D-HoVAIF能够较好地表征该类分子的结构,值得进一步推广应用。     

P2Y12受体拮抗剂定量构效关系的研究

P2Y12受体拮抗剂是一类重要的抗血小板药物,研究分子活性与其结构参数的关系,对于合成新的P2Y12受体拮抗剂具有一定指导作用.选用178个结构多样的P2Y12受体拮抗剂分子作为数据集,随机选取了143个P2Y12受体拮抗剂作为训练集,剩余分子作为检验集.采用多元线性回归(MLR)方法和主成分回归分析(PCA)方法对每个分子的636个分子参数进行线性回归分析.MLR所建模型的结果为:训练集R2=0.800,检验集R2=0.834;PCA模型结果为:训练集R2=0.545,检验集R2=0.665.相比之下MLR法所建模型具有良好的预测性和可靠性.通过模型分析,确定了影响分子活性的关键因素.以上模型对筛选和合成新型高效P2Y12受体拮抗剂提供了一定理论指导.     

A 3D‐QSAR Study of Celebrex‐Based Pdk1 Inhibitors Using Comfa Method

A 3D‐QSAR study of celebrex‐based compounds of PDK1 inhibitors using comparative molecular field analysis (CoMFA) was carried out. The structures of the compounds were obtained using quantum chemistry calculation. CoMFA calculations for a number of grouped subsets of compounds gave q² values of correlation in the range from 0 to 0.8. The low q² values should be mainly due to the narrow span of biological activity. Calculations for several subsets of 11–13 compounds gave high q² values, with 0.5–0.8. Factors affecting the results of the calculations are discussed. Calculated results with high q² values suggest that further chemical modifications of the compounds could lead to enhanced activity and could be an aid in the design of celebrex‐based cancer drugs.     

QSAR studies of some side chain modified 7-chloro-4-aminoquinolines as antimalarial agents

The quantitative structure–activity relationship (QSAR) analyses were carried out for a series of new side chain modified 4-amino-7-chloroquinolines to find out the structural requirements of their antimalarial activities against both chloroquine sensitive (HB3) and resistant (Dd2) Plasmodium falciparum strain. The statistically significant best 2D QSAR models for Dd2, having correlation coefficient (r²) = 0.9188 and cross validated squared correlation coefficient (q²) = 0.8349 with external predictive ability (pred_r²) = 0.7258 and for HB3, having r² = 0.9024, q² = 0.8089 and pred_r² = 0.7463 were developed by multiple linear regression coupled with genetic algorithm (GA–MLR) and stepwise (SW–MLR) forward algorithm, respectively. The results of the present study may be useful on the designing of more potent analogues as antimalarial agents.     

DFT‐based QSAR study and molecular design of AHMA derivatives as potent anticancer agents

A quantitative structure–activity relationship (QSAR) of 3‐(9‐acridinylamino)‐5‐hydroxymethylaniline (AHMA) derivatives and their alkylcarbamates as potent anticancer agents has been studied using density functional theory (DFT), molecular mechanics (MM+), and statistical methods. In the best established QSAR equation, the energy (E_NL) of the next lowest unoccupied molecular orbital (NLUMO) and the net charges (Q_FR) of the first atom of the substituent R, as well as the steric parameter (MR₂) of subsituent R₂ are the main independent factors contributing to the anticancer activity of the compounds. A new scheme determining outliers by “leave‐one‐out” (LOO) cross‐validation coefficient (q) was suggested and successfully used. The fitting correlation coefficient (R²) and the “LOO” cross‐validation coefficient (q²) values for the training set of 25 compounds are 0.881 and 0.829, respectively. The predicted activities of 5 compounds in the test set using this QSAR model are in good agreement with their experimental values, indicating that this model has excellent predictive ability. Based on the established QSAR equation, 10 new compounds with rather high anticancer activity much greater than that of 34 compounds have been designed and await experimental verification. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007