Structure Guided Natural Product Discovery: Isolation and Computational Optimization of Novel Baeckenone-Derived MurA Enzyme Inhibitors

Authors

  • Ilham Kurniawan Faculty of Medicine, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya 60294, Indonesia
  • Desmila Idola Faculty of Medicine, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya 60294, Indonesia
  • Ippei Niwata Department of Agricultural Chemistry, Faculty of Agriculture and Marine Sciences, Kochi University, Kochi 7808520, Japan
  • Aulia Umi Rohmatika Faculty of Medicine, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya 60294, Indonesia
  • Hisashi Muramatsu Department of Agricultural Chemistry, Faculty of Agriculture and Marine Sciences, Kochi University, Kochi 7808520, Japan
  • Chul-Sa Kim Department of Agricultural Chemistry, Faculty of Agriculture and Marine Sciences, Kochi University, Kochi 7808520, Japan
  • Takehiro Kashiwagi Department of Agricultural Chemistry, Faculty of Agriculture and Marine Sciences, Kochi University, Kochi 7808520, Japan
  • I Made Artika Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, West Java 16680, Indonesia
  • Wien Kusharyoto National Research and Innovation Agency, Jakarta Pusat 10340, Indonesia
  • Fachrur Rizal Mahendra Bioinformatic Research Center, Indonesian Institute of Bioinformatics, Jawa Timur 65162, Indonesia

DOI:

https://doi.org/10.48048/tis.2026.13006

Keywords:

Antibacterial, Baeckenones, Molecular dynamics, Multidrug-Resistant bacteria, MurA inhibitor

Abstract

The rapid spread of multidrug-resistant bacteria has created an urgent, global need for novel antibacterial agents capable of overcoming existing resistance mechanisms. This computational study employs an integrated in silico approach to explore the potential of baeckenone compounds as MurA enzyme inhibitor. We report the isolation of 3 compounds from Baeckea frutescens: (5,7-dihydroxy-8-(1-(2-hydroxy- 4-methoxy-3,3,5-trimethyl -6-oxocyclohexa-1,4-dien-1-yl)-2-methylpropyl)-6-methyl-2-phenylchroman-4-one), Baeckenone B, and Baeckenone L (a novel phoroglucinol). These natural compounds served as starting points for in silico structure-based optimization to predict enhanced MurA binding. All derivatives were evaluated for predicted drug likeness, bioactivity scores, and toxicity profile. Molecular docking against MurA was validated by successful re-docking of fosfomycin (RMSD = 0.394 Å). Binding stability was further assessed through 20 ns molecular dynamics (MD) simulations and MM-PBSA free energy calculations. Structural optimization predicted improved drug-likeness (all modified derivatives complied with Lipinski’s Rule of Five), enhanced bioactivity scores, and suggested in silico membrane integrity antagonist potential without predicted toxicity. Docking analysis indicated higher predicted binding affinities for modified compounds (ΔG = ‒7.3 to ‒7.7 kcal/mol), surpassing the non-covalent binding component of fosfomycin (ΔG = ‒4.5 kcal/mol). MD simulations confirmed enhanced complex stability, with modified ligands exhibiting lower RMSD (0.612 - 1.120 Å), reduced residue fluctuations (RMSF), and favorable MM-PBSA binding energies. Modified Baeckenone B showed the most promising predicted profile (ΔG = ‒7.4 kcal/mol, Ki = 0.58 µM), and stable binding (RMSD = 0.612 Å). This computational study provides a framework for prioritizing baeckenone derivatives for future experimental validation as novel antibacterial agents against multidrug-resistant pathogens.

HIGHLIGHTS

  • A new phloroglucinol, Baeckenone L, was successfully isolated from Baeckea frutescens.
  • Structure-based optimization enhanced predicted drug-likeness and bioactivity profiles.
  • Modified derivatives showed superior predicted non-covalent binding compared to fosfomycin’s non-covalent component under the same docking protocol, though fosfomycin’s clinical mechanism involves covalent inhibition.
  • MD simulations confirmed superior stability and favorable energetics of optimized ligands.
  • Modified Baeckenone B emerged as a computationally promising candidate for MurA inhibition, with predicted sub-micromolar affinity and favorable drug-like properties, warranting experimental validation.

GRAPHICAL ABSTRACT

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Published

2026-04-20

How to Cite

Kurniawan, I., Idola, D., Niwata, I., Rohmatika, A. U., Muramatsu, H., Kim, C.-S., Kashiwagi, T., Artika, I. M., Kusharyoto, W., & Mahendra, F. R. (2026). Structure Guided Natural Product Discovery: Isolation and Computational Optimization of Novel Baeckenone-Derived MurA Enzyme Inhibitors. Trends in Sciences, 23(10), 13006. https://doi.org/10.48048/tis.2026.13006