分子电性距离矢量用于三嗪类化合物的构效关系研究

采用分子电性距离矢量(Molecular Electronegativity Distance Vector,MEDV)表征了三嗪类化合物的分子结构,并运用多元线性回归(Multiple Linear Regression,MLR)建立了该类化合物结构与其发光菌和大型蚤毒性的定量结构-毒性相关(Quanti-tative Structure-Toxicity Relationship,QSTR)模型,同时采用留一法交互检验对所建模型进行了分析和验证,建模计算值的相关系数R分别为0.970和0.952,留一法交互检验预测值的相关系数RLOO分别为0.917和0.921,并进一步阐述了结构与毒性之间的关系。结果表明,三嗪环上π电子离域程度减小有利于毒性增加,侧链N上取代基数目增加,化合物毒性减小。为进一步预测该类化合物的毒性,进行药物筛选提供了有效的理论依据。     

Molecular Distance‐Edge Vector (μ) and Chromatographic Retention Index of Alkanes

A new method of quantitative structure‐retention relationship (QSRR) is proposed for estimating and predicting gas chromatographic retention indices of alkanes by using a novel molecular distance‐edge vector, called μ vector, containing 10 elements. The QSRR model (Ml), between the μ vector and chromatographic retention indices of 64 alkanes, was developed by using multiple linear regression (MLR) with the correlation coefficient being R = 0.9992 and the root mean square (RMS) error between the estimated and measured retention indices being RMS = 5.938. In order to explain the equation stability and prediction abilities of the M1 model, it is essential to perform a cross‐validation (CV) procedure. Satisfactory CV results have been obtained by using one external predicted sample every time with the average correlation coefficient being R = 0.9988 and average RMS = 7.128. If 21 compounds, about one third drawn from all 64 alkanes, construct an external prediction set and the 43 remaining construct an internal calibration set, the second QSRR model (M2) can be created by using calibration set data with statistics being R = 0.9993 and RMS = 5.796. The chromatographic retention indices of 21 compounds in the external testing set can be predicted by the M2 model and good prediction results are obtained with R = 0.9988 and RMS = 6.508.     

分子电性作用矢量法定量预测单质子化肽段离子迁移谱碰撞截面

基于分子二维图形特征得到了一种新的结构参数化方法:分子电性作用矢量(MEIV)。将其应用于113个单质子化肽段样本集的结构表征及离子迁移谱碰撞截面模拟和预测当中,通过严格检验所得到3个回归模型的复相关系数Rcum及交叉验证Q分别为:0.984、0.981、0.980和0.979、0.979、0.978。结果表明MEIV对有机分子结构及其性质具有良好的表达和预测能力。     

分子电性距离矢量用于稠环芳烃液相色谱保留值的QSPR研究

采用分子电性距离矢量(Molecular Electronegativity Distance Vector,MEDV)表征稠环芳烃类化合物的分子结构.分别运用多元线性回归(Multiple Linear Regres-sion,MLR)和偏最小二乘回归(PLS)建立了稠环芳烃类化合物结构与其液相色谱(LC)保留值的定量结构一性质关系(QSPR)模型,同时采用内部及外部双重验证的办法对所建模型稳定性能进行分析和验证,建模计算值、留一法交互检验预测值和外部样本预测值的复相关系数Rcum、RLOO、Qext分别为0.9970,0.9950,0.9925(MLR);0.9930,0.9790,0.9917(PLS).结果表明,MEDV能较好地表征该类分子结构信息,所建QSPR模型具有良好的稳定性和预测能力.为稠环芳烃类化合物分离、纯化、检测等方法的建立,提供有效的理论依据.     

