A Computational Approach to Understanding and Predicting the Edulcorant Profile of Glucosyl Steviol Glycosides

Abstract

Understanding the edulcorant profile of synthetic glucosyl steviol glycosides (GSGs) and rare natural steviol glycosides (SGs) is challenging due to their numerous species and rareness. This study developed a computational model based on the interactions of SG molecules with human sweet and bitter taste receptors (hSTR/hBTR). The models demonstrated a high correlation between the cumulative interaction energies and the perceived sweetness of SGs (R2 = 0.97), elucidating the mechanism of the diverse sweetness of SGs. It also revealed that more (within three) glucose residues at the C-13 position of the SG molecule yield stronger sweetness and weaker bitterness. Furthermore, the computational prediction was consistently validated with the known sweetness of GSG and also aligned well with that of several natural mogrosides. Thus, this model possesses a potential to predict the sweetness of SGs, GSGs, and mogrosides, facilitating the application or targeted synthesis of GSGs with desired sensory profiles.

Keywords

• sensory analysis
• sweetness
• glucosyl steviol glycoside
• steviol glycoside
• edulcorant quality
• mogroside