糖的原子电距矢量表达及其核磁共振碳谱模拟

ON AED VECTOR CHARACTERIZATION AND ^(13)C NMR SIMULATION FOR SUGARS

提出以原子电性距离矢量 (VAED) ,描述上百种糖分子中数百个不同等价碳原子的化学环境 ;并结合γ效应校正 ,建立核磁共振碳谱 ( 1 3CNMR)化学位移 (CS)的五参数线性模型 .用于糖分子中四类不同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及标准偏差SD和F -统计量F分别为 :伯碳n=62 ,R =0 .991 0 ,RMS =1 .960 2 (SD =1 .9762 ,F =5 0 2 .32 94 ,EV =0 .980 5 ) ;仲碳n=79,R =0 .9886,RMS=2 .5 40 5 (SD =2 .5 5 67,F=5 1 5 .60 4 6,EV =0 .975 7) ;叔碳n=30 2 ,R=0 .95 1 4 ,RMS =3.6884 (SD=3.694 5 ,F=4 68.82 76,EV =0 .90 35 )及季碳n =1 4 ,R=0 .5 772 ,RMS=8.862 6(SD =9.1 972 ,F =0 .5 82 8,EV =- 0 .0 837) .经交互校验 ,伯仲叔碳的化学位移模型稳定性较好 .并综合几种处理方法 ,找到一种较好的建模方法 ,将它用于几个外部样本的定量预测 ,结果良好 .

In bioorganic analysis, abundant structural information can be provided by carbon 13 nuclear magnetic resonance ( 13 C NMR) and more and more attentions have recently been paid on its molecular modelling and quantitative prediction which on the basis of the relationship of chemical shift of carbon nuclear magnetic resonance with descriptor variables of chemical structure. By using multiple linear regression (MLR) and latent factor analysis (LFA) techniques, quantitative \{\}\+\{13\}C NMR models are achieved to accurately express correlation of \{\}\+\{13\}C NMR chemical shifts with five structural parameters and to successfully predict the chemical shift \%(CS)\% of any other compounds optimally. First, the history and progress in quantitative structure spectra relationship (QSSR) were critically reviewed, and a set of novel descriptors consisting of 4 elements, called atomic electronegative distance edge vector (AEDV) were first developed by our laboratory and further investigated for the bioactive compounds. Next, MLR and LFA were simply introduced; Matlab and True Basic programs for quantitative molecular modelling (QMM) were designed and written by ourselves. Then, various chemical shifts of \{\}\+\{13\}C NMR for 457 different chemically equivalent carbon atoms in 135 natural sugars were estimated and/or predicted with the atomic electronegative distance edge vector (AEDV) with 4 elements and the γ calibration parameter: The correlation coefficients \%R\%, roots of mean square error \%RMS\%, standard deviation \%SD\%, F statistic value \%F\%, and explained variance being \%n=62, R=0.9910, RMS=1.9602 (SD=1.9762, R\+2=\{0.9821,\} F=502.3294, EV=0.9805); n=79, R=0.9886, RMS=2.5405 (SD=\{2.5567,\} R\+2=0.9773, F=515.6046, EV=0.9757); n=302, R=0.9514, RMS=\{3.6884\} (SD=3.6945, R\+2=0.9051, F=468.8276, EV=0.9035)\% and \%n=14, R=\{0.5772,\} RMS=8.8626(SD=9.1972, R\+2=0.3331, F=0.5828, EV=-0.0837)\% for the primary, secondary, tertiary and quaternary carbons in all carbohydrates, respectively. Finally, cross validation with leave one out (LOO) procedure was made on the QSSR equations for all four types of carbon atoms. The good results were obtained for the first three types of carbon atoms except the quaternary carbon atoms, which indicated that there exists a simply multiple linear relationship between CS and AEDV for primary, secondary, tertiary carbon atoms of sugars. \;