EXPLORING PROTEIN TARGETS OF TRITERPENE SAPONINS (C₅₄H₈₆O₂₄): A BIOINFORMATICS APPROACH TO NOVEL THERAPEUTIC DEVELOPMENT

Authors

  • SETIYO BUDI SANTOSO Department of Pharmacy, Universitas Muhammadiyah Magelang, Indonesia. Center for Digital Pharmacy Studies (Diphars), Universitas Muhammadiyah Magelang, Indonesia. Division of Pharmacology and Clinical Pharmacy, Universitas Muhammadiyah Magelang, Indonesia
  • ALFIAN SYARIFUDDIN Department of Pharmacy, Universitas Muhammadiyah Magelang, Indonesia. Center for Digital Pharmacy Studies (Diphars), Universitas Muhammadiyah Magelang, Indonesia. Division of Biological Pharmacy, Universitas Muhammadiyah Magelang, Indonesia
  • ARIEF KUSUMA WARDANI Department of Pharmacy, Universitas Muhammadiyah Magelang, Indonesia. Center for Digital Pharmacy Studies (Diphars), Universitas Muhammadiyah Magelang, Indonesia. Division of Chemistry in Pharmacy, Universitas Muhammadiyah Magelang, Indonesia
  • VIAN PUTRI WIDIASTUTI Department of Pharmacy, Universitas Muhammadiyah Magelang, Indonesia. Center for Digital Pharmacy Studies (Diphars), Universitas Muhammadiyah Magelang, Indonesia
  • MAY FAHTUN NINDA Department of Pharmacy, Universitas Muhammadiyah Magelang, Indonesia. Center for Digital Pharmacy Studies (Diphars), Universitas Muhammadiyah Magelang, Indonesia

DOI:

https://doi.org/10.22159/ijap.2025.v17s3.04

Keywords:

Chronic diseases, Biological targets, Protein interactions

Abstract

Objective: The exploration of triterpene saponins as novel therapeutic agents is essential due to the rising prevalence of chronic diseases and limitations of current treatments. These compounds exhibit diverse biological activities, particularly anti-inflammatory and anticancer effects; however, their systematic identification and protein target interactions remain underexplored.

Methods: Triterpene saponin compounds were identified using the KNApSAcK database, prioritized via the ChEMBL database, and further analyzed using SuperPred to predict high-confidence protein interactions. A protein interaction matrix was constructed to map therapeutic targets and clinical indications. Furthermore, glycosidic linkage variations among the compounds were examined using a Structure–Activity Relationship (SAR) approach based on valence bond theory, providing a comprehensive bioinformatics-based framework for therapeutic potential assessment.

Results: Seven compounds classified as triterpene saponins (C₅₄H₈₆O₂₄) were selected. Structural variations were observed in sugar moieties, side chains, functional groups, stereochemistry, and glycosidic linkages, contributing to their chemical diversity and potential specificity in protein interactions.

Conclusion: Our study highlights the potential of triterpene saponins (C₅₄H₈₆O₂₄) as promising drug candidates targeting key proteins, including APEX1, TLR-4, and KinaseP110.

References

1. Valli SA, TM. Bioinformatic study of an antitumor protein Azurin. Asian J Pharm Clin Res. 2018 Jun 7;11(6):169-76. doi: 10.22159/ajpcr.2018.v11i6.23339.

2. Zhan C, Li X, Zhao Z, Yang T, Wang X, Luo B. Comprehensive analysis of the triterpenoid saponins biosynthetic pathway in Anemone flaccida by transcriptome and proteome profiling. Front Plant Sci. 2016 Jul 25;7:1094. doi: 10.3389/fpls.2016.01094, PMID 27504115.

3. Elekofehinti OO, Iwaloye O, Olawale F, Ariyo EO. Saponins in cancer treatment: current progress and future prospects. Pathophysiology. 2021 Jun 5;28(2):250-72. doi: 10.3390/pathophysiology28020017, PMID 35366261.

