Admet prediction and in silico analysis of mangostin derivatives and sinensetin on maltase-glucoamylase target for searching anti-diabetes drug candidates

Intan Kris Prasetyanti, Sukardiman, Suharjono

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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, beta-mangostin, 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 α, 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 (α, 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.

Original languageEnglish
Pages (from-to)883-889
Number of pages7
JournalPharmacognosy Journal
Volume13
Issue number4
DOIs
Publication statusPublished - Jul 2021

Keywords

  • Anti-diabetes
  • Maltase-glucoamylase
  • Mangostin derivatives
  • Molecular docking
  • Sinensetin

Fingerprint

Dive into the research topics of 'Admet prediction and in silico analysis of mangostin derivatives and sinensetin on maltase-glucoamylase target for searching anti-diabetes drug candidates'. Together they form a unique fingerprint.

Cite this