IN SILICO ANALYSIS OF ANTIFUNGAL POTENTIAL AND PHARMACOKINETIC CHARACTERISTICS OF SHALLOT (Allium cepa L.) SECONDARY METABOLITES USING PASS ONLINE AND SWISSADME

ANALISIS IN SILICO POTENSI ANTIFUNGI DAN KARAKTERISTIK FARMAKOKINETIK METABOLIT SEKUNDER BAWANG MERAH (Allium cepa L.) MENGGUNAKAN PASS ONLINE DAN SWISSADME

Authors

  • Ahdilan Juliansyah College Student Author
  • Rahadatul Aisy Wafadhiyanti Indrapaslah College Student Author
  • Erwandi Erwandi College Student Author
  • Hikmal Hikmal College Student Author
  • Juliadi Nur Rahim College Student Author
  • Dodi Iskandar Author

DOI:

https://doi.org/10.71275/roce.v3i2.208

Keywords:

Shallot, Allium cepa L antifungal activity, secondary metabolites, PASS Online, SwissADME, drug-likeness

Abstract

Shallot (Allium cepa L.) contains various secondary metabolites with potential biological activities, including antifungal activity. This study aimed to evaluate the antifungal potential and pharmacokinetic characteristics of secondary metabolites from shallot using in silico approaches with PASS Online and SwissADME. PASS Online analysis demonstrated that all identified compounds possessed potential antifungal activity with varying Probability of Activity (Pa) values. Among the compounds, (+)-Dihydroeleutherinol showed the highest antifungal potential with a Pa value of 0.608, followed by (-)-3-[2-(Acetyloxy)propyl]-2-hydroxy-8-methoxy-1,4-naphthoquinone and (-)-Hongconin with Pa values of 0.599 and 0.594, respectively. The antifungal activity of these compounds is associated with their ability to disrupt fungal cell membranes, inhibit cell wall synthesis, and induce oxidative stress via the formation of reactive oxygen species (ROS). SwissADME analysis indicated that all compounds exhibited favorable pharmacokinetic and physicochemical profiles, including high water solubility, balanced lipophilicity, and acceptable bioavailability scores ranging from 0.55 to 0.56. Drug-likeness analysis further revealed that all compounds complied with Lipinski, Ghose, Veber, Egan, and Muegge rules, indicating good oral absorption potential and membrane permeability. In addition, physicochemical property analysis showed that all compounds had molecular weights below 500 g/mol, low topological polar surface area (TPSA), balanced hydrogen-bonding properties, and moderate molecular flexibility, which are important characteristics for drug development. Compounds such as (+)-Eleutherin, (-)-Isoeleutherin, and (+)-Dihydroeleutherinol demonstrated particularly promising profiles due to their balanced physicochemical and pharmacokinetic properties. Overall, the combined PASS Online and SwissADME analyses suggest that shallot secondary metabolites have strong potential as natural antifungal agents. However, further in vitro and in vivo studies are required to validate their biological activity, safety, toxicity, and mechanisms of action against pathogenic fungi. 

 

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Author Biographies

  • Ahdilan Juliansyah, College Student

    Plantation Crop Cultivation Study Program

  • Rahadatul Aisy Wafadhiyanti Indrapaslah, College Student

    Plantation Crop Cultivation Study Program

  • Erwandi Erwandi, College Student

    Plantation Crop Cultivation Study Program

  • Hikmal Hikmal, College Student

    Plantation Crop Cultivation Study Program

  • Juliadi Nur Rahim, College Student

    Plantation Crop Cultivation Study Program

  • Dodi Iskandar

    Integrated Plantation Product Processing Study Program

References

A. Ibrahim, S., & F. Rizk, H. (2021). Synthesis and Biological Evaluation of Thiazole Derivatives. Azoles - Synthesis, Properties, Applications and Perspectives, 1–20. https://doi.org/10.5772/intechopen.93037

Aarón, R.-H., Sheila, C.-M., Julio Emmanuel, G.-P., Óscar, J.-G., Aurelio, L.-M., & Jocksan Ismael, M.-C. (2025). In Silico strategies for drug discovery: optimizing natural compounds from foods for therapeutic applications. Discover Chemistry, 2(1). https://doi.org/10.1007/s44371-025-00201-3

