雄激素受体干扰物的活性预测模型的研究

目的在于定量预测雄激素受体干扰物活性,并确定最佳建模方法。选择150个分子作为数据集,随机选38个分子作为检验集,其它分子为训练集。每个化合物分子计算了193个分子参数。通过采用多元线性回归和主成分回归等方法,建立数学模型,并用验证集检验了所建模型的预测能力。结果发现逐步筛选法和主成分分析方法所建模型都表现出较强的预测能力(应用于检验集的相关系数分别为R=0.61,R=0.52)。以上研究将有助于新药雄激素受体抑制剂的筛选和开发。     

结构多样性化合物沸点QSPR模型研究

在定量结构-性质/活性关系(QSPR/QSAR)研究中,分子结构的数值化和建立良好预测的数学模型是2个重要的问题.建立具有良好适应性有实际应用价值的模型是进行QSPR/QSAR的最终目标.本文针对148种来自不同植物挥发油的具有结构多样性化合物,分别采用主成分回归(PCR)、偏最小二乘(PLS)和遗传算法(GA)对其沸点与结构之间的定量结构性能关系进行了研究,用拓扑指数建立了沸点预测模型.结果表明,PLS模型的预测能力最佳,模型训练集的平均相关系数为0.996,平均训练偏差为7.05,检验集的平均相关系数为0.986,平均检验偏差为12.91.     

A novel set of Wiener indices

According to the definition of molecular connectivity and the definition of the Wiener index, a novel set of Wiener indices (mV(t)) were defined, named novel Wiener index. The potential usefulness of the novel Wiener index in QSAR/QSPR is evaluated by its correlation with a number of C(3)-C(8) alkanes and by a favorable comparison with models based on molecular connectivity index and Wiener index.     

Improved QSPR analysis of standard entropy of acyclic and aromatic compounds using optimized correlation weights of linear graph invariants

Entropy is calculated for a representative set of acyclic and aromatic compounds within the realm of QSAR/QSPR theory. Flexible topological molecular indices are chosen as independent variables in the fitting equations. The comparison with results derived from quantum mechanical calculations shows that the present approach gives better predictions. Some possible future extensions are pointed out.     

运用线性和非线性的方法预测烷基苯的沸点和摩尔体积(英文)

本文中建立了几个定量的模型预测80个烷基苯的沸点和79个烷基苯的摩尔体积.每个烷基苯的结构用其分子式得到的6个数字编码来描述.把这6个数字编码作为捕述符,运用多元线性回归,多元非线性回归和人工神经网络地方法来分别建立定量构效关系模犁.模型具有很好的预测性.沸点的3个预测模型,RMS偏差都小于9℃,摩尔体积的3个预测模型的RMS偏差都小于6 cm3·mol-1.     

双酚A型聚碳酸酯快速拉伸过程的分子动力学模拟

本文采用用分子动力学方法研究了双酚A型聚碳酸酯的快速拉伸过程.采用COMPASS力场和NPT系综研究了应力应/变关系、能量/应变关系等.应力-应变曲线的研究结果显示,前"屈服点"和后"屈服点"分别为0.14和0.17,应变≤0.05为"弹性区域".0.14<ε_(xx)<1.05的区域为"塑性区域",ε_(xx)>1.05属于"硬化"区.能量-应力关系的研究结果显示,在应力-应变呈线性关系的"弹性区域",体系的总势能及各势能分量随应变增大发生不规则的波动.为了从能量的角度解释PBC-PC在外部拉伸条件下的应变情况,本文还研究了体系总能量与各能量分项,与应变的关系,对链结构与能量分项的关系进行了讨论.     

一些有机锡化合物的QSPR和QSAR研究

应用量子化学HF/3-21G从头算法计算得量子化学参数,研究一些有机锡化合物的定量结构-性质关系和定量结构-活性关系。结果表明:有机锡化合物的正辛醇/水分配系数(logK_(ow))与分子极化率和分子范德华体积有关,而有机锡化合物对巨溞(daphnia magna)的急性毒性,则与分子最高占用轨道能和分子水化能有关,并建成它们的构效关系式。     

多氯联苯分子空间坐标与气相色谱相对保留时间的QSPR研究

应用ChemWindow和ChembioOffice绘图软件对209种多氯联苯化合物(PCBs)作图,通过分子最低能量模块计算得到其空间稳定构型,空间构型对应着分子空间坐标,固定坐标原点,得到同一坐标系的分子空间坐标。对PCBs分子空间坐标研究,定义了2个描述符,原子距离指数(Y_S)和分子空间特征指数(Y_F)。用多元线性回归方法获得了多氯联苯化合物的气相色谱相对保留时间(GCRRT)与该空间距离指数之间良好的定量结构一性质相关(QSPR)模型,定义的指数易于计算和运用。模型相关性良好(R=0.990),具有较高的预测能力和可靠性,从另一角度为QSPR研究提供一个新的思路。     

