Author(s):
Rangga Adhi Prastika, Suhailah Hayaza, Azka Muhammad Nurrahman, Raden Joko Kuncoroningrat Susilo
Email(s):
suhailah@ftmm.unair.ac.id
DOI:
10.52711/0974-360X.2025.00606 
Address:
Rangga Adhi Prastika, Suhailah Hayaza, Azka Muhammad Nurrahman, Raden Joko Kuncoroningrat Susilo
Nanotechnology Engineering, Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya 60115, Indonesia.
*Corresponding Author
Published In:
Volume - 18,
Issue - 9,
Year - 2025
ABSTRACT:
Colon cancer is a deadly cancer that affects the colorectal region. This cancer is the second highest leading cause of cancer related death just behind lung cancer. According to the World Health Organization (WHO) there are around 1,9 million new colon cancer cases and more than 930 thousands deaths caused by colon cancer during 2020. Conventional methods to treat colon cancer, such as operation, chemotherapy and radiotherapy have drawbacks. One potential alternative to treat colon cancer is to target the Human Uridine Phosphorylase 1 (hUPP1) enzyme which plays a role in the growth of colon cancer. The use of nutraceutical products from okra pods extract conjugated with various FeNP is predicted to inhibit the growth of colon cancer. This research aims to analyze the nature of active compounds from okra fruit as well as the conjugation effect of various FeNP. Methods performed in silico with drug-likeness approach, molecular docking, and molecular dynamics simulation. In drug-likeness, addition FeNP have affected pharmacokinetics properties of the compounds where the addition of Fe, FeO, and Fe3O4 demonstrated better antineoplastic and anti-inflammatory (intestinal) activity compared to Fe2O3. Molecular docking shows that all compounds have qualified the lipinski rules with binding energy and RMSD that indicated strong and stable interactions against hUPP1 enzyme. Molecular dynamic simulation and MM-GBSA shows great stability and a consistent interaction between okra pods extract compounds toward hUPP1 enzyme during simulation. This result shows that compounds from okra pods extract can potentially be used to treat colon cancer.
Cite this article:
Rangga Adhi Prastika, Suhailah Hayaza, Azka Muhammad Nurrahman, Raden Joko Kuncoroningrat Susilo. Research Journal of Pharmacy and Technology. 2025;18(9):4215-4. doi: 10.52711/0974-360X.2025.00606
Cite(Electronic):
Rangga Adhi Prastika, Suhailah Hayaza, Azka Muhammad Nurrahman, Raden Joko Kuncoroningrat Susilo. Research Journal of Pharmacy and Technology. 2025;18(9):4215-4. doi: 10.52711/0974-360X.2025.00606 Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2025-18-9-26
REFERENCES:
1. Prihantono, Rusli R, Christeven R, Faruk M. Cancer Incidence and Mortality in a Tertiary Hospital in Indonesia: An 18-Year Data Review. Ethiopian Journal of Health Sciences. 2023; 33(3): 515–522.
2. Fillon M. Study identifies signs and symptoms of colorectal cancer risk at younger ages. CA: A Cancer Journal for Clinicians. 2023; 73(5): 448–450.
3. Krasteva N, Georgieva M. Promising Therapeutic Strategies for Colorectal Cancer Treatment Based on Nanomaterials. Pharmaceutics. 2022; 14(6): 1213.
4. Kumar A, Gautam V, Sandhu A, Rawat K, Sharma A, Saha L. Current and emerging therapeutic approaches for colorectal cancer: A comprehensive review. World Journal of Gastrointestinal Surgery. 2023; 15(4): 495–519.
5. Janani B, Vijayakumar M, Priya K, Kim JH, Prabakaran DS, Shahid M, Al-Ghamdi S, Alsaidan M, Bahakim NO, Abdelzaher MH, Ramesh T. EGFR-Based Targeted Therapy for Colorectal Cancer-Promises and Challenges. Vaccines. 2022; 10(4): 499.
6. Bhasin N, Alleyne D, Gray OA, Kupfer SS. Vitamin D Regulation of the Uridine Phosphorylase 1 Gene and Uridine-Induced DNA Damage in Colon in African Americans and European Americans. Gastroenterology. 2018; 155(4): 1192-1204.
7. Weng W, Liu N, Toiyama Y, Kusunoki M, Nagasaka T, Fujiwara T, Wei Q, Qin H, Lin H, Ma Y, Goel A. Novel evidence for a PIWI-interacting RNA (piRNA) as an oncogenic mediator of disease progression, and a potential prognostic biomarker in colorectal cancer. Molecular Cancer 2018; 17: 16.