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,     

多氯代二苯并呋喃在不同色谱柱上的气相色谱保留行为——定量结构-色谱保留关系(QSRR)的研究

 以一种拟原子的方式处理多氯代二苯并呋喃 (PCDFs)异构体中的苯环 ,将PCDFs异构体中的原子或基团分为 3类 ,即 :氯原子 (Cl) (记为“1”) ,氧原子 (O) (记为“2”)及拟原子 (B) (记为“3”)。在烷烃分子距边矢量的基础上 ,提出一种以基团为基准的分子距离边数矢量 (μ矢量 ) ,借助多元线性回归方法分别建立了多氯代二苯并呋喃在不同色谱柱上的色谱保留指数与表征其结构的 μ矢量间的定量结构 色谱保留关系 (QSRR)相关模型。各样本总体所建模型的相关系数均在 0 98以上。     

利用分子路径指数矢量对烷烃摩尔响应值的估计与预测

 利用分子路径指数矢量表示烷烃分子结构方法 ,结合多元线性回归算法及反传神经网络算法 ,对烷烃摩尔响应值进行处理 ,获得了比文献更佳的预测效果 ,交互校验的相关系数达 0 96 8以上。     

Synthesis,Biological Evaluation,and Molecular Modeling of Aza-Crown Ethers

Synthetic and natural ionophores have been developed to catalyze ion transport and have been shown to exhibit a variety of biological effects. We synthesized 24 aza- and diaza-crown ethers containing adamantyl, adamantylalkyl, aminomethylbenzoyl, and ε-aminocaproyl substituents and analyzed their biological effects in vitro. Ten of the compounds (8, 10–17, and 21) increased intracellular calcium ([Ca²⁺]_i) in human neutrophils, with the most potent being compound 15 (N,N’-bis[2-(1-adamantyl)acetyl]-4,10-diaza-15-crown-5), suggesting that these compounds could alter normal neutrophil [Ca²⁺]_i flux. Indeed, a number of these compounds (i.e., 8, 10–17, and 21) inhibited [Ca²⁺]_i flux in human neutrophils activated by N-formyl peptide (fMLF). Some of these compounds also inhibited chemotactic peptide-induced [Ca²⁺]_i flux in HL60 cells transfected with N-formyl peptide receptor 1 or 2 (FPR1 or FPR2). In addition, several of the active compounds inhibited neutrophil reactive oxygen species production induced by phorbol 12-myristate 13-acetate (PMA) and neutrophil chemotaxis toward fMLF, as both of these processes are highly dependent on regulated [Ca²⁺]_i flux. Quantum chemical calculations were performed on five structure-related diaza-crown ethers and their complexes with Ca²⁺, Na⁺, and K⁺ to obtain a set of molecular electronic properties and to correlate these properties with biological activity. According to density-functional theory (DFT) modeling, Ca²⁺ ions were more effectively bound by these compounds versus Na⁺ and K⁺. The DFT-optimized structures of the ligand-Ca²⁺ complexes and quantitative structure-activity relationship (QSAR) analysis showed that the carbonyl oxygen atoms of the N,N’-diacylated diaza-crown ethers participated in cation binding and could play an important role in Ca²⁺ transfer. Thus, our modeling experiments provide a molecular basis to explain at least part of the ionophore mechanism of biological action of aza-crown ethers.     

支持向量机用于多氯代萘毒性的定量构效研究

用偏最小二乘法(PLS)和留一交叉验证从90多个量子化学参数中筛选出极化率、分子量、部分原子上的净电荷、静电势等作为描述符,应用支持向量机(SVM)对20个多氯代萘同系物的三组毒性数据分别建立了定量构效关系模型.所得模型的交叉验证相关系数的平方分别为0.805、0.890、0.936.并将偏最小二乘法建模所得结果与之进行比较,结果表明,SVM预报能力优于PLS.     

Study on the Quantitative Structure-toxicity Relationships for the Selected Esters by Using Molecular Electronegativity Interaction Vector （MEIV）

The molecular electronegativity interaction vector (MEIV) was used to describe the molecular structure of 30 selected esters. Two excellent QSTR models were built up by using multiple linear regression (MLR) and partial least-squares regression (PLS). The correlation coefficients (R) of the two models were 0.945 and 0.941, respectively. The models were evaluated by performing the cross validation with the leave-one-out (LOO) procedure. The cross-verification correlation coefficients (RCV) of the two models were 0.921 and 0.919, respectively. The results showed that the models constructed in this work could provide estimation stability and favorable predictive ability.     

