Molecular Docking Study Of Active Compounds Of Purslane (Portulaca oleracea L.) As Antioxidant Enzyme Activators

Nucke Aurelya Pramesti; Tiara Ajeng Listyani; Anna Fitriawati

doi:10.55227/ijhet.v5i3.1220

Authors

Nucke Aurelya Pramesti Program Studi Sarjana Farmasi, Fakultas Ilmu Kesehatan Universitas Duta Bangsa Surakarta
Tiara Ajeng Listyani Program Studi Sarjana Farmasi, Fakultas Ilmu Kesehatan Universitas Duta Bangsa Surakarta
Anna Fitriawati Program Studi Sarjana Farmasi, Fakultas Ilmu Kesehatan Universitas Duta Bangsa Surakarta

DOI:

https://doi.org/10.55227/ijhet.v5i3.1220

Keywords:

Purslane, Nrf2, Molecular Docking, Antioxidant, Adme-Toxicity

Abstract

Oxidative stress resulting from an imbalance between Reactive Oxygen Species (ROS) and endogenous antioxidant systems contributes to various degenerative diseases. Activation of the Keap1-Nrf2 pathway plays a crucial role in upregulating antioxidant enzyme expression. Purslane (*Portulaca oleracea* L.) is known to be rich in phenolic compounds and flavonoids with antioxidant potential; however, studies regarding its molecular interactions with the Keap1-Nrf2 pathway remain limited. This study aimed to determine molecular interaction patterns, predict ADME and toxicity profiles, and identify the active compound in purslane with the greatest potential as an Nrf2 antioxidant enzyme activator. This was a quantitative, pre-experimental *in silico* study utilizing AutoDock Vina (via the PyRx platform) for molecular docking, VegaZZ and PyMOL for preparation and visualization, and SwissADME and pkCSM for ADME-toxicity prediction. Docking results revealed that compounds such as Taraxerol, Hesperidin, Quercetin-O-hexoside, Neochlorogenic acid, and Chlorogenic acid exhibited favorable binding affinities (RMSD ≤2 Å) and formed non-covalent interactions with key residues, such as GLN530 and SER508. Most compounds demonstrated ADME and toxicity profiles supporting their development as oral drug candidates with low safety risks. Taraxerol was identified as the best compound, as it met the established criteria across all testing parameters. Active compounds in purslane show potential as Nrf2 activators; although no single compound met every criterion for an ideal drug candidate, Taraxerol emerged as the most promising candidate, warranting further structural optimization to assess its functional efficacy.

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References

Agu, P. C., Afiukwa, C. A., Orji, O. U., Ezeh, E. M., Ofoke, I. H., Ogbu, C. O., Ugwuja, E. I., & Aja, P. M. (2023). Molecular docking as a tool for the discovery of molecular targets of nutraceuticals in diseases management. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-40160-2

Alzain, A. A., Mukhtar, R. M., Abdelmoniem, N., Shoaib, T. H., Osman, W., Alsulaimany, M., Aljohani, A. K. B., Almadani, S. A., Alsaadi, B. H., Althubyani, M. M., Mohamed, S. G. A., Mohamed, G. A., & Ibrahim, S. R. M. (2023). Modulation of NRF2/KEAP1-Mediated Oxidative Stress for Cancer Treatment by Natural Products Using Pharmacophore-Based Screening, Molecular Docking, and Molecular Dynamics Studies. Molecules, 28(16), 1–14. https://doi.org/10.3390/molecules28166003

Amin, M. L. (2021). P-glycoprotein inhibition for optimal drug delivery. Drug Target Insights, 2021(7), 27–34. https://doi.org/10.4137/DTI.S12519

Aziz, W. M., Ahmed, S. A., Shaker, S. E., Fayed, D. B., Metwally, N. S., & Shawky, H. (2024). Portulaca oleracea L seed extracts counteract diabetic nephropathy through SDF-1/IL10/PPARγ–mediated tuning of keap1/Nrf2 and NF-κB transcription in Sprague Dawley rats. Diabetology and Metabolic Syndrome , 16(1), 1–16. https://doi.org/10.1186/s13098-024-01330-y

Bansal, P., Kumar, R., Singh, J., & Dhanda, S. (2021). In silico molecular docking of SARS-CoV-2 surface proteins with microbial non-ribosomal peptides: identification of potential drugs. Journal of Proteins and Proteomics, 12(3), 177–184. https://doi.org/10.1007/s42485-021-00072-z