8. Proboningrat A, Ansori ANM, Fadholly A, Putri N, Kusala MKJ, Achmad AB. First Report on the Cytotoxicity of Pinus merkusii Bark Extract in WiDr, A Human Colon Carcinoma Cell Line. Research Journal of Pharmacy and Technology. 2021; 14(3): 1685–1688.
9. Alifiansyah MRT, Herdiansyah MA, Pratiwi RC, Pramesti RP, Hafsyah NW, Rania AP, Putra JERP, Cahyono PA, Litazkiyyah, Muhammad SK, Murtadia AAA, Kharisma VD, Ansori ANM, Jakhmola V, Ashok PK, Kalra JM, Purnobasuki H, Pratiwi IA. QSAR of acyl alizarin red biocompound derivatives of Rubia tinctorum roots and its ADMET properties as anti-breast cancer candidates against MMP-9 protein receptor: In Silico study. Food Systems. 2024; 7(2): 312–320.
10. Fadholly A, Ansori ANM, Utomo B. Anticancer Effect of Naringin on Human Colon Cancer (WiDr Cells): In Vitro Study. Research Journal of Pharmacy and Technology. 2022; 15(2): 885.
11. Rachida ZA, Ridha OM, Eddine LS, Souhaila M. Screening of phenolic compounds from Abelmoschus esculentus L extract fruits and in vitro evaluation of antioxidant and antibacterial activities. Research Journal of Pharmacy and Technology. 2017; 10(12): 4371–4376.
12. Husen SA, Wahyuningsih SPA, Ansori ANM, Hayaza S, Susilo RJK, Winarni D, Punnapayak H, Darmanto W. Antioxidant Potency of Okra (Abelmoschus esculentus Moench) Pods Extract on SOD Level and Tissue Glucose Tolerance in Diabetic Mice. Research Journal of Pharmacy and Technology. 2019; 12(12): 5683–5688.
13. Abideen Adeyinka A, Hidayat O, Adekanmi U, Muraina T, Adekanmi O, Adekanmi S. Characterization and Phytochemical Property of Okra Fruits. International Journal of Academic Engineering Research. 2020; 4: 34–39.
14. Deng Y, Li S, Wang M, Chen X, Tian L, Wang L, Yang W, Chen L, He F, Yin W. Flavonoid-rich extracts from okra flowers exert antitumor activity in colorectal cancer through induction of mitochondrial dysfunction-associated apoptosis, senescence and autophagy. Food and Function. 2020; 11(12): 10448–10466.
15. Jain S, Saxena N, Sharma MK, Chatterjee S. Metal nanoparticles and medicinal plants: Present status and future prospects in cancer therapy. Materials Today: Proceedings. 2020; 31: 662–673.
16. Wu L, Wang C, Li Y. Iron Oxide Nanoparticle Targeting Mechanism and its Application in Tumor Magnetic Resonance Imaging and Therapy. Nanomedicine. 2022; 17(21)1567-1583.
17. Chen J, Wang Y, Han L, Wang R, Gong C, Yang G, Li Z, Gao S, Yuan Y. A ferroptosis-inducing biomimetic nanocomposite for the treatment of drug-resistant prostate cancer. Materials Today Bio. 2022; 17: 100484.
18. Nakamura H, Takada K. Reactive oxygen species in cancer: Current findings and future directions. Cancer Science. 2021; 112(10): 3945–3952.
19. Katsipis G, Tsalouxidou V, Halevas E, Geromichalou E, Geromichalos G, Pantazaki AA. In vitro and in silico evaluation of the inhibitory effect of a curcumin-based oxovanadium (IV) complex on alkaline phosphatase activity and bacterial biofilm formation. Applied Microbiology and Biotechnology. 2021; 105(1): 147–168.
20. Bharskar G, Mankar S, Siddheshwar S. Analytical Methods for Estimation of Curcumin in Bulk, Pharmaceutical Formulation and in Biological Samples. Asian Journal Pharmaceutical Analysis. 2022; 12(2): 142–148.
21. Romdhane MH, Chahdoura H, Barros L, Dias MI, Corrêa RCG, Morales P, Ciudad-Mulero M, Flamini G, Majdoub H, Ferreira ICFR. Chemical Composition, Nutritional Value, and Biological Evaluation of Tunisian Okra Pods (Abelmoschus esculentus L. Moench). Molecules. 2020; 25(20): 4739.
