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Trichosanthes kirilowii polysaccharides: A comprehensive review of structural characterization, bioactivities, and
Xuebin Xu1, Jiufu Xiao1, Han Zhang1
1Key Laboratory of Basic and Application Research of Beiyao (Ministry of Education), Heilongjiang University of Chinese Medicine, Harbin, 150040, PR China.
Abstract:
Trichosanthes kirilowii polysaccharides (TKP), isolated from the seeds, peels, and roots, exhibit remarkable structural heterogeneity and diverse biological activities. This review systematically summarizes recent advances in the extraction, purification, structural characterization, and biological activities of TKP. Additionally, the structure-activity relationships of TKP were investigated using multivariate statistical approaches, including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and exploratory partial least squares regression (PLSR). Current evidence indicates that polysaccharides from different T. kirilowii tissues exhibit significant variations in molecular weight (MW), monosaccharide composition, and glycosidic linkage patterns. Preliminary analyses based on limited datasets suggest potential associations between certain monosaccharides and biological activities; however, these observations require validation in larger, independent studies. Moreover, monosaccharide composition alone cannot account for the biological activities of TKP and should be interpreted alongside other structural characteristics. Overall, the biological activities of TKP are governed by multiple structural features. Monosaccharide composition displays tissue-associated compositional patterns; however, these patterns are derived from literature-compiled datasets and have not been validated with independent samples. These findings provide new insights into the quality evaluation and structure-activity relationships of TKP. Future studies should focus on standardized structural characterization, expanded datasets, advanced glycomics technologies, and AI-assisted modeling to develop more robust quantitative structure-activity relationship models.
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