Structural Characterization of Volatile Components of Rosa Banksiae Ait for Estimation and Prediction of Their Linear Retention Indices and Retention Times

The molecular electronegativity-distance vector （MEDV） was used to describe the molecular structure of volatile components of Rosa banksiae Ait, and QSRR model was built up by use of multiple linear regression （MLR）. Furthermore, in virtue of variable screening by the stepwise multiple regression technique, the QSRR models of 10 and 6 variables and linear retention index （LRI） 10, 7 and 6 varieables were built up by combinating MEDV with the Ultra2 column GC retention time （tR） of 53 volatile components of Rosa Banksiae Air. The multiple correlation coefficients （R） of modeling calculation values of QSRR model were 0.906, 0.906, 0.949, 0.943 and 0.949, respectively. The cross-verification multiple correlation coefficients （RCV） were 0.903, 0.904, 0.867, 0.901 and 0.904, respectively. The results show that the models constructed could provide estimation stability and favorable predictive ability.     

取代基物化参数及其在药物定量构效关系中的应用

把取代基电性、立体及疏水性物化参数组合建立一种新取代基描述方法, 对环尿素类和N,N-二甲基-2-溴苯乙胺类衍生物进行结构表征. 对训练样本集通过逐步回归筛选变量, 所建多元线性回归方程R2分别为0.853和0.960, 留一法交互检验Rcv2分别为0.723和0.901；用预测集样本作外部预测, 所得Qext2分别为0.7617和0.7653. 结果显示：环尿素类化合物结构中苯环邻位立体、间位疏水、对位疏水及立体因素对该类药物抗HIV活性产生阻抑作用； N,N-二甲基-2-溴苯乙胺类苯环上取代基立体因素及对位给电子效应有利于提高肾上腺素能阻断活性.     

一种新的氨基酸描述子及其在肽QSAR中的应用

从天然氨基酸的25个结构与拓扑变量中经主成分分析得到一种新的氨基酸描述子——VSTV （principal component scores vector of structural and topological variables）.应用该描述子对以下3个体系,即血管紧张素转化酶抑制剂（2肽）、抗菌18肽和促凝血酶原激酶抑制剂（6～12肽）进行分子结构参数化表达,并在此基础上通过偏最小二乘回归(PLSR)建立定量构效关系(QSAR)模型,取得了优于文献的结果.模型的复相关系数（R2）和交互检验复相关系数（Q2）分别为0.789, 0.767; 0.996, 0.879; 0.981, 0.480.     

有机污染物的生物富集因子与拓扑指数的数学模型

依据价连接性指数(xi)、电性拓扑态指数(ej)及电性距离矢量(mk)构建239种有机污染物生物富集因子(FBC)的6参数QSFR(定量结构-生物富集因子相关性)模型, 不仅相关程度高, 而且所用自变量数少. 该模型的传统相关系数(R2)为0.821, LOO(levae-one-out)交互验证系数(Q2)为0.809, 证明具有良好的稳健性及预测能力. 根据进入该模型的6个参数可知, 影响有机污染物FBC的主要结构基团是: —C—、>C—、—O—、—X、—NH2以及分子的柔韧性、折叠程度等空间因素. 可以认为在生物富集过程中,“诱导契合机理”也发挥一定作用. 对自变量集进行正交变换, 既不影响模型的相关性, 又能降低其自相关性.     

多环芳烃分子结构的距边矢量表征及其气相色谱保留指数预测

 从分子图论拓扑学角度出发 ,提出用六元素组成的分子距边矢量VMDE表达上百个多环芳烃化学结构 ,对 10 0种多环芳烃的毛细管气相色谱保留值进行定量相关性研究 ,发现存在良好的线性相关关系 :IR=a +bVMDE,n =10 0 ,r =0 .988,其中a ,b为回归系数 ,可用于多环芳烃的色谱保留指数的分子建模与定量预测。