摘要
提出以原子电性距离矢量 (VAED)描述各种碱基分子中不同等价碳原子的化学环境 ,结合γ效应校正与碳原子类型 ,建立核磁共振碳谱 ( 1 3CNMR)化学位移 (CS)的五参数线性模型 .用于碱基分子中 4类不同碳 (其中主要是仲叔季碳 )的等价碳原子化学位移的估计 ,复相关系数R和均方根误差RMS[ppm]分别为仲叔季碳 :1 )对C2n =1 2 ,R =0 .9998,R2 =0 .9997,F =2 732 .2 4 98,EV =0 .9994,RMS =0 .1 80 4 ,SD =0 .1 8842 )对C3n =41 ,R =0 .9334,R2 =0 .871 2 ,F =38.32 99,EV =0 .852 8,RMS =9.52 68,SD =9.64523)对C4n =2 3,R =0 .91 83,R2 =0 .8433,F =1 4.3479,EV =0 .7972 ,RMS =6.530 4 ,SD =6.67721 )对C2n =1 2 ,R =0 .9998,R2 =0 .9997,F =2 592 .70 72 ,EV =0 .9994,RMS =0 .1 852 ,SD =0 .1 9342 )对C3n =41 ,R =0 .92 70 ,R2 =0 .8594,F =34.62 83,EV =0 .8393,RMS =9.548,SD =1 0 .0 7843)对C4n =2 3,R =0 .90 71 ,R2 =0 .82 2 9,F =1 2 .3881 ,EV =0 .770 8,RMS =6.942 5,SD =7.0 985经交互校验 ,模拟稳定性较好 .并综合几种处理方法 ,找到一种较好的建模方法 ,将它用于 4个外部样本化学位移的定量预测 。
Abundant structural information can be provided by carbon 13 nuclear magnetic resonance (\{\}\+\{13\}C NMR) in organic analysis, and recently more and more attentions have been paid on its molecular modelling and quantitative predication which on the basis of the relationship of carbon 13 nuclear magnetic resonance with chemical structure description. By using multiple linear regression(MLR) and factor analysis(FA) methods, quantitative \{\}\+\{13\}C NMR models are achieved to express correlation of \{\}\+\{13\}C NMR chemical shifts with structural parameters and the chemical shift(CS) of any other compounds is successfully predicted.\;The history and progress in quantitative spectral relationship(QSSR) were crifically reviewed. MLR and FA methods were simply introduced. The Matlab and True Basic programs for quantitative molecular modelling(QMM) were designed by ourselves. The studies of all 20 inartificial amino bases' NMR CS were estimated and predicted with the atom distance edge vector(ADEV) and γ calibration. The result indicated that between CS and ADEV there exists a simple multiple linear relationship. Another parameter vector called the molecular path vector(VMP) was also used to model the chemical shift sum (CSS) of 150 alkanes, VMP with length 1 though 4 as well correlated with CSS more efficiently. Quantitative structure toxicity relationship(QSTR) were also developed that link molecular structure of a set of 50 alkylated phenols with their polar narcosis toxicity by employing their electronic, steric and hydrophoibic parameters. \;
出处
《波谱学杂志》
CAS
CSCD
北大核心
2000年第4期309-315,共7页
Chinese Journal of Magnetic Resonance
基金
国家教委霍英东基金
国家自然科学基金
机械部优秀人才专项基金
关键词
原子电性距离矢量
^13CNMR波谱模拟
碱基分子
Nuclear magnetic resonance, Multiple linear regression, Factor analysis, Atom distance edge vector, γ calibration, Chemical shift sum, Molecular path vector, Quantitative structure spectral relationship, Quantitative structure toxicity relatio