Evidence map›Paper›PMID 38634946›Full record

ArticleJournal of molecular modeling2024

Proposed molecular mechanism of non-competitive inhibition using molecular dynamics simulations between α-glucosidase enzyme and mangostin compound as antidiabetic.

Ahmad Fariz Maulana, Iman Permana Maksum, Sriwidodo Sriwidodo, Yaya Rukayadi

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In one paragraph

Article in Journal of molecular modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. ADMET & DMPK · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Ahmad Fariz MaulanaDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Padjadjaran University, Jatinangor, Sumedang, 45363, Indonesia.
Iman Permana MaksumDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Padjadjaran University, Jatinangor, Sumedang, 45363, Indonesia. iman.permana@unpad.ac.id.
Sriwidodo SriwidodoDepartment of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Padjadjaran University, Jatinangor, Sumedang, 45363, Indonesia.
Yaya RukayadiDepartment of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.
Padjadjaran University · IDUniversiti Putra Malaysia · MY

Funding

Academic Leadership Grant (ALG) 1427/UN6.3.1/LT/2020
6 · The paper itself

Abstract

contextFurther understanding of the molecular mechanisms is necessary since it is important for designing new drugs. This study aimed to understand the molecular mechanisms involved in the design of drugs that are inhibitors of the α-glucosidase enzyme. This research aims to gain further understanding of the molecular mechanisms underlying antidiabetic drug design. The molecular docking process yielded 4 compounds with the best affinity energy, including γ-Mangostin, 1,6-dimethyl-ester-3-isomangostin, 1,3,6-trimethyl-ester-α-mangostin, and 3,6,7-trimethyl-ester-γ-mangostin. Free energy calculation with molecular mechanics with generalized born and surface area solvation indicated that the 3,6,7-trimethyl-γ-mangostin had a better free energy value compared to acarbose and simulated maltose together with 3,6,7-trimethyl-γ-mangostin compound. Based on the analysis of electrostatic, van der Waals, and intermolecular hydrogen interactions, 3,6,7-trimethyl-γ-mangostin adopts a noncompetitive inhibition mechanism, whereas acarbose adopts a competitive inhibition mechanism. Consequently, 3,6,7-trimethyl-ester-γ-mangostin, which is a derivative of γ-mangostin, can provide better activity in silico with molecular docking approaches and molecular dynamics simulations.

methodThis research commenced with retrieving protein structures from the RCSB database, generating the formation of ligands using the ChemDraw Professional software, conducting molecular docking with the Autodock Vina software, and performing molecular dynamics simulations using the Amber software, along with the evaluation of RMSD values and intermolecular hydrogen bonds. Free energy, electrostatic interactions, and Van der Waals interaction were calculated using MM/GBSA. Acarbose, used as a positive control, and maltose are simulated together with test compound that has the best free energy. The forcefields used for molecular dynamics simulations are ff19SB, gaff2, and tip3p.

Indexed as

alpha-GlucosidasesHypoglycemic AgentsXanthonesAcarboseEstersMaltoseMolecular Docking SimulationMolecular Dynamics SimulationAcarbosealpha-GlucosidasesEstersHypoglycemic AgentsMaltosemangostinXanthonesAntidiabeticDiabetesIn silicoMolecular dockingMolecular dynamics simulation

Identifiers

PMID38634946
OpenAlexW4394921375

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.