Prediction of gas chromatographic retention indices of alkylbenzenes

The retention indices (RIs) of a set of alkylbenzenes on a polar gas chromatographic column are predicted directly from their molecular structures. Numerical descriptors are calculated based on the structure of a group of 150 alkylbenzenes. The descriptors are of three types: topological, geometric, and electronic. Statistical methods are employed to find an informative subset of these descriptors that can accurately predict the gas chromatographic RIs. The Automated Data Analysis and pattern Recognition Toolkit (ADAPT) software system is used to construct a large pool of structurally derived numerical descriptors which are used to build quantitative structure-retention relationships (QSRRs). Multiple linear regression analysis and computational neural networks are used to map the descriptors to the RIs.