Prediction of acute toxicity of organophosphorus pesticides using topological indices

Topological indices were used in the prediction of the acute toxicity (intraperitoneal and oral LD₅₀) of organophosphorus pesticides on rats. Models with six variables for the prediction of LD₅₀-i.p. (r?=?0.849, Q ²?=?0.613) and eight variables for LD₅₀-oral (r?=?0.906, Q ²?=?0.701) were selected. External group and cross-validation by use of leave-n-out tests were also performed in order to assess the stability and the prediction performance of the selected topological models.     

基于启发式算法和支持向量机算法预测醛类化合物急性毒性

应用启发式算法(HM)和支持向量机算法(SVM)建立了88种醛类化合物对大鼠急性毒性的定量构效关系模型。应用ChemOffice2004软件进行化合物的结构输入,利用半经验方法进行分子结构优化,在CODDESA软件中计算出组成、拓扑、几何、电子和量子化学参数。并用启发式方法筛选出相对阳性电荷、氧原子数量、碳原子的最小亲核反应指数、双键相对数量、碳原子数量、碳氢键之间的最大交换能量、最大σ-σ键序和双键数量8个参数,在此基础上应该多元线性回归和支持向量机方法建立QSPR模型。两种方法均得到了较好的结果,HM和SVM的交互检验的相关系数分别为0.90和0.93;通过对模型的稳定性和预测能力比较,SVM建立的QSAR模型能够更好地预测醛类化合物对大鼠急性毒性LD50。     

4D-QSAR analysis of a set of ecdysteroids and a comparison to CoMFA modeling.

The ecdysteroid-responsive Drosophila melanogaster B(II) cell line is a prototypical homologous inducible gene expression system. A training set of 71 ecdysteroids, for which the -log(EC(50)) potencies in the ecdysteroid-responsive B(II) cell line were measured, was used to construct 4D-QSAR models. Four nearly equivalent optimum 4D-QSAR models, for two modestly different alignments, were identified (Q(2) = 0.76-0.80). These four models, together with two CoMFA models, were used in consensus modeling to arrive at a three-dimensional pharmacophore. The C-2 and C-22 hydroxyls are identified as hydrogen-bond acceptor sites which enhance activity. A hydrophobic site near C-12 is consistent with increasing activity. The side-chain substituents at C-17 are predicted to adopt semiextended "active" conformations which could fit into a cylinder-shaped binding pocket lined largely with nonpolar residues for enhanced activity. A test set of 20 ecdysteroids was used to evaluate the QSAR models. Two 4D-QSAR models for one alignment were identified to be superior to the others based on having the smallest average residuals of prediction for the prediction set (0.69 and 1.13 -log[EC(50)] units). The correlation coefficients of the optimum 4D-QSAR models (R(2) = 0.87 and 0.88) are nearly the same as those of the best CoMFA model (R(2) = 0.92) determined for the same training set. However, the cross-validation correlation coefficient of the CoMFA model is less significant (Q(2) = 0.59) than those of the 4D-QSAR models (Q(2) = 0.80 and 0.80).     

甲基丙烯酸三丁基锡酯与丙烯酸酯的共聚合

采用自由基引发剂对甲基丙烯酸三丁基锡酯和丙烯酸酯进行共聚合 ,其竞聚率用YBR法解出共聚方程的微分式而求得。甲基丙烯酸三丁基锡酯 (M1 )和丙烯酸甲酯 (M2 )、丙烯酸乙酯 (M2 )、丙烯酸丁酯 (M2 )共聚反应的竞聚率分别为r1 =1 .0 1± 0 .0 6,　r2 =0 .2 9± 0 .0 3;　r1 =1 .0 7± 0 .0 5 ,r2 =0 .38± 0 .0 3;　r1 =1 .1 1± 0 .0 5 ,　r2 =0 .45± 0 .0 3;　而所得到的甲基丙烯酸三丁基锡酯的Q、e值是它对各个单体的所有Q、e值的平均值 ,其Q =0 .5 7,e=- 0 .39     

