Computer-assisted methods are applied to the development of predictive models for the normal boiling points of diverse sets of pyrans and pyrroles. The models developed employ molecular structure based parameters or descriptors to encode the features of the compounds which determine the boiling point. A set of 20 descriptors is identified that allows for the development of good quality models for the pyrans and for sets of furans, tetrahydrofurans (THFs), and thiophenes, which have been studied previously. A model is presented which yields good predictions for a combined set of pyrans, furans, THFs, and thiophenes. The scope of this work is expanded to include nitrogen-containing heterocycles through the study of a diverse set of pyrroles. As part of this work, a new set of descriptors is developed for the purpose of capturing information concerning the molecular features responsible for intermolecular hydrogen-bonding interactions. Finally, the pyrrole dataset is combined with a large set of furans, THFs, thiophenes, and pyrans for the purpose of producing a more general boiling point prediction equation. The results of these studies are examined to determine their impact on future work.

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Numerical representations of structure-based features are used to estimate both the retention indexes and sweetnesses of a diverse set of industrially important fragrance compounds. Retention indexes measured on nonpolar as well as polar stationary phases are modeled with accuracies of 3.6% and 5.6% at the mean of the respective retention ranges. Similar success was achieved when the developed equations were applied to predict the retention indexes of external data set compounds. Finally, the implications of using strictly 2-D structural information versus incorporating geometrical information are explored and discussed. The intensity of sweetness attributed to each compound is quantitatively predicted using identical multiple linear regression techniques. Difficulties encountered in this portion of the study warranted a critique of the procedures used to gain access to the odor data. As a consequence, the limited control exerted over several experimental variables is questioned.