{"title":"Highlighting glycosylation ways in Caryophyllaceae saponins by simplex simulation approach","authors":"Asma Hammami, M. Farman, N. Semmar","doi":"10.3390/mol2net-05-06386","DOIUrl":null,"url":null,"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 Scheffe’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.","PeriodicalId":337320,"journal":{"name":"Proceedings of MOL2NET 2019, International Conference on Multidisciplinary Sciences, 5th edition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of MOL2NET 2019, International Conference on Multidisciplinary Sciences, 5th edition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/mol2net-05-06386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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 Scheffe’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.