Ligand-targeted fishing of α-glucosidase inhibitors from Tribulus terrestris L. based on chitosan-functionalized multi-walled carbon nanotubes with immobilized α-glucosidase.

α-Glucosidase inhibitors in natural products are one of the promising drugs for the treatment of type 2 diabetes. However, due to the complexity of the matrix, it is challenging to comprehensibly clarify the specific pharmacodynamic substances. In this study, a novel high-throughput inhibitor screening strategy was established based on covalent binding of α-glucosidase on chitosan-functionalized multi-walled carbon nanotubes coupled with high-resolution mass spectrometry. The synthesized MWCNTs@CS@GA@α-Glu was characterized by TEM, SEM, FTIR, Raman, and TG. Performance studies showed that the microreactor exhibited stronger thermostability and pH tolerance than that of the free one while maintaining its inherent catalytic activity. Feasibility study applying a model mixture of known α-glucosidase ligand and non-ligands indicated the selectivity and specificity of the system. By integrating ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-QTOF-MS) with ion mobility mass spectrometry (IMS), 15 ligands were obtained and tentatively identified from Tribulus terrestris L., including 8 steroidal saponins, 4 flavonoids, and 3 alkaloids. These inhibitors were further validated by in vivo experiments and molecular docking simulation.

Evaluation of Qi-deficiency Model Based on Urine Non-targeted Metabonomics / 中国实验方剂学杂志

ObjectiveTo evaluate the success of Qi-deficiency model of Balb/C-nu mice established by swimming exhaustion test from the view of biomarkers and metabolic pathways by metabonomics. MethodBalb/C-nu mice were randomly divided into the normal group and Qi-deficiency group， Qi-deficiency model was established by swimming with 5% body weight metal fixed at the tail for 15 consecutive days until exhaustion （nose tip immersion time>5 s）. The urine metabonomics was analyzed by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry （UPLC-Q-TOF/MS）， and the mobile phase was acetonitrile （A）-0.1% formic acid aqueous solution （B） for gradient elution （0-1 min， 5%-8%A； 1-4 min， 8%-8.5%A； 4-5 min， 8.5%-12%A； 5-10 min， 12%-40%A； 10-12 min， 40%-100%A； 12-15 min， 100%A）， the flow rate was 0.3 mL·min-1， the injection volume was 10 μL， electrospray ionization （ESI） in positive and negative ion modes was used in MS analysis， the MS data were acquired in full-scan mode from m/z 50-1 000. Principal component analysis （PCA）， orthogonal partial least squares-discriminant analysis （OPLS-DA）， human metabolome database （HMDB）， high collision energy ion fragments collected by MSE and tandem MS （MS/MS） ion information were used to identify potential biomarkers. Kyoto Encyclopedia of Genes and Genomes （KEGG） database and MetaboAnalyst 5.0 were used to analyze the corresponding metabolic pathways and pathway enrichment of biomarkers. ResultEndogenous substances in urine of mice in normal group and Qi-deficiency group were obviously separated， and there were 24 biomarkers with significant difference. The metabolic pathways involved in these biomarkers were tricarboxylic acid cycle， glycolysis metabolism， amino acid metabolism， fatty acid metabolism， pyrimidine metabolism， steroid hormone biosynthesis and tryptophan metabolism. Among them， the metabolic pathways related to energy were tricarboxylic acid cycle， glycolysis metabolism， amino acid metabolism， fatty acid metabolism， pyrimidine metabolism and steroid hormone biosynthesis. ConclusionThrough the investigation of urine metabonomics， combined with the physical signs， the Qi-deficiency model established by swimming exhaustion test in Balb/C-nu mice is successfully evaluated， and it is also verified that there is a close correlation between Qi-deficiency and energy metabolism.

Evaluation of Qi-deficiency Model Based on Urine Non-targeted Metabonomics / 中国实验方剂学杂志

ObjectiveTo evaluate the success of Qi-deficiency model of Balb/C-nu mice established by swimming exhaustion test from the view of biomarkers and metabolic pathways by metabonomics. MethodBalb/C-nu mice were randomly divided into the normal group and Qi-deficiency group， Qi-deficiency model was established by swimming with 5% body weight metal fixed at the tail for 15 consecutive days until exhaustion （nose tip immersion time>5 s）. The urine metabonomics was analyzed by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry （UPLC-Q-TOF/MS）， and the mobile phase was acetonitrile （A）-0.1% formic acid aqueous solution （B） for gradient elution （0-1 min， 5%-8%A； 1-4 min， 8%-8.5%A； 4-5 min， 8.5%-12%A； 5-10 min， 12%-40%A； 10-12 min， 40%-100%A； 12-15 min， 100%A）， the flow rate was 0.3 mL·min-1， the injection volume was 10 μL， electrospray ionization （ESI） in positive and negative ion modes was used in MS analysis， the MS data were acquired in full-scan mode from m/z 50-1 000. Principal component analysis （PCA）， orthogonal partial least squares-discriminant analysis （OPLS-DA）， human metabolome database （HMDB）， high collision energy ion fragments collected by MSE and tandem MS （MS/MS） ion information were used to identify potential biomarkers. Kyoto Encyclopedia of Genes and Genomes （KEGG） database and MetaboAnalyst 5.0 were used to analyze the corresponding metabolic pathways and pathway enrichment of biomarkers. ResultEndogenous substances in urine of mice in normal group and Qi-deficiency group were obviously separated， and there were 24 biomarkers with significant difference. The metabolic pathways involved in these biomarkers were tricarboxylic acid cycle， glycolysis metabolism， amino acid metabolism， fatty acid metabolism， pyrimidine metabolism， steroid hormone biosynthesis and tryptophan metabolism. Among them， the metabolic pathways related to energy were tricarboxylic acid cycle， glycolysis metabolism， amino acid metabolism， fatty acid metabolism， pyrimidine metabolism and steroid hormone biosynthesis. ConclusionThrough the investigation of urine metabonomics， combined with the physical signs， the Qi-deficiency model established by swimming exhaustion test in Balb/C-nu mice is successfully evaluated， and it is also verified that there is a close correlation between Qi-deficiency and energy metabolism.