Studi Komputasional Senyawa Flavonoid Tanaman Obat sebagai Kandidat Agen Antidiabetik

Purpose: This study aimed to investigate the potential of natural flavonoid compounds brazilin, luteolin, and butein as antidiabetic agents by exploring their interactions with key molecular targets in type 2 diabetes mellitus. Methodology/approach: This research was conducted using a computational approach involving molecular docking and pharmacokinetic prediction. Docking simulations were performed using AutoDock Vina and PyRx to evaluate the binding affinity of the selected flavonoids to the enzymes ?-glucosidase, ?-amylase, and glucokinase. Results/findings: The results showed that All three flavonoids exhibited strong binding affinities to ?-glucosidase and ?-amylase, indicating their potential to inhibit carbohydrate-digesting enzymes. Conclutions: Flavonoids from medicinal plants have potential as natural antidiabetic agents by inhibiting glucose-metabolizing enzymes and modulating insulin pathways. Computational studies have shown strong target interactions and favorable pharmacokinetic profiles, although further in vitro and in vivo validation is needed. Limitations: The findings of this study were limited to in silico data, and further validation through in vitro and in vivo experiments is necessary to confirm their effectiveness and safety. Contribution: This research contributes to the field of pharmaceutical sciences and natural product-based drug development, providing valuable insights for researchers and healthcare professionals interested in alternative therapies for diabetes management.

Authors

Institutions

Publication Details

Journal
Jurnal Ilmu Medis Indonesia
Published
2024-09-12
DOI
https://doi.org/10.35912/jimi.v4i1.4553
Primary Topic
Natural Antidiabetic Agents Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Studi Komputasional Senyawa Flavonoid Tanaman Obat sebagai Kandidat Agen Antidiabetik

Rosmadi Fauzi, Saeful Amin, Zulfan Alfairuz Zabbady Hurry, Tri Adi Sumantri
Jurnal Ilmu Medis Indonesia
Natural Antidiabetic Agents Studies
article

Studi Komputasional Senyawa Flavonoid Tanaman Obat sebagai Kandidat Agen Antidiabetik

Rosmadi Fauzi, Saeful Amin, Zulfan Alfairuz Zabbady Hurry, Tri Adi Sumantri
article en

Abstract

Purpose: This study aimed to investigate the potential of natural flavonoid compounds brazilin, luteolin, and butein as antidiabetic agents by exploring their interactions with key molecular targets in type 2 diabetes mellitus. Methodology/approach: This research was conducted using a computational approach involving molecular docking and pharmacokinetic prediction. Docking simulations were performed using AutoDock Vina and PyRx to evaluate the binding affinity of the selected flavonoids to the enzymes ?-glucosidase, ?-amylase, and glucokinase. Results/findings: The results showed that All three flavonoids exhibited strong binding affinities to ?-glucosidase and ?-amylase, indicating their potential to inhibit carbohydrate-digesting enzymes. Conclutions: Flavonoids from medicinal plants have potential as natural antidiabetic agents by inhibiting glucose-metabolizing enzymes and modulating insulin pathways. Computational studies have shown strong target interactions and favorable pharmacokinetic profiles, although further in vitro and in vivo validation is needed. Limitations: The findings of this study were limited to in silico data, and further validation through in vitro and in vivo experiments is necessary to confirm their effectiveness and safety. Contribution: This research contributes to the field of pharmaceutical sciences and natural product-based drug development, providing valuable insights for researchers and healthcare professionals interested in alternative therapies for diabetes management.

Jurnal Ilmu Medis IndonesiaVol. 4(1)
Universitas Tunas Pembangunan (ID)
Openalex Percentile: Top 59%
Natural Antidiabetic Agents Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.