Metabolomics-Driven LC-HRMS Identification and Multi-Target Computational Pharmacology of Shzygium polyanthum Bioactives for Mechanism-Based Precision Management of Type 2 Diabetes Mellitus

  • Said Haikal Alfajar Universitas Sumatera Utara, Medan, Indonesia
  • Urip Harahap Universitas Sumatera Utara, Medan, Indonesia
  • Aminah Dalimunthe Universitas Sumatera Utara, Medan, Indonesia
  • Nur Aira Juwita Universitas Sumatera Utara, Medan, Indonesia
  • Rony Abdi Syahputra Universitas Sumatera Utara, Medan, Indonesia
Keywords: Computational Pharmacology, Drug-Likeness, Enzyme Inhibitors, Herbal Medicine, Molecular Docking.

Abstract

Type 2 Diabetes Mellitus (T2DM) continues to be a major cause of mortality and metabolic complications in developing nations, highlighting the urgent need for safer and more accessible therapies. Herbal bioactives from Syzygium polyanthum (SYPOL) have gained attention due to their traditional use in managing blood glucose levels. Nevertheless, the molecular mechanisms underlying their antidiabetic effects remain poorly understood. This study employed an integrative in silico approach to evaluate the interactions between SYPOL-derived compounds and ten key protein targets involved in T2DM pathogenesis, including HK2, AKT1, PYGL, INSR, PYGM, IGF1R, PPARG, SLC2A1, MAPK3, and GCK. Ethanolic leaf extracts of SYPOL were analyzed using Liquid Chromatography–High Resolution Mass Spectrometry (LC-HRMS) for phytochemical profiling. Detected compounds were screened for structural availability, toxicity, ADME properties, and compliance with Lipinski's Rule of Five prior to molecular docking. From 9.834 detected phytochemical features, 31 compounds met the selection criteria and were docked against the ten diabetes-related targets. The simulations revealed stable interactions within active site regions, primarily driven by hydrogen bonding and favorable binding energies, suggesting potential modulation of glucose metabolism and insulin signaling pathways. ADME profiling indicated acceptable pharmacokinetic properties, with most compounds satisfying Lipinski's parameters. Toxicity prediction showed a 54.83% probability of nephrotoxicity, emphasizing the importance of safety validation in future studies SYPOL contains multi-target bioactive compounds with potential to regulate glucose homeostasis. This computational analysis provides a mechanistic basis for subsequent experimental research and supports the development of SYPOL-based phytotherapeutics for T2DM management.

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Published
2026-06-04
How to Cite
Alfajar, S. H., Harahap, U., Dalimunthe, A., Juwita, N. A., & Syahputra, R. A. (2026). Metabolomics-Driven LC-HRMS Identification and Multi-Target Computational Pharmacology of Shzygium polyanthum Bioactives for Mechanism-Based Precision Management of Type 2 Diabetes Mellitus. International Journal of Science and Society, 8(2), 223-241. Retrieved from https://www.ijsoc.goacademica.com/index.php/ijsoc/article/view/1673
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Vol 8 No 2 (2026): International Journal of Science and Society (IJSOC)
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