Predicting Pharmacokinetic Properties of Small Molecules Using Graph-Based Signature (pkCSM) of Kaempferol from Cherry Leaves (Muntingia Calabura L.)

Authors

  • Fendy Prasetyawan Universitas Kadiri
  • Yuneka Saristiana Universitas Kadiri
  • Mujtahid Bin Abd Kadir Universitas Muhammadiyah Makasar
  • Ratna Mildawati STIKes Ganesha Husada Kediri
  • Chandra Arifin Akademi Kesehatan Arga Husada
  • Abd Rofiq Akademi Kesehatan Arga Husada
  • Widhi Astutik Institute Ilmu Kesehatan Bhakti Wiyata Kediri

DOI:

https://doi.org/10.55927/mpst.v1i4.3

Keywords:

Kaempferol, Muntingia calabura, pkCSM, Pharmacokinetics, Toxicity

Abstract

Kaempferol is a natural flavonoid found in many plants, including Muntingia calabura L. (cherry) leaves, and is known for its diverse pharmacological properties such as anti-inflammatory, antioxidant, anticancer, and antimicrobial activities. In this study, we aimed to predict the pharmacokinetic properties and toxicity profiles of kaempferol using an in silico approach via the pkCSM platform. The SMILES notation of kaempferol was obtained from the PubChem database and entered into the pkCSM server to analyze its ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) characteristics. The prediction results showed that kaempferol had a molecular weight of 286.239 g/mol and a LogP value of 2.2824, indicating moderate lipophilicity. Kaempferol has one rotatable bond, six hydrogen bond acceptors, and four hydrogen bond donors, which contribute to its molecular stability and pharmacological potential. In terms of absorption, kaempferol showed good human intestinal absorption (74.29%), although it was quite water soluble and showed limited Caco-2 permeability. It was identified as a substrate for P-glycoprotein but not an inhibitor of P-glycoprotein I or II. Kaempferol had a predicted volume of distribution (VDss) of 1.274 log L/kg and an unbound fraction of 0.178, indicating good distribution in body tissues. Predicted blood-brain barrier and central nervous system permeability were low, indicating limited CNS exposure

References

Ardianto, N., Prasetyawan, F., Saristiana, Y., Muslikh, F. A., Mildawati, R., & Dhafin, A. A. & Rofiq, A.(2023). Forensic Pharmacy Case Study: Identification of Hazardous Mercury Content as a Whitening Agent in Beauty Cream Products. International Journal of Contemporary Sciences (IJCS), 1(2), 85-90.

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(1), 42717. https://doi.org/10.1038/srep42717

Di, L., Kerns, E. H., Fan, K., McConnell, O. J., & Carter, G. T. (2003). High throughput artificial membrane permeability assay for blood–brain barrier. European Journal of Medicinal Chemistry, 38(3), 223–232. https://doi.org/10.1016/S0223-5234(03)00012-6

Ferreira, L. G., dos Santos, R. N., Oliva, G., & Andricopulo, A. D. (2015). Molecular docking and structure-based drug design strategies. Molecules, 20(7), 13384–13421. https://doi.org/10.3390/molecules200713384

Hopkins, A. L. (2008). Network pharmacology: The next paradigm in drug discovery. Nature Chemical Biology, 4(11), 682–690. https://doi.org/10.1038/nchembio.118

Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 46(1–3), 3–26. https://doi.org/10.1016/S0169-409X(00)00129-0

Mildawati, R., Saristiana, Y., Prasetyawan, F., Fadel, M. N., & Besan, E. J. (2025). Prediction of Kaempferol from Kersen Leaf (Muntingia calabura L.) as THIF1A Expression Inhibitor for Glioblastoma. JELE: Journal of English Literature and Education, 1(1), 25-31.

Muslikh, F. A., Prasetyawan, F., Hesturini, R. J., Sari, F., & Mawarni, O. K. (2023). Physicochemical and Pharmacokinetic Property Prediction of Substances in Centella asiatica using pkCSM: Prospects for the Creation of Therapeutic Formulations from Plant Isolates. International Journal of Global Sustainable Research, 1(3), 485-494.