Application of novel atom-type AI topological indices to QSPR studies of alkanes

Atom-type AI topological indices derived from the topological distance sums and vertex degree further are used to describe different structural environment of each atom-type in a molecule. The multiple linear regression based on combined use of the proposed Xu index and AI indices is performed to develop high quality QSPR models for describing six physical properties (the normal boiling points, heats of vaporization, molar volumes, molar refractions, van der Waals' constants, and Pitzer's acentric factors) of alkanes with up to nine carbon atoms. For each of six properties, the correlation coefficient r of the final models is larger than 0.995 and particularly the decrease in the standard error (s) is within the range of 45-86% as compared with the simple linear models with Xu index alone. The agreement between calculated and experimental data is quite good. The results indicate the potential of these indices for application to a wide range of physical properties. The role of each of the molecular size and individual groups in the molecules are illustrated by analyzing the relative or fraction contributions of individual indices. The results indicate that the six physical properties of alkanes are dominated by molecular size while AI indices have smaller influence dependent on the studied properties. Moreover, the studies demonstrate that each atomic group contributes an indefinite value to properties dependent on its structural environment in a molecule or other groups present. The cross-validation using the more general leave-n-out method demonstrates the final models to be highly statistically reliable.     

环境化合物对鱼类毒性的定量构效关系研究

本研究基于定量构效关系方法预测环境化合物对鱼类的毒害(50%Lethal Concentration,LC50),并确定影响毒性关键分子的结构特征及几种模拟方法的比较.构建114个化学分子的数据集,随机选取85个75%分子为训练集,剩下的29个分子作为检验集,每个化学分子计算194个分子参数,分别采用逐步多元线性回归分析法(multiple linear regression,MLR)、主成分回归法(Principal Component Regression,PCA)和偏最小二乘法(Partial Least Square,PLS)构建定量结构-毒害关系(Quantitativestructure-activity relationships,QSTB)模型.用逐步多元线性回归分析法得出的训练集和预测集的实验值-logLC50与预测值-logLC50的相关系数分别为R2tr=0.86,R2te=O.83,说明该模型可靠性和鲁棒性较高;主成分回归法用8个主成分,其训练集和预测集的实验-logLC50与预测-logLC50的R2tr=0.81,R2te=O.77;偏最小二乘法用了5个潜变量,其训练集和预测集的实验-logLC50与预测-logLC50的R2tr=0.88,R2te=0.85.MLR方法得出化合物对鱼类的毒害影响较大的分子参数,主要分属电拓扑状态参数(SssO,SsCl,SdCH2,SsNH2)、分子连接指数(Xvo)以及修正Kappa指数(Ka2).以上研究对预测环境化合物的鱼类毒害(LC50),以及从机理上加深对有机物的毒性作用机理提供重要价值.     

多氯联苯定量结构-性质的关系

基于定量结构-性质相关(QSPR)研究多氯联苯化合物(PCBs)的性质具有重要意义。用分子负电性距离矢量(MEDV)表征209个PCBs的分子结构,同时用多元线性回归(MLR)技术和逐步回归结合留一法交叉检验筛选模型变量,建立多氯联苯类化合物的水溶性(LgS_w)、土壤吸附性(LgK_(oc))、色谱保留指数(RRI)、水溶液活度系数(LgY_w)、总分子表面积(TSA)与MEDV的QSPR模型,其线性相关系数(R)分别为0.9651,0.9692,0.9968,0.9111,0.9960。继用留一法和外部样本检验模型稳定性能,其相关系数(R_(CV),Q_(ext))分别为0.9611、0.9812;0.9572、0.9845;0.9941、0.9984;0.9980、0.9412;0.9953、0.9998。结果表明:所建QSPR模型均稳定性和预测能力良好。     

Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.     

量子化学参数用于脂肪族化合物分配系数的QSPR研究

采用ChemOffice 8.0中的MOPAC-AM 1量子化学方法计算149种脂肪族化合物的6种量子化学参数,取142个化合物作为样本集,用多元逐步回归分析法建立定量结构相关(QSPR)模型.模型能预测好脂肪族化合物的正辛醇/水分配系数(logP).logP平均误差为0.176个对数单位,模型的稳健性检验结果表明,模型中自变量无相关关系,残差呈正态分布.预测7个样本以验证模型,表明该模型的预测能力较好.     

烃类物质闪点定量构效的关系

应用CODESSA软件计算300种烃类物质的分子结构描述符,用启发式回归(HM)、最佳多元线性回归(B-MLR)法,以筛选出来的分子描述符建立线性回归模型.用B-MLR法所选4个描述符作为支持向量机(SVM)的输入,建立非线性模型.预测结果表明:所建模型稳健,泛化能力强,预测误差小.非线性模型(R2=0.9884,RMSE=8.7570)的性能优于线性回归模型(HM:R2=0.9815,RMSE=11.0653;B-MLR:R2=0.9814,RMSE=11.1041),预测的效果令人满意.