Publications by authors named "Ke-xian Chen"

The physicochemical mechanism of starch digestion is very complicated since it may be affected by the non-valence interactions of the amylase inhibitor with the substrate or the enzyme. The role of hydrophobic interaction in the process of starch digestion is not clear. In this study, pluronics (PLs) with different hydrophobicity were used as model amphiphilic compounds to study their inhibition on starch digestion using multi-spectroscopic methods.

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Control of lipid digestibility by various food components has received great attention in recent decades. However, there is limited literature on investigating the synergistic effect of exogenous emulsifiers and endogenous sodium cholate (SC) on lipid digestion in a simulated physiological crowded medium. In this work, the synergistic interaction of Tween80 and SC according to the regular solution theory, and the hydrolysis of lipid emulsions containing tricaprylin, glyceryltrioleate or soybean oil in crowding medium was studied.

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Vesicles possess unique biofilm structures and offer biomimetic advantages for drug and gene delivery. Herein, we report the spontaneous vesicle formation from ultrashort alkyl-phosphonic acids in the presence of amino acids. The aggregation characteristics and self-assembly structures of vesicles in aqueous solution were investigated by using dynamic light scattering, zeta potential, and cryo-transmission electron microscopy.

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The properties of vesicles formed from the self-assembly of amphiphilic molecules can mimic the functionality of the natural lipid membranes. In this study, the self-assembly process of the amphiphilic structures formed by the interaction between ultra-small fatty acids [FAs, Cn (n = 4-8)] and amino acids (AAs) to generate vesicles under aqueous conditions were investigated in detail, along with the corresponding dynamic vesiculation mechanisms. Our results showed that the molar ratio of FAs/AAs and the chain length of FAs largely affected the structural characteristics and dispersion of vesicles.

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Five flavone C-glycosides were isolated from the methanol extract of the degrease seeds of Ziziphus jujuba var. spinosa though various column chromatography methods including silica gel, MPLC, and HPLC. The structures were elucidated as 6"-feruloyl- 6'''-vanillylspinosin(1), 6",6'"-diferuloylspinosin(2), spinosin(3), swertisin(4) and isoswertisin(5) based on the NMR and MS spectral data.

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Jasmonates and related compounds have been highlighted recently in the field of plant physiology and plant molecular biology due to their significant regulatory roles in the signaling pathway for the diverse aspects of plant development and survival. Though a considerable amount of studies concerning their biological effects in different plants have been widely reported, the molecular details of the signaling mechanism are still poorly understood. This review sheds new light on the structural requirements for the bioactivity/property of jasmonic acid derivatives in current computational perspective, which differs from previous research that mainly focus on their biological evaluation, gene and metabolic regulation and the enzymes in their biosynthesis.

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Quantitative structure-activity relationship analysis for recently synthesized aryl alkanol piperazine derivatives was studied for their antidepressant activities. The statistically significant 2D-QSAR models (r(2)>0.924, r(-CV)(2)>0.

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Jasmonates and related compounds, including amino acid conjugates of jasmonic acid, have regulatory functions in the signaling pathway for plant developmental processes and responses to the complex equilibrium of biotic and abiotic stress. But the molecular details of the signaling mechanism are still poorly understood. Statistically significant quantitative structure-property relationship models (r(2) > 0.

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Predictive quantitative structure-activity relationship analysis was developed for a diverse series of recently synthesized 1-aryl-tetrahydroisoquinoline analogs with anti-HIV activities in this study. The conventional 2D-QSAR models were developed by genetic function approximation (GFA) and stepwise multiple linear regression (MLR) with acceptable explanation of 94.9% and 95.

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