4. Setiyaningsih H, Hidayat IW, Syarifuddin A, Santoso SB, Wijayatri R. The ruling of novel drugs to the molecular targets on variant pathological. In: Pambuko ZB, Setiyo M, Praja CB, Setiawan A, Yuliastuti F, Muliawanti L, Dewi VS, editors. Proceedings of the 5th Borobudur international symposium on humanities and social science (BISHSS 2023). Paris: Atlantis Press SARL; 2024. p. 4-13. doi: 10.2991/978-2-38476-273-6_2.

5. Hikmah DN, Syarifuddin A, Santoso SB, Wijayatri R, Hidayat IW. The role of genetic mutation on schizophrenia: a basic review prior to pharmacogenomics. In: Pambuko ZB, Setiyo M, Praja CB, Setiawan A, Yuliastuti F, Muliawanti L, Dewi VS, editors. Proceedings of the 4th Borobudur international symposium on humanities and social science 2022 (BIS-HSS 2022). Paris: Atlantis Press SARL; 2024. p. 835-47. doi: 10.2991/978-2-38476-118-0_96.

6. Zahrah SS, Wijayatri R, Hidayat IW, Syarifuddin A, Santoso SB. From the genetic mutation to the specific pathologies. In: Pambuko ZB, Setiyo M, Praja CB, Setiawan A, Yuliastuti F, Muliawanti L, Dewi VS, editors. Proceedings of the 4th Borobudur international symposium on humanities and social science 2022 (BIS-HSS 2022). Paris: Atlantis Press SARL; 2024. p. 439-47. doi: 10.2991/978-2-38476-118-0_49.

7. Jays J, Saravanan J. A molecular modelling approach for structure based virtual screening and identification of novel isoxazoles as potential antimicrobial agents against S. aureus. Int J Pharm Pharm Sci. 2024 Apr 1;16(4):36-41. doi: 10.22159/ijpps.2024v16i4.49731.

8. Abiyana SR, Santoso SB, Pribadi P, Hapsari WS, Syarifuddin A. From the drug bank application to the novel drugs: a pharmacogenomic summary. E3S Web Conf. 2024;500:13. doi: 10.1051/e3sconf/202450004002.

9. Gallo K, Goede A, Preissner R, Gohlke BO. SuperPred3.0: drug classification and target prediction a machine learning approach. Nucleic Acids Res. 2022 Jul 5;50(W1):W726-31. doi: 10.1093/nar/gkac297, PMID 35524552.

10. Bouzier A, Rojas J, Ibinga SK, Lamarti A, Martin P, Morillo M. The impact of saponins on health review. Biointerface Res Appl Chem. 2022 Sep 26;13(4):362. doi: 10.33263/BRIAC134.362.

11. Suebsakwong P, Chulrik W, Chunglok W, Li JX, Yao ZJ, Suksamrarn A. New triterpenoid saponin glycosides from the fruit fibers of Trichosanthes cucumerina L. RSC Adv. 2020;10(18):10461-70. doi: 10.1039/d0ra01176b, PMID 35492927.

12. Bildziukevich U, Wimmerova M, Wimmer Z. Saponins of selected triterpenoids as potential therapeutic agents: a review. Pharmaceuticals (Basel). 2023 Mar 2;16(3):386. doi: 10.3390/ph16030386, PMID 36986485.

13. Liu J, Yin X, Kou C, Thimmappa R, Hua X, Xue Z. Classification biosynthesis and biological functions of triterpene esters in plants. Plant Commun. 2024 Feb 13;5(4):100845. doi: 10.1016/j.xplc.2024.100845, PMID 38356259.

14. Cao XW, Wang FJ, Liew OW, Lu YZ, Zhao J. Analysis of triterpenoid saponins reveals insights into structural features associated with potent protein drug enhancement effects. Mol Pharm. 2020 Feb 3;17(2):683-94. doi: 10.1021/acs.molpharmaceut.9b01158, PMID 31913047.