Bueso-Bordils, J. I., Antón-Fos, G. M., Martín-Algarra, R., & Alemán-López, P. A. (2024). Overview of Computational Toxicology Methods Applied in Drug and Green Chemical Discovery. Journal of Xenobiotics, 14(4), 1901–1918. https://doi.org/10.3390/jox14040101

Culletta, G., Buttari, B., Arese, M., Brogi, S., Almerico, A. M., Saso, L., & Tutone, M. (2024). Natural products as non-covalent and covalent modulators of the KEAP1/NRF2 pathway exerting antioxidant effects. European Journal of Medicinal Chemistry, 270. https://doi.org/10.1016/j.ejmech.2024.116355

Dai, Z., Wu, Y., Xiong, Y., Wu, J., Wang, M., Sun, X., Ding, X., Yang, L., Sun, X., & Ge, G. (2024). CYP1A inhibitors: Recent progress, current challenges, and future perspectives. Medicinal Research Reviews, 44(1), 169–234. https://doi.org/10.1002/med.21982

Etukudo, E. M., Usman, I. M., Oviosun, A., Ojiakor, V. O., Makena, W., Owembabazi, E., Aja, P. M., Mutume Nzanzu Vivalya, B., Archibong, V. B., & Anyanwu, E. (2025). Exploring the Neuroprotective Potentials of Flavonoid Metabolites in Syzygium aromaticum: A Review with in-silico Insight to Therapeutic Potential. Journal of Experimental Pharmacology, 17(August), 587–611. https://doi.org/10.2147/JEP.S536765

Foti, R. S. (2023). Cytochrome P450 and Other Drug-Metabolizing Enzymes As Therapeutic Targets. Drug Metabolism and Disposition, 51(8), 936–949. https://doi.org/10.1124/dmd.122.001011

Fransiski, C. H., Hami Seno, D. S., & Safithri, M. (2023). IDENTIFIKASI SENYAWA PADA BATANG KROKOT (Portulaca oleracea L.) DAN POTENSINYA SEBAGAI AKTIVATOR SUPEROKSIDA DISMUTASE IN SILICO. Jurnal Farmamedika (Pharmamedica Journal), 8(1), 85–94. https://doi.org/10.47219/ath.v8i1.197

Hassanein, E. H. M., Althagafy, H. S., Baraka, M. A., Abd-alhameed, E. K., Ibrahim, I. M., Abd El-Maksoud, M. S., Mohamed, N. M., & Ross, S. A. (2024). The promising antioxidant effects of lignans: Nrf2 activation comes into view. Naunyn-Schmiedeberg’s Archives of Pharmacology, 397(9), 6439–6458. https://doi.org/10.1007/s00210-024-03102-x

Huang, S. Y., Grinter, S. Z., & Zou, X. (2024). Scoring functions and their evaluation methods for protein-ligand docking: Recent advances and future directions. Physical Chemistry Chemical Physics, 12(40), 12899–12908. https://doi.org/10.1039/c0cp00151a

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., Zaslavsky, L., Zhang, J., & Bolton, E. E. (2021). PubChem in 2021: New data content and improved web interfaces. Nucleic Acids Research, 49(D1), D1388–D1395. https://doi.org/10.1093/nar/gkaa971

Komura, H., Watanabe, R., & Mizuguchi, K. (2023). The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery. Pharmaceutics, 15(11), 1–30. https://doi.org/10.3390/pharmaceutics15112619

Listyani, T. A., Ramadhani, D. A., & Raharjo, D. (2024). Analisis Docking Molekuler Beserta Prediksi Adme Senyawa Derivat Flavonoid Sebagai Inhibitor Enzim 15-Lipoxygenase-2. Bhamada: Jurnal Ilmu Dan Teknologi Kesehatan (E-Journal), 15(2), 73–83. https://doi.org/10.36308/jik.v15i2.626

Miyazaki, K., Sasaki, A., & Mizuuchi, H. (2023). Advances in the Evaluation of Gastrointestinal Absorption Considering the Mucus Layer. Pharmaceutics, 15(12). https://doi.org/10.3390/pharmaceutics15122714

Mohanty, M., & Mohanty, P. S. (2023). Molecular docking in organic, inorganic, and hybrid systems: a tutorial review. Monatshefte Fur Chemie, 154(7), 683–707. https://doi.org/10.1007/s00706-023-03076-1

Mokhosoev, I. M., Astakhov, D. V., Terentiev, A. A., & Moldogazieva, N. T. (2024). Human Cytochrome P450 Cancer-Related Metabolic Activities and Gene Polymorphisms: A Review. Cells, 13(23). https://doi.org/10.3390/cells13231958