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。     

三维全息原子场作用矢量用于HEPT类抗艾滋病药物的QSAR研究

采用本实验室新近提出的三维全息原子场作用矢量表征34个1-[(2-羟乙氧)甲基]-6-苯硫基胸腺嘧啶(HEPT)类抗艾滋病药物结构并与其活性建立定量构效关系模型. 采用逐步回归对变量进行筛选后, 运用多元线性回归(multiple linear regression, MLR)建模的复相关系数(R2cum)、交互校验的复相关系数(Q2cum)和模型的标准偏差(SD)分别为R2cum=0.928、Q2cum=0.883与SD=0.43, 均优于Hancsh报道的值(R2cum=0.911、Q2cum=0.863与SD=0.45). 模型具有良好的稳定性和预测能力, 表明三维全息原子场作用矢量能较好表征该类分子结构信息, 值得进一步推广应用.     

三维全息原子场作用矢量(3D-HoVAIF)用于神经氨酸酶抑制剂的结构表征与设计及定量构效关系(QSAR)研究

对100个神经氨酸酶抑制剂抗禽流感药物结构并与其活性建立定量构效关系模型。采用本实验室提出的三维全息原子场作用矢量(3D-HoVAIF)对100个神经氨酸酶抑制剂进行结构表征,然后采用逐步回归对变量进行筛选后,运用偏最小二乘建立3D-HoVAIF描述子与神经氨酸酶抑制剂活性之间的QSAR模型。结果表明:复相关系数(R),交互校验的复相关系数(Q2)和模型的标准偏差(SD)分别为R2=0.805、Q2=0.657和SD=0.936,模型具有良好的稳定性和预测能力,并对文献中23个药物和设计的32个化合物进行了预测。表明三维全息原子场作用矢量能较好表征该类分子结构信息值得进一步推广应用。     

Refinement and use of the approximate similarity in QSAR models for benzodiazepine receptor ligands

Several considerations for refining the approximate similarity measurements have been introduced in this paper: the use of topological invariants for the calculation of similarity indexes and the development of new similarity correction processes. The quality of the new similarity measurements obtained with the proposed methods has permitted the development of fast, cheap, and simple quantitative structure-activity relationship models for the prediction of biological activities of nonbenzodiazepine gamma-aminobutyric acid(A)/benzodiazepine receptor ligands (58 compounds). Internal and external validations were carried out for the approximate similarity matrices computed using different approaches. Satisfactory results which compare reasonably well with a 3D approach were obtained: Q2= 0.65 and standard error in cross validation SECV= 0.83 for the training stage; r = 0.79 and error in external prediction = 0.82 for the test step. In addition, the method proposed was compared with other topological approaches based on constitutional similarity and on fingerprints. Satisfactory results were obtained.     

普通有机分子或药物热分解稳定性的理论预测

采用密度泛函理论方法, 在B3LYP/6-31+G(d,p)水平上, 对任意选定的32个有机化合物或药物进行最低能量构象优化和结构参数理论计算. 建立了四极矩参数Q_ii与半数摩尔热分解函数Y_d(1/2)的相关方程, 其定量构性关系(QSPR)方程为Y_d(1/2)=-8.65747-3.8954Q_ii, 相关系数为r²=-0.99297, 交叉验证相关系数为XV-r²=0.99188, F检验结果为4237.343321. 训练集化合物的半数分解温度T_d(1/2)的平均绝对预测误差(AVEDEV)为14.70 K. 进一步利用该方程对测试集中43个分子进行预测验证, T_d(1/2)的预测值与实验值的相关系数为0.92304, Y_d的预测值与实验值的相关系数为0.99345, 证实了所建立方法的可靠性. 结构差异性分析表明, 训练集和测试集中的化合物均较均匀地分布在结构参数的3D空间中, 化合物结构具有较好的多样性和差异性.