15. Savarino P, Contino C, Colson E, Cabrera Barjas G, De Winter J, Gerbaux P. Impact of the hydrolysis and methanolysis of bidesmosidic chenopodium quinoa saponins on their hemolytic activity. Molecules. 2022 May 17;27(10):3211. doi: 10.3390/molecules27103211, PMID 35630692.

16. He Q, Wang Y, Zhao F, Wei S, Li X, Zeng G. Ape1: a critical focus in neurodegenerative conditions. Biomed Pharmacother. 2024 Oct;179(1):117332. doi: 10.1016/j.biopha.2024.117332, PMID 39191031.

17. Cho HR, Kumari N, Thakur N, Vu HT, Kim H, Choi SH. Decreased APE-1 by nitroxoline enhances therapeutic effect in a temozolomide resistant glioblastoma: correlation with diffusion weighted imaging. Sci Rep. 2019 Nov 12;9(1):16613. doi: 10.1038/s41598-019-53147-9, PMID 31719653.

18. Huang T, Wang YJ, Huang MT, Guo Y, Yang LC, Liu XJ. LINC00470 accelerates the proliferation and metastasis of melanoma through promoting APEX1 expression. Cell Death Dis. 2021 Apr 19;12(5):410. doi: 10.1038/s41419-021-03612-z, PMID 33875645.

19. Caston RA, Gampala S, Armstrong L, Messmann RA, Fishel ML, Kelley MR. The multifunctional APE1 DNA repair redox signaling protein as a drug target in human disease. Drug Discov Today. 2021 Jan;26(1):218-28. doi: 10.1016/j.drudis.2020.10.015, PMID 33148489.

20. Kim JM, Yeo MK, Lim JS, Song IS, Chun K, Kim KH. APEX1 expression as a potential diagnostic biomarker of clear cell renal cell carcinoma and hepatobiliary carcinomas. J Clin Med. 2019 Aug 1;8(8):1151. doi: 10.3390/jcm8081151, PMID 31375000.

21. Cao L, Cheng H, Jiang Q, Li H, Wu Z. APEX1 is a novel diagnostic and prognostic biomarker for hepatocellular carcinoma. Aging. 2020 Mar 13;12(5):4573-91. doi: 10.18632/aging.102913, PMID 32167932.

22. Mijit M, Liu S, Sishtla K, Hartman GD, Wan J, Corson TW. Identification of novel pathways regulated by APE1/Ref-1 in human retinal endothelial cells. Int J Mol Sci. 2023 Jan 6;24(2):1101. doi: 10.3390/ijms24021101, PMID 36674619.

23. Alibashe Ahmed M, Brioudes E, Reith W, Bosco D, Berney T. Toll like receptor 4 inhibition prevents autoimmune diabetes in NOD mice. Sci Rep. 2019 Dec 18;9(1):19350. doi: 10.1038/s41598-019-55521-z, PMID 31852918.

24. Utami D, Chalid MT, Masadah R, Sjahril R, Bahagia Febriani AD. Association of toll like receptor 2 (TLR2) expression in placenta and intrauterine exposure to hepatitis B virus. Interdiscip Perspect Infect Dis. 2022 Jul 13;2022:4838376. doi: 10.1155/2022/4838376, PMID 35875205.

25. Rogava M, Braun AD, Van Der Sluis TC, Shridhar N, Tuting T, Gaffal E. Tumor cell intrinsic toll like receptor 4 signaling promotes melanoma progression and metastatic dissemination. Int J Cancer. 2022 Jan 1;150(1):142-51. doi: 10.1002/ijc.33804, PMID 34528710.

26. Ou T, Lilly M, Jiang W. The pathologic role of toll like receptor 4 in prostate cancer. Front Immunol. 2018 Jun 6;9:1188. doi: 10.3389/fimmu.2018.01188, PMID 29928275.

27. Sun P, Cui M, Jing J, Kong F, Wang S, Tang L. Deciphering the molecular and cellular atlas of immune cells in septic patients with different bacterial infections. J Transl Med. 2023 Nov 2;21(1):777. doi: 10.1186/s12967-023-04631-4, PMID 37919720.

