PubMed · 5127965
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A K Bose. 1971-01-01. Cyclamates versus cigarettes.. https://pubmed.ncbi.nlm.nih.gov/5127965/
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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.
Twenty monosubstituted phenylsulfamates (cyclamates) have been synthesized and have had their taste portfolios determined. These have been combined with 63 compounds already in the literature to give a database of 83 ortho, meta, and para compounds. A training set of 75 compounds was randomly selected leaving eight compounds as a test set. A series of nine predictors determined with Corey-Pauling-Koltun models, calculated from the PC SPARTAN PRO program and Hammett sigma values taken mainly from the literature, have been used to establish structure-taste relationships for these types of sweeteners. The taste panel data for all compounds were categorized into three classes, namely, sweet (S), nonsweet (N), and sweet/nonsweet (N/S), and a novel "sweetness value" or weighting was also calculated for each compound. Linear and quadratic discriminant analysis were first used with the S, N, and N/S data, but the results were somewhat disappointing. Classification and regression tree analysis using the sweetness values for all 75 compounds was more successful, and only 14 were misclassified and six of the eight test set compounds were correctly classified. For the 29 meta compounds, one subset using just two parameters classified 83% of these compounds. Finally, using various methods, predictions were made on the likely tastes of a number of meta compounds and a striking agreement was found between the tree prediction and those given by earlier models. This appears to offer a strong vindication of the tree approach.
The interaction of the sweeteners saccharine and cyclamate with large unilamellar liposomes and planar bilayer lipid membranes (BLM) was studied. Application of the methods of light scattering and sound velocimetry showed that saccharine induces aggregation of liposomes, while cyclamate probably caused increase of the hydration of liposome surface. The sweeteners induced changes of BLM compressibility in a direction perpendicular to the membrane plane. The cyclamate induced considerably larger decreases in the elasticity module than saccharine. The obtained results show that both saccharine and cyclamate interacts with the surface of lipid bilayer and could modify the physical properties of lipid membranes.