Naeem, A., Ming, Y., Pengyi, H., Jie, K. Y., Yali, L., Haiyan, Z., Shuai, X., Wenjing, L., Ling, W., Xia, Z. M., Shan, L. S., & Qin, Z. (2022). The fate of flavonoids after oral administration: a comprehensive overview of its bioavailability. Critical Reviews in Food Science and Nutrition, 62(22), 6169–6186. https://doi.org/10.1080/10408398.2021.1898333

Noga, M., & Jurowski, K. (2025). Qualitative and quantitative in silico toxicity profiling of “angel dust”: phencyclidine (PCP) analogues as new psychoactive substances (3-HO-PCP, 3-MeO-PCP, 4-MeO-PCP, 3-HO-PCE, 3-MeO-PCE, 4-MeO-PCE). Archives of Toxicology. https://doi.org/10.1007/s00204-025-04242-6

Paggi, J. M., Pandit, A., & Dror, R. O. (2024). The Art and Science of Molecular Docking. Annual Review of Biochemistry, 93(1), 389–410. https://doi.org/10.1146/annurev-biochem-030222-120000

Pardridge, W. M. (2020). BBB Biology and Methodology. April, 556–569.

Pavithra Adi Venakata Lakshmi S, Govinda Rao Kamala, & Saraswathi S. (2025). A Review on Advances Computer-Aided Drug Design and Its Applications in Drug Discovery. Journal of Pharma Insights and Research, 3(4), 062–069. https://doi.org/10.69613/9b88sm25

Rimac, H., Grishina, M., & Potemkin, V. (2021). Use of the Complementarity Principle in Docking Procedures: A New Approach for Evaluating the Correctness of Binding Poses. Journal of Chemical Information and Modeling, 61(4), 1801–1813. https://doi.org/10.1021/acs.jcim.0c01382

Sahu, D., Rathor, L. S., Dwivedi, S. D., Shah, K., Chauhan, N. S., Singh, M. R., & Singh, D. (2024). A Review on Molecular Docking As an Interpretative Tool for Molecular Targets in Disease Management. Assay and Drug Development Technologies, 22(1), 40–50. https://doi.org/10.1089/adt.2023.060

Sharma, G., Kumar, N., Sharma, C. S., Alqahtani, T., Tiruneh, Y. K., Sultana, S., Rolim Silva, G. V., de Lima Menezes, G., Zaki, M. E. A., & Nobre Oliveira, J. I. (2025). Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-86016-9

Sheikh, K. A., Mir, R. H., Dar, M. O., Wali, A. F., Qadir, I., Nazir, S., Zargar, M. I., Talath, S., Sridhar, S. B., Shareef, J., & Masoodi, M. H. (2025). Phytochemical screening, antioxidant, and antimicrobial analysis of Portulaca oleracea seeds with in-silico molecular docking insights. Journal of Genetic Engineering and Biotechnology, 23(3), 100516. https://doi.org/10.1016/j.jgeb.2025.100516

Shivanika, C., Deepak Kumar, S., Ragunathan, V., Tiwari, P., Sumitha, A., & Brindha Devi, P. (2022). Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. Journal of Biomolecular Structure and Dynamics, 40(2), 585–611. https://doi.org/10.1080/07391102.2020.1815584

Tripathi, S., Kharkwal, G., Mishra, R., & Singh, G. (2024). Nuclear factor erythroid 2-related factor 2 (Nrf2) signaling in heavy metals-induced oxidative stress. Heliyon, 10(18), e37545. https://doi.org/10.1016/j.heliyon.2024.e37545

Wang, K., Huang, Y., Wang, Y., You, Q., & Wang, L. (2024). Recent advances from computer-aided drug design to artificial intelligence drug design. RSC Medicinal Chemistry, 15(12), 3978–4000. https://doi.org/10.1039/d4md00522h

Zhang, H., Chen, G., Yang, J., Yang, C., & Guo, M. (2022). Screening and characterisation of potential antioxidant, hypoglycemic and hypolipidemic components revealed in Portulaca oleracea via multi-target affinity ultrafiltration LC–MS and molecular docking. Phytochemical Analysis, 33(2), 272–285. https://doi.org/10.1002/pca.3086

Zhang, J., Li, H., Zhang, Y., Huang, J., Ren, L., Zhang, C., Zou, Q., & Zhang, Y. (2025). Computational toxicology in drug discovery: applications of artificial intelligence in ADMET and toxicity prediction. Briefings in Bioinformatics, 26(5). https://doi.org/10.1093/bib/bbaf533