28. Kuzmich NN, Sivak KV, Chubarev VN, Porozov YB, Savateeva Lyubimova TN, Peri F. TLR4 signaling pathway modulators as potential therapeutics in inflammation and sepsis. Vaccines. 2017 Oct 4;5(4):34. doi: 10.3390/vaccines5040034, PMID 28976923.

29. Secomandi E, Salwa A, Vidoni C, Ferraresi A, Follo C, Isidoro C. High expression of the lysosomal protease cathepsin D confers better prognosis in neuroblastoma patients by contrasting EGF-induced neuroblastoma cell growth. Int J Mol Sci. 2022 Apr 26;23(9):4782. doi: 10.3390/ijms23094782, PMID 35563171.

30. Li H, Wen X, Ren Y, Fan Z, Zhang J, He G. Targeting PI3K family with small molecule inhibitors in cancer therapy: current clinical status and future directions. Mol Cancer. 2024 Aug 10;23(1):164. doi: 10.1186/s12943-024-02072-1, PMID 39127670.

31. Yadati T, Houben T, Bitorina A, Shiri Sverdlov R. The ins and outs of cathepsins: physiological function and role in disease management. Cells. 2020 Jul;9(7):1679. doi: 10.3390/cells9071679, PMID 32668602.

32. Ozkayar N, Akyel F, Barça AN, Piskinpasa SV, Turhan T, Ates I. The relation between serum cathepsin D level and carotid intima media thickness in nondiabetic hypertensive patients. Turk J Med Sci. 2016;46(1):13-7. doi: 10.3906/sag-1410-55, PMID 27511327.

33. Ampofo E, Spater T, Nalbach L, Menger MD, Laschke MW. The marine derived triterpenoid frondoside a inhibits thrombus formation. Mar Drugs. 2020 Feb;18(2):111. doi: 10.3390/md18020111, PMID 32074969.

34. Lacaille Dubois MA, Wagner H. New perspectives for natural triterpene glycosides as potential adjuvants. Phytomedicine. 2017:S0944-7113(17)30158-7. doi: 10.1016/j.phymed.2017.10.019, PMID 29239784.

35. Li J, He J, He H, Wang X, Zhang S, He Y. Sweet triterpenoid glycoside from cyclocarya paliurus ameliorates obesity induced insulin resistance through inhibiting the TLR4/NF-κB/NLRP3 inflammatory pathway. Curr Res Food Sci. 2024 Jan 14;8:100677. doi: 10.1016/j.crfs.2024.100677, PMID 38303998.

36. Dickinson SE, Wondrak GT. TLR4 in skin cancer: from molecular mechanisms to clinical interventions. Mol Carcinog. 2019 Jul;58(7):1086-93. doi: 10.1002/mc.23016, PMID 31020719.

37. Lu H, Betancur A, Chen M, Ter Meulen JH. Toll like receptor 4 expression on lymphoma cells is critical for therapeutic activity of intratumoral therapy with synthetic TLR4 agonist glucopyranosyl lipid A. Front Oncol. 2020 Aug 19;10:1438. doi: 10.3389/fonc.2020.01438, PMID 32974162.

38. Mathai N, Chen Y, Kirchmair J. Validation strategies for target prediction methods. Brief Bioinform. 2020;21(3):791-802. doi: 10.1093/bib/bbz026, PMID 31220208.

39. Zeng Z, Hu J, Xiao G, Liu Y, Jia D, Wu G. Integrating network toxicology and molecular docking to explore the toxicity of the environmental pollutant butyl hydroxyanisole: an example of induction of chronic urticaria. Heliyon. 2024 Jul 30;10(15):e35409. doi: 10.1016/j.heliyon.2024.e35409, PMID 39170477.

40. Moumbock AF, Li J, Mishra P, Gao M, Gunther S. Current computational methods for predicting protein interactions of natural products. Comput Struct Biotechnol J. 2019 Oct 28;17:1367-76. doi: 10.1016/j.csbj.2019.08.008, PMID 31762960.

