Development of structure-taste relationships for thiazolyl-, benzothiazolyl-, and thiadiazolylsulfamates.

A total of 28 new five-membered aromatic ring thiazolyl-, benzothiazolyl-, and thiadiazolylsulfamates, as their sodium salts, have been synthesized and combined with 30 known similar heterocyclic sulfamates to create a database for the study of structure-activity (taste) relationships (SARs) in this heterocyclic subgroup, which is known to contain a somewhat disproportionate number of sweet compounds compared to other groups of tastants. A series of nine parameters (descriptors) to describe the properties of the sulfamate anions were calculated in Spartan Pro and HyperChem programs. These are the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), length of the molecule, dipole moment, area, volume, E(solv), sigma (from the literature), and log P. The taste data for all 58 compounds were categorized into three classes, namely, sweet (S), nonsweet (N), and nonsweet/sweet (N/S). Discriminant analysis only classified 44 of the 58 compounds correctly. Classification and regression tree analysis (CART) using the S_ Plus program proved highly effective, in that the derived tree correctly classified 46 compounds from a training set of 48 and, from a computer randomly selected test set of 10 compounds, 7 had their taste correctly predicted. A second tree was grown using the additional taste category N/S, and this tree also performed extremely well, with 8 of the 10 compounds in the test set correctly classified. These trees should be very reliable for predicting the tastes of other heterocyclic sulfamates, which belong to the subset used here.

Structure-taste relationships for disubstituted phenylsulfamate tastants using classification and regression tree (CART) analysis.

Forty-two new disubstituted phenylsulfamates have been synthesized, and 30 of these have been combined with 40 already available from earlier work to create a training database of 70 compounds. On the basis of panel taste data these were divided into three categories, N (nonsweet), N/S (nonsweet/sweet), and (S) sweet, and a "sweetness value" or weighting was also calculated for each compound. Using these 70 compounds as a training set and a series of nine predictors derived from Corey-Pauling-Koltun (CPK) models, calculated from the PC SPARTAN PRO program and Hammett sigma values taken from the literature, a classification and regression tree analysis (CART) was carried out leading to a regression tree that correctly classified 62 of the 70 compounds (89% overall correct classification). The tree's predictive ability varies for the different taste categories, and for nonsweet compounds it is virtually 100%; for nonsweet/sweet compounds it is 66%, and for sweet compounds it is approximately 75%. This tree correctly predicted taste categories for 10 compounds from a test set of 12 randomly selected from among the 42 new compounds (83% correct classification). Therefore, it can be used with a good degree of confidence to predict the tastes of disubstituted phenylsulfamates. For the design of new sweeteners, appropriate values or ranges of the descriptors are derived.