Abstract: In bioorganic analysis, abundant structural information can be provided by ¹³C NMR,and more and more attentions have recently been paid on its molecular modelling and quantitative prediction on the basis of the relationship of chemical shift of carbon nuclear magneticresonance with descriptor variables of chemical structure. By using multiple linear regression(MLR) and factor analysis (FA) techniques, quantitative ¹³C NMR models are achieved toaccurately express correlation of ¹³C NMR chemical shifts with structural parameters and tosucessfully predict the chemical shift (CS) of any other compounds optimally. First, the history and progress in quantitative-strycture-spectra relationship (QSSR) were critically reviewed. MLR and FA were simply introduced. Next, Matlab and True Basic programs forquantitative molecular modelling (QMM) were designed by ourselves. Then, investigation ofNMR CS for all 20 natural amino acids was estimated and predicted with the atom distanceedge vector (ADEV) and γ calibration, the result indicated that there exists a simply multiple linear relationship between CS and ADEV.

Key words: NMR, Multiple linear regression, Factor analysis, Atom distance-edge vector, γ calibration, π-efect, Chemical shift, Quantitative structure-spectra relationship, Amino acids