A three-dimensional computerized model of the receptor responsible for sensing the sweet taste in the tongue was built in the laboratory of Prof. Masha Niv from the Faculty of Agriculture at the Hebrew University, and it was discovered that it allows scanning huge databases to extract sweet compounds from them in a much shorter time than is currently customary
Mammals are innately attracted to a sweet taste - a feature that allows the consumption of carbohydrates, which is an evolutionary advantage in nature and at the same time a big problem for humans in the modern era, where access to sweets has become almost unlimited. The search for the "next stevia" is in full swing, with many researchers investing a lot of effort to find natural and healthy sweeteners, sugar-free and low-calorie, without aftertastes and that would be cheap for the industry - instead of the artificial sweeteners that are harmful to health. The essential problem today is the time it takes to find those new sweeteners. In addition, the spatial structure of the sweet taste receptor has not been discovered to date, and therefore there is a need for creativity when it comes to finding new compounds that can create the desired taste.
In a study recently published in the scientific journal "Food Chemistry", researchers from the Hebrew University - Prof. Masha Niv from the Institute of Biochemistry, Food and Nutrition Sciences, and research assistant Yaron Ben Shoshan-Galatsky - built a three-dimensional computerized model of the receptor responsible for sensing the sweet taste in the tongue, and tested In a computational method, these materials are spatially suitable for locating the link in the receptor model. The spatial model chosen as the most reliable is the one that was able to retrieve known sweet substances, but not "distracting" substances (substances that resemble sweets in their spatial form, but are not actually sweet). Using such a model in particular and computational methods in general make it possible to scan huge databases in order to extract sweet compounds from them - and in a much shorter time than is currently accepted in the market.
In the next step in the research, the 40,000D model was used to scan an electronic database in which there are about 400 substances found in food. For the XNUMX substances with the best match to the receptor, a search was made in databases and patents. From this search, it emerged that for dozens of the substances discovered in the scan, patent applications were recently submitted as sweeteners. This fact indicates the reliability of the model and its ability to classify substances as sweet from a very large database.
According to Prof. Niv and Ben Shoshan-Galatsky, "studies of this type, based on computational methods (currently applied mainly in drug development), make it possible to significantly reduce the amount of resources and time invested in the search for new sweeteners", and this is the most significant result of this study. It is now being tested in Prof. Niv's laboratory whether in the list of the most suitable substances that came up in the research there are other modern sweet substances that have not yet been discovered in the industry.
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