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Highlighting glycosylation ways in Caryophyllaceae saponins by simplex simulation approach
1 , 2 , * 3
1  Institut National des Sciences Appliquées et de Technologies (INSAT). Université de Carthage. Tunisia.
2  Quaid-i-Azam University, Department of Chemistry, Islamabad, Pakistan
3  University of Tunis El Manar. Pasteur Institute of Tunis. Laboratory of BioInformatics, bioMathematics and bioStatistics (BIMS), 1002, Tunis, Tunisia

Abstract:

Glycosylation mechanisms in saponins of Caryophyllaceae plant family were subjected to simulation by statistically exploring variability of 231 chemical structures belonging to four different aglycones: gypsogenin (Gyp), quillaic acid (QA), gypsogenic acid (GA), 16-OH-gypsogenic acid (16-OH-GA). Saponins based on different aglycones were initially characterized by relative glycosylation levels of different carbons. Simulation was initialized by combining the four saponin groups using Scheffé’s mixture design which provides a complete set of N gradual weightings of groups. Combined saponins were randomly and iteratively sampled from different groups by bootstrap technique. For a same combination, saponins were averaged leading to barycentric glycosylation profile. Iterations of the N barycentric profiles and averaging provided a final response matrix of N smoothed glycosylation profiles from which regulation mechanisms of carbons were highlighted in different aglycone-based saponins. Glucose (Glc) was revealed to be widely favored in GA and 16-OH-GA with more target aspect of 28-Glc in 16-OH-GA and relatively shared distribution between C28 (mainly) C3 and C23 in GA. Strong competition for galactose (Gal) was highlighted between C3 and C28 with target aspects to 28-Gal in GA and 3-Gal in (Gyp, QA). Gyp and QA showed higher regulations of pentoses (xylose, Xyl; arabinose, Ara) with more affinity of GA for (3-Ara, 28-Xyl) and 16-OH-GA for (3-Xyl, 28-Ara). These results call for further investments in simulations of glycosylation mechanisms helping for better understanding metabolic aspects of saponins, and encouraging future analytic experiments in the field.

Keywords: Computational chemistry; mixture design; metabolism; regioselectivity, chemical substitution
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