分子三维投影法在苯酚类化合物构效关系研究中的应用

对苯酚类化合物进行三维投影得到了5个形状参数,将其与3个Am指数及8个量子化学参数相结合.由最佳变量子集回归法对变量进行了压缩与选择,运用多元回归分析和人工神经网络法分别构造了预测数学模型,得到了满意的结果.     

一种运动检测算法在无人机视频遥感上的应用

提出了一种基于灰度投影与位平面匹配的图像全局运动估计算法,并将其应用于无人机图像稳定系统中.算法采用灰度投影获取全局运动,用网格检测和灰度切分图精确匹配的方法获取更准确的运动数据.由于算法中使用自适应性的灰度切分层选择和基于灰度投影的运动估计缩小搜索区域,使算法效率在空间复杂度和时间复杂度上得到提高,具有较好的实时性和对影像的适应性.     

CO分子结点电子结构和输运性质的第一原理研究

采用基于密度泛函理论(DFT)的非平衡态格林函数方法(NEGF), 计算了CO分子结点低偏压下的电流和电导. 通过系统透射谱、投影态密度(PDOS)以及分子自洽投影哈密顿量(MPSH)本征态的分析将透射通道与局域分子轨道联系起来, 从系统电子结构解释了其传输性质. 讨论了电荷转移对系统电导的影响.     

光谱多元分析的校正模型检验及干扰物的检出

提出了一种在校正模型不确定时分析体系的光谱多元分析方法,首先构造投影阵以检验校正模型的合理性,通过检验可以发现分析体系是否含有其它不纯物,继用不纯物在投影空间中的矢量与可能存在物质的投影光谱进行检索比较,检出不纯物并测出各组份含量.将此法应用于3个分析体系,获得满意的结果.     

多元曲线分辨等方法和红外光谱用于二硝基五亚甲基四胺的合成反应机理研究

通过红外光谱在线监测强酸催化下硝酰胺、甲醛和氨水合成二硝基五亚甲基四胺(DPT)的反应过程, 利用渐进因子分析(EFA)、直观推导式演进特征投影法(HELP)和多元曲线分辨-交替最小二乘法(MCR-ALS)等化学计量学方法对反应过程获得的红外光谱信息进行解析, 得到了各组分纯物质的浓度变化曲线和对应的红外光谱, 并把多元曲线分辨-交替最小二乘法与直观推导式演进特征投影法的分析结果进行比较, 得出可相互验证的一致结论, 以此推测出该反应合理的反应机理. 化学计量学方法对在线红外光谱信息的分辨可以快速有效地反映DPT合成过程中各组分的浓度和红外光谱变化情况, 对其反应机理研究具有重要指导意义.     

二维色谱/光谱重叠峰的定性定量方法研究(Ⅱ)——投影降秩分辨法与大气飘尘中多环芳烃的测定

提出了一种新的联用色谱定性定量方法--投影降秩分辨法.该法可不经对重叠组分的逐一分辨直接对目标组分进行定性定量分析.以实际分析体系大气飘尘中多环芳烃菲、蒽、萤蒽和芘为目标组分,成功地进行了直接定性定量分析.     

主成分分析用于实时直接分析飞行时间质谱法判定中性笔字迹的形成时间

采用实时直接分析飞行时间质谱法,对同一种墨水6个不同时间书写的48个样本字迹进行分析,建立其质谱指纹图谱,再运用主成分分析法对数据进行投影。结果表明:48个样本字迹被分为6类,与已知的样本字迹形成时间分类一致。采用所建立的主成分投影,识别6个未知样本,结果达到分离聚类。     

中药丹参高效液相色谱重叠峰的解析

采用超临界CO2萃取方法对丹参中的脂溶性成分进行提取,利用高效液相等度分离方法对丹参脂溶性成分进行分离,再结合启发渐进式特征投影法和固定尺寸移动窗口渐进因子分析法对未能完全分离的重叠峰进行解析,得到了比较满意的结果.     

兴安落叶松针叶挥发油的GC-MS和启发渐进式特征投影法分析

采用水蒸气蒸馏法提取兴安落叶松针叶挥发油,利用气相色谱.质谱(GC-MS)联用对挥发油进行成分测定,并对其重叠色谱峰采用启发渐进式特征投影(HELP)法进行分辨,得到各组分的纯色谱峰和质谱,然后采用峰面积归一化法确定各化合物的相对含量.共分离出110种化合物,鉴定了70种化合物,占挥发油总量的93.09%,其中单萜、倍半萜和二萜的含量分别为31.92%、53.29%和6.91%.     

