An Efficient and Simple Approach to Predict Kovat's Indexes of Polychlorinated Naphthalenes in Gas Chromatography

Molecular structures of polychlorinated naphthalenes were numerically described with a simple but efficient encoding method. Correspondingly a set of structural parameters were obtained for these compounds and linearly correlated with their gas chromatography retention indexes. A quantitative structure-retention relationship Model (M1) was developed by using multiple linear regression (MLR) with correlation coefficient R = 0.9880 between the numeric structural codes and the gas chromatography retention indexes of 62 polychlorinated naphthalenes. If the "leave-one-out" cross-validation procedure was employed to construct QSPR model for all samples, the second model M2 with the correlation coefficient being R = 0.9839 was generated. The structural codes of polychlorinated naphthalenes were tested with MLR for estimation and prediction of the GC RI by models M1 and M2, and the results obtained were satisfactory.