Deciphering Depression-Targeted Mechanisms of Pandanus odorifer Leaf Extracts Based on Component Analysis and Integrated Molecular Approaches

Authors

  • Ersanda Nurma Praditapuspa Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Hang Tuah, East Java 60111, Indonesia
  • Farizah Izazi Department of Biology Pharmacy, Faculty of Pharmacy, Universitas Hang Tuah, East Java 60111, Indonesia
  • Dita Savitri Bachelor Program of Pharmacy, Faculty of Pharmacy, Universitas Hang Tuah, East Java 60111, Indonesia
  • Rina Andayani Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Hang Tuah, East Java 60111, Indonesia
  • Saipul Maulana Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Universitas Tadulako, Central Sulawesi 94148, Indonesia
  • Mohammad Rizki Fadhil Pratama Department of Pharmacy, Faculty of Health Science, Universitas Muhammadiyah Palangkaraya, Kalimantan Tengah 73111, Indonesia
  • Masteria Yunovilsa Putra Research Center for Vaccine and Drugs, National Research and Innovation Agency, West Java 16911, Indonesia
  • Juni Ekowati Department of Pharmaceutical Sciences, Faculty of Pharmacy, Universitas Airlangga, East Java 60115, Indonesia

DOI:

https://doi.org/10.48048/tis.2025.9320

Keywords:

Network pharmacology, In silico, Depression, Molecular dynamics, Pandanus odorifer

Abstract

Introduction: Mental health is a worldwide health problem. Antidepressants have therapeutic effects but after prolonged use, they can cause unwanted side effects. Seeing the great potential of coastal plants such as sea pandanus (Pandanus odorifer) attracts attention in creating a more effective and safe treatment. The aim of this study is to identify the compounds contained in sea pandanus and elucidate the molecular mechanism in the target proteins of depressive diseases. Materials and methods: LC-MS has been used to identify compounds in sea pandanus. The network pharmacology approach used Cytoscape 3.9.1, OMIM, Disgenet, SEA, SwissTarget, STRING 2.0.0, Metascape, and Kyoto Encyclopedia of Genes and Genomes (KEGG) to predict the molecular antidepressant mechanism of the metabolite compounds. Validation was achieved using MOE with MAOA receptor (PDB ID: 2Y5Z). Molecular dynamics simulation using Maestro Schrödinger 2020-1 software. Results and discussion: A total of 19 active compounds were identified through LC-MS. Network pharmacology analysis showed that the MAOA target was the most influential protein target in the network pharmacology study of antidepressants from metabolite compounds of sea pandanus methanol extract. The results of in silico validation and molecular dynamics simulation support the network pharmacology findings. Benzylcarbonyl-Lys-Dab-Arg-NH2 compound showed higher affinity to MAOA receptor target compared to standard drug (fluoxetine) with S score −10.7455 kcal/mol and MMGBSA value −68.0669 kcal/mol. Conclusions: The compound Benzylcarbonyl-Lys-Dab-Arg-NH2 showed higher binding affinity towards MAOA compared to the native ligand and drug fluoxetine, also maintaining a s2interaction within the MAOA active site, indicating that Pandanus odorifer has significant promise as a novel antidepressant agent. These findings provide a strong basis for further investigation into its efficacy and safety in a clinical setting, potentially leading to the development of more effective and targeted treatments for depression.

HIGHLIGHTS

  • This article focused on the exploration of Pandanus odorifer leaves as a potential source of bioactive compounds for depression therapy.
  • Pandanus odorifer were profiled using LC-MS (Liquid Chromatography-Mass Spectrometry) technique to identify metabolite compounds.
  • Computational-based approaches were conducted using network pharmacology, molecular docking, and molecular dynamics.
  • Network pharmacology was used to understand the interaction of bioactive compounds with molecular targets related to depression.
  • Molecular docking was done to evaluate the potential binding of the compound to depression-related protein targets.
  • Molecular dynamics was used to analyze the stability of compound interactions with protein targets.

GRAPHICAL ABSTRACT

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Published

2025-02-28