Agoni, C., Olotu, F. A., Ramharack, P., & Soliman, M. E. (2020). Druggability and drug-likeness concepts in drug design: are biomodelling and predictive tools having their say? Journal of Molecular Modeling, 26(6), 120. https://doi.org/10.1007/s00894-020-04385-6

Althubaiti, A. (2023). Sample size determination: A practical guide for health researchers. Journal of General and Family Medicine, 24(2), 72–78. https://doi.org/10.1002/jgf2.600

Ayoobi, A., & Choi, H. W. (2026). In Silico Molecular Docking and Pharmacokinetic Evaluation of Cannabinoid Derivatives as Multi-Target Inhibitors for EGFR, VEGFR-1, and VEGFR-2 Proteins. Current Issues in Molecular Biology, 48(2), 1–33. https://doi.org/10.3390/cimb48020204

Borba-Santos, L. P., Nicoletti, C. D., Vila, T., Ferreira, P. G., Araújo-Lima, C. F., Galvão, B. V. D., Felzenszwalb, I., de Souza, W., de Carvalho da Silva, F., Ferreira, V. F., Futuro, D. O., & Rozental, S. (2022). A novel naphthoquinone derivative shows selective antifungal activity against Sporothrix yeasts and biofilms. Brazilian Journal of Microbiology : [Publication of the Brazilian Society for Microbiology], 53(2), 749–758. https://doi.org/10.1007/s42770-022-00725-1

Chen, Q., Yang, M., Lai, X., Hu, J., Fazal, A., Zhang, Y., Lv, X., Xiao, J., Fan, Z., Pan, Z., Yin, T., Sun, S., Lu, G., Qi, J., Lin, H., Wen, Z., Yang, Y., & Han, H. (2026). Antifungal potential of naphthoquinone derivatives: screening of shikonin-based compounds and mechanistic insights into 5,8-dihydroxy-1,4-naphthoquinone against Candida albicans in vitro and in vivo. Microbiology Spectrum, 14(4), e0243825. https://doi.org/10.1128/spectrum.02438-25

Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7, 42717. https://doi.org/10.1038/srep42717

Elhamouly, N. A., Hewedy, O. A., Zaitoon, A., Miraples, A., Elshorbagy, O. T., Hussien, S., El-Tahan, A., & Peng, D. (2022). The hidden power of secondary metabolites in plant-fungi interactions and sustainable phytoremediation. Frontiers in Plant Science, 13, 1044896. https://doi.org/10.3389/fpls.2022.1044896

Fagerholm, U. (2022). Investigation of Molecular Weights and Pharmacokinetic Characteristics of Older and Modern Small Drugs. BioRxiv, 2022.09.21.508888.

Feng, Q., De Chavez, D., Kihlberg, J., & Poongavanam, V. (2025). A membrane permeability database for nonpeptidic macrocycles. Scientific Data , 12(1), 1–11. https://doi.org/10.1038/s41597-024-04302-z

Jiang, J., Keniya, M. V, Puri, A., Zhan, X., Cheng, J., Wang, H., Lin, G., Lee, Y.-K., Jaber, N., Zhao, C., Pang, C., Hassoun, Y., Zheng, H., Shor, E., Shi, Z., Lee, S.-H., Xu, M., Perlin, D. S., & Dai, W. (2025). Molecular landscape of the fungal plasma membrane and implications for antifungal action. Nature Communications, 16(1), 9125. https://doi.org/10.1038/s41467-025-64171-x

Miebs, G., Mielniczuk, A., Kadziński, M., & Bachorz, R. A. (2024). Beyond the Arbitrariness of Drug-Likeness Rules: Rough Set Theory and Decision Rules in the Service of Drug Design. Applied Sciences (Switzerland), 14(21). https://doi.org/10.3390/app14219966

Moldovan, C., Frumuzachi, O., Babotă, M., Barros, L., Mocan, A., Carradori, S., & Crişan, G. (2022). Therapeutic Uses and Pharmacological Properties of Shallot (Allium ascalonicum): A Systematic Review. Frontiers in Nutrition, 9, 903686. https://doi.org/10.3389/fnut.2022.903686