22. Yang J, Chen X, Rao S, Li Y, Zang Y, Zhu B. Identification and Quantification of Flavonoids in Okra (Abelmoschus esculentus L. Moench) and Antiproliferative Activity In Vitro of Four Main Components Identified. Metabolites. 2022; 12(6): 483.
23. Rajendran P, Rathinasabapathy R, Chandra Kishore S, Bellucci S. Computational-Simulation-Based Behavioral Analysis of Chemical Compounds. Journal of Compos Science. 2023; 7(5): 196.
24. Alsedfy MY, Ebnalwaled AA, Moustafa M, Said AH. Investigating the binding affinity, molecular dynamics, and ADMET properties of curcumin-IONPs as a mucoadhesive bioavailable oral treatment for iron deficiency anemia. Scientific Reports. 2024; 14(1): 22027.
25. Filimonov DA, Lagunin AA, Gloriozova TA, Rudik AV, Druzhilovskii DS, Pogodin PV, Poroikov VV. Prediction of the Biological Activity Spectra of Organic Compounds Using the Pass Online Web Resource. Chemistry of Heterocyclic Compounds. 2014; 50(3): 444–457.
26. Khan T, Lawrence AJ, Azad I, Raza S, Joshi S, Khan AR. Computational Drug Designing and Prediction Of Important Parameters Using in silico Methods- A Review. Current Computer-Aided Drug Design. 2019; 15(5): 384–397.
27. Lagunin A, Filimonov D, Poroikov V. Multi-Targeted Natural Products Evaluation Based on Biological Activity Prediction with PASS. Current Pharmaceutical Design. 2010; 16(15): 1703–1717.
28. Radha M, Ratnasabapathysarma V, Suganya J. In Silico approach to inhibit Synthetic HIV-TAT activity using Phytoconstituents of Moringa oleifera leaves extract. Research Journal of Pharmacy and Technology. 2020; 13(8): 3610–3614.
29. Dighe AS, Tajamulhaq AE. An Overview of Molecular Docking. Asian Journal of Pharmaceutical Research. 2024; 14(3): 336–0.
30. Chagas CM, Moss S, Alisaraie L. Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five. International Journal of Pharmaceutics. 2018; 549(1–2): 133–49.
31. S SM, Kumar RS, V S, Menon SV, Mohan S, Suja ST, Sathianarayanan, Manakadan AA. A Computational approach for identification of Phytochemicals for targeting and optimizing the inhibitors of Heat shock proteins. Research Journal of Pharmacy and Technology. 2015; 8(9): 1199–1204.
32. Yang S, Kar S, Leszczynski J. Chapter 25 - Tools and software for computer-aided drug design and discovery. Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development. 2023; 637–661.
33. Falivene L, Cao Z, Petta A, Serra L, Poater A, Oliva R, Scarano V, Cavallo L. Towards the online computer-aided design of catalytic pockets. Nature Chemistry. 2019; 11(10): 872–879.
34. Pu L, Govindaraj RG, Lemoine JM, Wu HC, Brylinski M. DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network. PLOS Computational Biology. 2019; 15(2): e1006718.
35. Duppala SK, Pawar SC, Vyas A, Vure S. Protein-Protein Docking and Structural Prediction of KMT2C Variant from Cervical Cancer Whole Exome Sequencing Data. Research Journal of Pharmacy and Technology. 2024; 17(5): 2301–8.
36. S BR, K L, R M, K BR, R K, B V. Comparing the binding energies and inhibition constant of Sunitinib malate-metal complex on Tyrosine kinase receptor by Computational Molecular Docking. Research Journal of Pharmacy and Technology. 2024; 17(9): 4501–6.
37. Fischer A, Smieško M, Sellner M, Lill MA. Decision Making in Structure-Based Drug Discovery: Visual Inspection of Docking Results. Journal of Medicinal Chemistry. 2021; 64(5): 2489–2500.
38. Çapan I, Gümuş M, Gökce H, Çetin H, Sert Y, Koca İ. Synthesis, dielectric properties, molecular docking and ADME studies of pyrrole-3-ones. Journal of Biomolecular Structure and Dynamics. 2022; 40(19): 8655–8671.
39. Abdelsattar AS, Dawoud A, Helal MA. Interaction of nanoparticles with biological macromolecules: a review of molecular docking studies. Nanotoxicology. 2021; 15(1): 66-95.
40. Mohammadjani N, Karimi S, Moetasam Zorab M, Ashengroph M, Alavi M. Comparative molecular docking and toxicity between carbon-capped metal oxide nanoparticles and standard drugs in cancer and bacterial infections. BioImpacts. 2024; 14(2): 27778.