GC-MS结合保留指数对中药挥发油的定性

利用GC-MS联用和化学计量学方法,对6种中药挥发油进行分析,对其中的重叠色谱峰采用直观推导式演进特征投影法(HELP)法进行了分辨,同时计算了各组分的程序升温保留指数,通过质谱库定性.得到共有成分32个.结果表明,保留指数有很好的重复性,可与质谱库结合用作物质的定性.     

3D-QSAR Study on the Inhibitory Activity of Flavonoids on PIM-1 Kinase

20 Typical flavonoids were selected for study on the interaction between them and PIM-1 kinase with the comparative molecular field analysis method(CoMFA) as well as the comparative molecular similarity index analysis method(CoMSIA) based on molecule docking.3D-QSAR models between these flavonoids and receptor PIM-1 kinase were established.The obtained optimal cross-validation correlation coefficient Q2 for CoMFA model was 0.582,and the non-cross-validation correlation coefficient R2 was 0.955;the corresponding values for CoMSIA model were 0.790 and 0.974,respectively.These two models showed fairly fine stability and predictive ability.In addition,molecule docking results revealed the key residues in the receptor cavity and their specific action ways with flavonoids.     

Semi-empirical topological method for the prediction of the chromatographic retention of cis- and trans-alkene isomers and alkanes.

A new index is proposed for the prediction of the chromatographic retention of the cis- and trans-n-alkene isomers and alkanes. This index is based on the hypothesis that the chromatographic retention of the molecule is due to the interaction of each carbon atom with the stationary phase, and consequently the index is reduced by its neighbours' steric effects. The topological values are obtained by a numerical approximation considering the general behaviour of the chromatographic retention of the compounds. The simple linear regressions between the chromatographic retention and the index proposed for all branched alkanes and also isomers of the studied straight-chain C5 and C14 alkenes (1-ene, cis- and trans-2-, 3-, 4-, 5-, 6- and 7-enes) is very good (the correlation coefficient is r = 0.9999), and the elution sequence is correct for most of them. The models have a high predictive ability, as established by cross-validation values (r2cv). Thus, this new method, different from those already existent, can be used as complementary tool for the elucidation of the molecular structure, or prediction of the chromatographic retention of the cis- and trans-alkene isomers and branched alkanes. It could be extended with success, in the future, to the other types of compounds.     

Comments on exclusion of polymer chains from small pores and its relation to gel permeation chromatography.

Some criticisms of our theoretical treatment of the partial exclusion of flexible-chain polymers in solution from cavities of macromolecular size and its application to gel permeation chromatography are examined. In other discussion, it is confirmed by simple reasoning that the identification, explicit or implicit in various studies, of the mean projection of a polymer molecule onto a line as a characteristic dimension governing the extent of permeation of simple pores does not depend on specific molecular models. Our previous calculation of permeation by certain random-flight branched-chain species is shown to lead, incidentally, to the mean projection for these structures. From relations between the mean projection and the hydrodynamic volume of a molecule, it appears that the product of intrinsic viscosity and molecular weight is not a common calibration factor for elution of all molecular species from a gel chromatographic column, but theory and experience do support the validity of this correlation among solutes with similar molecular architecture.     

用拓扑指数和神经网络研究有机污染物的生物富集因子

在修正Randic的分子连接性指数和连接矩阵的基础上, 定义新型分子连接性指数(mF), 并计算了239种有机污染物的分子连接性指数(mF). 用其1F构建了239种有机污染物生物富集因子(lgBCF)的QSAR模型, 该模型判定系数(R2)及逐一剔除法(LOO)的交互验证系数(Q2)分别为0.747和0.742. 而用1F和4个电性距离矢量(Mk)构建的五元QSAR模型的R2及Q2分别为0.829和0.819. 结果表明, 从统计学的角度, 该模型具有高度的稳定性及良好预测能力. 从此模型可知, 有机污染物BCF的主要影响因素是—C—, ＞C—, —O—, —S—, —X等分子结构碎片以及分子的柔韧性、折叠程度等空间因素. 将5个结构参数作为人工神经网络的输入层结点, 采用5∶26∶1的网络结构, 利用BP算法, 获得了一个令人满意的QSAR模型, 其R2和标准偏差s分别为0.987和0.157, 表明lgBCF与这5个参数具有良好的非线性关系. 从上可见, 新建的连接性指数1F以及电性距离矢量与有机物的生物富集因子具有良好的相关性, 可望在物质构效关系研究中获得广泛的应用.     