Oyejide, A. J., Adekunle, Y. A., Abodunrin, O. D., & Atoyebi, E. O. (2025). Artificial intelligence, computational tools and robotics for drug discovery, development, and delivery. Intelligent Pharmacy, 3(3), 207–224. https://doi.org/10.1016/j.ipha.2025.01.001

Pogodin, P. V, Lagunin, A. A., Rudik, A. V, Filimonov, D. A., Druzhilovskiy, D. S., Nicklaus, M. C., & Poroikov, V. V. (2018). How to Achieve Better Results Using PASS-Based Virtual Screening: Case Study for Kinase Inhibitors. Frontiers in Chemistry, 6, 133. https://doi.org/10.3389/fchem.2018.00133

Prabawati, S., Widayanti, S. M., Sulistyaningrum, A., Setyadjit, S., Arif, A. Bin, Winarti, C., Jamal, I. B., Munarso, S. J., Waryat, W., Budiyanto, A., & Risfaheri, R. (2026). Physiology, Nutrition, and Postharvest Technology on Shallots (Allium cepa L. aggregatum): A Review. Scientifica, 2026(1), 8328535. https://doi.org/https://doi.org/10.1155/sci5/8328535

Roney, M., & Mohd Aluwi, M. F. F. (2024). The importance of in-silico studies in drug discovery. Intelligent Pharmacy, 2(4), 578–579. https://doi.org/10.1016/j.ipha.2024.01.010

Sadybekov, A. V, & Katritch, V. (2023). Computational approaches streamlining drug discovery. Nature, 616(7958), 673–685. https://doi.org/10.1038/s41586-023-05905-z

Sharma, A., Raut, S. S., Shukla, A., Singh, A., & Mishra, A. (2026). Therapeutic targeting of the mitochondrial dysfunction-PANoptosis axis: Mechanistic insights and emerging strategies. Translational Research, 291, 1–39. https://doi.org/https://doi.org/10.1016/j.trsl.2026.03.004

Soorni, A., Akrami, A. M., Abolghasemi, R., & Vahedi, M. (2021). Transcriptome and phytochemical analyses provide insights into the organic sulfur pathway in Allium hirtifolium. Scientific Reports, 11(1), 1–13. https://doi.org/10.1038/s41598-020-80837-6

Tanwar, S., Kalra, S., & Bari, V. K. (2024). Insights into the role of sterol metabolism in antifungal drug resistance: a mini-review. Frontiers in Microbiology, 15, 1409085. https://doi.org/10.3389/fmicb.2024.1409085

van Rhijn, N., & Rhodes, J. (2025). Evolution of antifungal resistance in the environment. Nature Microbiology, 10(8), 1804–1815. https://doi.org/10.1038/s41564-025-02055-y

Wang, B., Liu, Q., Zhao, W., Zhang, T., Zhang, D., Sutcharitchan, C., & Li, S. (2026). Revolutionizing drug discovery from natural products: The roles of artificial intelligence and multi-omics in accelerating innovation. Acta Pharmaceutica Sinica B, (xxx). https://doi.org/10.1016/j.apsb.2025.12.030

Zeki, N. M., & Mustafa, Y. F. (2024). Digital alchemy: Exploring the pharmacokinetic and toxicity profiles of selected coumarin-heterocycle hybrids. Results in Chemistry, 10, 101754. https://doi.org/https://doi.org/10.1016/j.rechem.2024.101754

Zhang, S., Liu, K., Liu, Y., Hu, X., & Gu, X. (2025). The role and application of bioinformatics techniques and tools in drug discovery. Frontiers in Pharmacology, 16(February), 1–12. https://doi.org/10.3389/fphar.2025.1547131

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Published

2026-08-08

How to Cite

IN SILICO ANALYSIS OF ANTIFUNGAL POTENTIAL AND PHARMACOKINETIC CHARACTERISTICS OF SHALLOT (Allium cepa L.) SECONDARY METABOLITES USING PASS ONLINE AND SWISSADME: ANALISIS IN SILICO POTENSI ANTIFUNGI DAN KARAKTERISTIK FARMAKOKINETIK METABOLIT SEKUNDER BAWANG MERAH (Allium cepa L.) MENGGUNAKAN PASS ONLINE DAN SWISSADME. (2026). ROCE : Jurnal Pertanian Terapan, 3(2). https://doi.org/10.71275/roce.v3i2.208

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