41. Herrera-Rodríguez AM, Miletic V, Aponte-Santamaría C, Gräter F. Molecular Dynamics Simulations of Molecules in Uniform Flow. Biophysical Journal. 2019; 116(9): 1579–1585.
42. Nagalakshmi V, Lavanya J, Bhavya B, Riya V, Venugopal B, Ramesh AS. In-silico Profiling of Deleterious Non Synonymous SNPs of Homogentisate 1,2 Dioxygenase (HGD) Gene for Early Diagnosis of “Alkaptonuria”. Research Journal of Pharmacy and Technology. 2022; 15(9): 3898–3904.
43. Justino GC, Nascimento CP, Justino MC. Molecular dynamics simulations and analysis for bioinformatics undergraduate students. Biochemistry and Molecular Biology Education. 2021; 49(4): 570–582.
44. Arnittali M, Rissanou AN, Harmandaris V. Structure Of Biomolecules Through Molecular Dynamics Simulations. Procedia Computer Science. 2019; 156: 69–78.
45. Rollando R, Warsito W, Masruri M, Widodo N. Potential matrix metalloproteinase-9 inhibitor of aurone compound isolated from Sterculia quadrifida leaves: In-vitro and in-silico studies. Research Journal of Pharmacy and Technology. 2022; 15(11): 5250–4.
46. Dong Y wei, Liao M ling, Meng X liang, Somero GN. Structural flexibility and protein adaptation to temperature: Molecular dynamics analysis of malate dehydrogenases of marine molluscs. Proceedings of the National Academy of Sciences of the United States of America. 2018; 115(6): 1274–1279.
47. Martínez L. Automatic Identification of Mobile and Rigid Substructures in Molecular Dynamics Simulations and Fractional Structural Fluctuation Analysis. PLOS One. 2015;10(3):e0119264.
48. Mortier J, Rakers C, Bermudez M, Murgueitio MS, Riniker S, Wolber G. The impact of molecular dynamics on drug design: applications for the characterization of ligand–macromolecule complexes. Drug Discovery Today. 2015; 20(6): 686–702.
49. Sneha P, George Priya Doss C. Chapter Seven-Molecular Dynamics: New Frontier in Personalized Medicine. Advances in Protein Chemistry and Structural Biology. 2016; 102: 181–224.
50. Patle MR, Ganatra SH. In-Silico Inhibition Studies of Phenothiazine Based Compounds on Quinolinic Acid Phosphoribosyltransferase (1QPQ) Enzyme as A Potent Anti-Tuberculosis Agent. Asian Journal of Research in Chemistry. 2011; 4(6): 990–996.
51. H GS, R PM, K BG. Inhibition Studies of Pyridine Based Compounds on Quinolinic Acid Phosphoribosyltransferase (1QPQ) Enzyme as A Potent Anti-Tuberculosis Agent. Asian Journal of Research in Chemistry. 2012; 5(9): 1159–1165.
52. Tripathi MK, Ahmad S, Tyagi R, Dahiya V, Yadav MK. Chapter 5 - Fundamentals of molecular modeling in drug design. Computer Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based Approaches. 2022; 125–155.
53. Cappel D, Wahlström R, Brenk R, Sotriffer CA. Probing the Dynamic Nature of Water Molecules and Their Influences on Ligand Binding in a Model Binding Site. Journal of Chemical Information and Modeling. 2011; 51(10): 2581–2594.
54. Chen W, He H, Wang J, Wang J, Chang C en A. Uncovering water effects in protein–ligand recognition: importance in the second hydration shell and binding kinetics. Physical Chemistry Chemical Physics. 2023; 25(3): 2098–2109.
55. Ausaf Ali S, Imtaiyaz Hassan Md, Islam A, Ahmad F. A Review of Methods Available to Estimate Solvent-Accessible Surface Areas of Soluble Proteins in the Folded and Unfolded States. Current Protein and Peptide Science. 2014; 15(5): 456–476.
56. Kleinjung J, Fraternali F. Design and application of implicit solvent models in biomolecular simulations.Current Opinion in Structural Biology. 2014; 25: 126–134.
57. Adsule PV, Purandare DV, Chabukswar AR, Nanaware R, Lokhande PD. Designing of Coumarin molecules as EGFR inhibitors and their ADMET, MD Simulation Studies for Evaluating potential as Anticancer molecules. Research Journal of Pharmacy and Technology. 2024; 17(3): 1008–4.