多溴代芴热力学性质的理论预测研究

为了预测环境污染物多溴代芴的热力学性质,计算了60种多溴代芴的分子连接性指数、电性距离矢量指数、电性拓扑状态指数以及分子形状指数.采用多元线性回归的方法建立了多溴代芴化合物的标准生成焓(Δ_fH~0)、标准熵(S~0)、标准生成吉布斯自由能(Δ_fG~0)及等容热容等热力学性质的QSPR相关性模型,方程的相关系数值均在0.99以上.与相关文献的相关系数R和标准误差S进行比较,该模型具有良好的预测能力和稳定性.     

Idealization of correlations between optimal simplified molecular input-line entry system-based descriptors and skin sensitization

The Index of Ideality of Correlation (IIC) is a new criterion of the predictive potential for quantitative structure–property/activity relationships. The value of the IIC is a mathematical function sensitive to the value of the correlation coefficient and dispersion (expressed via mean absolute error). The IIC has been applied to develop QSAR models for skin sensitization achieving good predictive potential. The ‘ideal correlation’ is based on elementary fragments of simplified molecular input-line entry system (SMILES) and on the taking into account of the total numbers of nitrogen, oxygen, sulphur and phosphorus in the molecule.     

Structural Characterization and Toxicity Prediction of Some Organic Compounds

A new molecular structural characterization(MSC)method called molecular vertexes correlative index(MVCI)was constructed in this paper.The index was used to describe the structures of 45 compounds and a quantitative structure-activity relationship(QSAR)model of toxicity(–lgEC50)was obtained through multiple linear regression(MLR)and stepwise multiple regression(SMR).The correlation coefficient(R)of the model was 0.912,and the standard deviation(SD)of the model was 0.525.The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations.The Leave-One-Out(LOO)Cross-Validation(CV)correlation coefficient(RCV)was 0.816 and the standard deviation(SDCV)was 0.739,respectively.For the external validation,the correlation coefficient(Rtest)was 0.905 and the standard deviation(SDtest)was 0.520,respectively.The results showed that the index was superior in molecular structural representation.The stability and predictability of the model were good.     

Single molecule fluorescence correlation spectroscopy of single apoptotic cells using a red-fluorescent caspase probe

The detection of single molecules in single cells has enabled biochemical analyses to be conducted with high sensitivity and high temporal resolution. In this work, detection of apoptosis was studied by single molecule fluorescence correlation spectroscopy (FCS) in single living cells. Caspase activity was assayed using a new red fluorogenic probe that avoids the spectral overlap of green fluorescent probes and cell autofluorescence. This new probe, 2SBPO-Casp, was synthesized by coupling a water-soluble Nile Blue derivative (2SBPO) to an aspartic acid residue. Upon apoptosis induction and caspase activation, free 2SBPO dye is shown to accumulate inside the cell after probe cleavage. In previous work in our lab, single molecule fluorescence in single apoptotic cells was detected 45 min after induction using a rhodamine 110-based probe. However, significant statistical analysis was needed to exclude false positives. The use of 2SBPO-Casp overcomes the autofluorescence problem and offers a steady fluorescence signal. In our single molecule FCS measurements, Ramos cells were determined apoptotic on the basis of their correlation coefficient value (R(2)). Cells that contain an R(2) ≥ 0.65 were identified as highly correlated and therefore determined to be apoptotic. Single apoptotic cells identified in this manner were found as early as 30 min after induction and the number of apoptotic cells reached a peak value at the 3rd hour, which is consistent with other techniques. Using single molecule techniques and a new apoptosis probe, the temporal dynamics were elucidated with better sensitivity and resolution than in previous studies.     

Structural interpretation of a topological index. 1. External factor variable connectivity index (EFVCI)

The external factor variable connectivity index (EFVCI) is interpreted by mining out the structural features hidden in the space spanned by the EFVCI indices through projection pursuit combining with number-theory net (NT-net) on the unit sphere U(Us). Projection pursuit is concerned with "interesting" projections of high-dimensional data sets to machine-pick "interesting" low-dimensional projections of a high-dimensional point cloud by numerically maximizing a certain objective function or projection index. At first, the optimal EFVCI index reaches to -0.80 in the correlation with a retention index of 207 hydrocarbons produced by insects. The EFVCI indices, with regression results of R = 0.99998, s = 3.49, RMSECV = 3.90, and F = 7.9560e+005, obtain high regression quality. The model is proven valid by leave-one-out cross validation. Second, the EFVCI index is interpreted by the structure information, that is, size, branch number, graph center, and branching position of topological structures, which is searched out on the unit sphere U(Us) by projection pursuit. Finally, the interpretation information is used to discover some chemical knowledge concerning the variation of the retention index with the change in chemical structures.