41. Hashemi ZS, Zarei M, Fath MK, Ganji M, Farahani MS, Afsharnouri F. In silico approaches for the design and optimization of interfering peptides against protein protein interactions. Front Mol Biosci. 2021 Apr 28;8:669431. doi: 10.3389/fmolb.2021.669431, PMID 33996914.

42. Javaid S, Zafar H, Atia Tul Wahab, Gervais V, Ramos P, Muller I. Identification of new lead molecules against anticancer drug target TFIIH subunit P8 using biophysical and molecular docking studies. Bioorg Chem. 2021 Sep;114:105021. doi: 10.1016/j.bioorg.2021.105021.

43. Li C, Geng C, Wang J, Shi L, Ma J, Liang Z. Investigating the inflammatory mechanism of notoginsenoside R1 in diabetic nephropathy via Itgb8 based on network pharmacology and experimental validation. Mol Med. 2024 Dec 26;30(1):277. doi: 10.1186/s10020-024-01055-8, PMID 39725889.

44. Wei H, McCammon JA. Structure and dynamics in drug discovery. Npj Drug Discov. 2024 Nov 7;1(1):1-8. doi: 10.1038/s44386-024-00001-2.

45. Mo N, Zhou P, Liu F, Su H, Han L, Lu C. Integrating network pharmacology molecular docking and experimental validation to reveal the mechanism of radix Rehmanniae in psoriasis. Med (Baltim). 2024 Oct 25;103(43):e40211. doi: 10.1097/MD.0000000000040211, PMID 39470475.

46. Wang YC, Li TZ, Chen JJ. Compound protein interaction prediction based on heterogeneous network reveals potential antihepatoma agents. iScience. 2024 Jun 29;27(8):110418. doi: 10.1016/j.isci.2024.110418, PMID 39108729.

47. Yin T, Wang H, Zou Y. Application of network pharmacology bioinformatics computational molecular docking and experimental validation to study the anticancer effects of oleanolic acid in oral squamous carcinoma cells. Acta Pharm. 2025 Mar 31;75(1):41-68. doi: 10.2478/acph-2025-0005, PMID 40208786.

48. Alali H, Bloch I, Rapaport I, Rodrigues L, Sher I, Ansbacher T. Application of in silico filtering and isothermal titration calorimetry for the discovery of small molecule inhibitors of MDM2. Pharmaceuticals (Basel). 2022 Jun;15(6):752. doi: 10.3390/ph15060752, PMID 35745671.

49. Sun Y, Cai J, Ding S, Bao S. Network pharmacology was used to predict the active components and prospective targets of paeoniae radix alba for treatment in endometriosis. Reprod Sci. 2023 Apr;30(4):1103-17. doi: 10.1007/s43032-022-01102-x, PMID 36258089.

50. Iqbal S, Karim MR, Mohammad S, Ahn JC, Kariyarath Valappil A, Mathiyalagan R. In silico and in vitro study of isoquercitrin against kidney cancer and inflammation by triggering potential gene targets. Curr Issues Mol Biol. 2024 Apr;46(4):3328-41. doi: 10.3390/cimb46040208, PMID 38666938.

Published

28-08-2025

How to Cite

SANTOSO, S. B., SYARIFUDDIN, A., WARDANI, A. K., WIDIASTUTI, V. P., & NINDA, M. F. (2025). EXPLORING PROTEIN TARGETS OF TRITERPENE SAPONINS (C₅₄H₈₆O₂₄): A BIOINFORMATICS APPROACH TO NOVEL THERAPEUTIC DEVELOPMENT. International Journal of Applied Pharmaceutics, 17(3), 30–34. https://doi.org/10.22159/ijap.2025.v17s3.04

Issue

Section

Original Article(s)

Similar Articles

<< < 1 2 3 4 5 > >> 

You may also start an advanced similarity search for this article.