@article {2038, title = {Metabolite Profiling of Compounds from Sargassum polycystum using UPLC-QToF-MS/MS}, journal = {Pharmacognosy Journal}, volume = {15}, year = {2023}, month = {June 2023}, pages = {321-333}, type = {Research Article}, chapter = {321}, abstract = {

Background: There are many types of seaweed that have high economic value. Brown seaweed (Sargassum polycystum) can be used as a raw material in the industry and as a medicinal plant. Maintaining the quality of a compound requires an analytical method that can identify the diversity of metabolome profiles. Objective: This investigation seeks to discover the metabolite profile of S. polycystum from Sumenep, Madura Island, Indonesia, utilizing the UPLC-QToF MS/MS equipment. Materials and Methods: The extract was further fractioned using n-hexane, ethyl acetate, and water. The metabolite profiling of extract and fractions used the UPLC-QToF-MS/MS instrument. It was produced with SPE and then introduced into the MS Xevo G2-S QToF detector of the ACQUITY UPLC{\textregistered} H-Class System. The findings of the UPLC-QToF-MS/MS analysis were processed with the MassLynx 4.1 software to obtain chromatogram data and m/z spectra of each observed peak, which were then validated using the ChemSpider and MassBank databases. Results: Based on the results of metabolite profiling using UPLC-QToF-MS/MS, the 96 \% ethanol extract of S. polycystum indicated a total of 61 compounds, the n-hexane fraction indicated a total of 55 compounds, the ethyl acetate fraction indicated a total of 67 compounds, and the water fraction indicated a total of 49 compounds. Conclusion: There are 232 compounds in the extract and a fraction of S. polycystum consisting of 168 known compounds and 64 unknown compounds.

}, keywords = {Metabolite profiling, Sargassum polycystum, Seaweed, UPLC-QToF-MS/MS}, doi = {10.5530/pj.2023.15.82}, author = {Pramudita Riwanti and Intan Kris Prasetyanti and Burhan Ma{\textquoteright}arif} } @article {1608, title = {ADMET Prediction and In silico Analysis of Mangostin Derivatives and Sinensetin on Maltase-Glucoamylase Target for Searching Anti-Diabetes Drug Candidates}, journal = {Pharmacognosy Journal}, volume = {13}, year = {2021}, month = {July 2021}, pages = {883-889}, type = {Original Article}, chapter = {883}, abstract = {

Background: Diabetes mellitus (DM) is a complex chronic disease with hyperglycemia, which is glucose levels above normal whose number of sufferers is increasing. By inhibiting the human maltase-glucoamylase enzyme which is included in the starch-digestion pathway are used to delay glucose production and thus aid in the treatment of type II diabetes. Aims and Methods: To analyze the potential of mangostin derivatives (alpha-mangostin, betamangostin, gamma-mangostin) and sinensetin as anti-diabetes through ADMET prediction and in silico tests against human maltase-glucoamylase targets using the docking method with miglitol was used as a control. Result: The ligands ɑ, β, γ-mangostin and sinensetin have good interactions with macromolecules and form hydrogen bonds also van der Waals on the macromolecule active side of human maltase-glucoamylase. Conclusion: The ADMET of mangostin derivatives (ɑ, β, and γ), and sinensetin can be predicted by the pkCSM online tool, and they showed good affinity on maltase-glucoamylase target compared to standard drugs like miglitol.

}, keywords = {Anti-diabetes, Maltase-glucoamylase, Mangostin derivatives, Molecular docking, Sinensetin}, doi = {10.5530/pj.2021.13.113}, author = {Intan Kris Prasetyanti and Sukardiman and Suharjono} }