Nababan, O. A., Oktadiana, I., Prasetyawan, F., Saristiana, Y., Muslikh, F. A., & Mildawati, R. (2024). Evaluasi Penggunaan Obat Pada Pasien Hipertensi Rawat Jalan Di Puskesmas “X” Kota Solo. Jurnal Media Akademik (JMA), 2(2).

Oktadiana, I., Daulay, M., Mildawati, R., Prasetyawan, F., Saristiana, Y., & Nugroho, B. P. (2024). Penyuluhan Dan Sosialisasi Tanaman Obat Keluarga Untuk Menurunkan Kadar Gula Darah Di Desa Batu Dua Kabupaten Simalungun. Abdi Masyarakat Vokasi, 1(1), 73-79.

Pires, D. E. V., Blundell, T. L., & Ascher, D. B. (2015). pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of Medicinal Chemistry, 58(9), 4066–4072. https://doi.org/10.1021/acs.jmedchem.5b00104

Prasetyawan, F., Salmasfattah, N., Muklish, F. A., & Saristiana, Y. (2024). Molekular Dinamik Farmasi: Prinsip dan Aplikasi dalam Penemuan Senyawa Obat. Borneo Novelty Publishing.

Prasetyawan, F., Saristiana, Y., Salmasfattah, N., Mildawati, R., Mayasari, S., & Zahra, I. (2024). Prediction of Hyoscine from Amethyst Fruit (Datura metel L.) as Beta-adrenergic Receptor Kinase Inhibitor for Heart Failure: Prediksi Hyoscine dari Buah Kecubung (Datura metel L.) sebagai Penghambat Reseptor Beta-adrenergik Kinase untuk Gagal Jantung. Al-Adawiyyah: Jurnal Sains, Farmasi dan Kesehatan, 1(2).

Saristiana, Y., Prasetyawan, F., & Mildawati, R. (2024). Prediction of Chalcone from Anting-Anting (Acalypha indica L.) for Feruloyl Esterase Inhibitor as Penyakit Alzheimer: Prediksi Kalkon dari Anting-Anting (Acalypha indica L.) untuk Inhibitor Feruloyl Esterase sebagai Penyakit Alzheimer. Al-Adawiyyah: Jurnal Sains, Farmasi dan Kesehatan, 1(2).

Sharma, N., & Vasudeva, N. (2016). Ethnopharmacological, phytochemical and pharmacological profile of genus Muntingia: A review. Asian Pacific Journal of Tropical Disease, 6(11), 887–891. https://doi.org/10.1016/S2222-1808(16)61151-2

Szakács, G., Váradi, A., Özvegy-Laczka, C., & Sarkadi, B. (2008). The role of ABC transporters in drug absorption, distribution, metabolism, excretion and toxicity (ADME–Tox). Drug Discovery Today, 13(9–10), 379–393. https://doi.org/10.1016/j.drudis.2007.12.010

Veber, D. F., Johnson, S. R., Cheng, H. Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n

Zanger, U. M., & Schwab, M. (2013). Cytochrome P450 enzymes in drug metabolism: Regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacology & Therapeutics, 138(1), 103–141. https://doi.org/10.1016/j.pharmthera.2012.12.007.

Downloads

Published

2025-04-30

How to Cite

Prasetyawan, F., Saristiana, Y., Kadir, M. B. A., Mildawati, R., Arifin, C., Rofiq, A., & Astutik, W. (2025). Predicting Pharmacokinetic Properties of Small Molecules Using Graph-Based Signature (pkCSM) of Kaempferol from Cherry Leaves (Muntingia Calabura L.). Multidisciplinary Perspectives in Science and Technology, 1(1), 25–44. https://doi.org/10.55927/mpst.v1i4.3

Issue

Section

Articles