Author(s):
Fadilah Fadilah, Linda Erlina
Email(s):
fadilah81@gmail.com
DOI:
10.52711/0974-360X.2025.00558
Address:
Fadilah Fadilah1,2, Linda Erlina1,2
1Department of Medical Chemistry, Faculty of Medicine, Universitas Indonesia,
Jakarta, Indonesia. Jl. Salemba Raya No.6, Jakarta Pusat, Indonesia 10430.
2Bioinformatics Core Facilities, Indonesian Medical Education and Research Institute (IMERI),
Jakarta, Indonesia. Jl. Salemba Raya No.6, Jakarta Pusat, Indonesia 10430.
*Corresponding Author
Published In:
Volume - 18,
Issue - 8,
Year - 2025
ABSTRACT:
Background: Bcl-2 family proteins regulate apoptosis, and their overexpression is linked to cancer progression and therapy resistance. Targeting Bcl-2 with novel inhibitors is a promising approach for anticancer drug development. Methods: Pharmacophore modeling was performed using a training set of 5 diverse Bcl-2 inhibitors with IC_50 values ranging from 0.00012 to 3.37µM. Ten pharmacophore models were generated and validated using receiver operating characteristic (ROC) curves, enrichment factor (EF), and Güner-Henry (GH) scoring with a test set containing 24 active compounds and 1309 decoys. Model 8 demonstrated the best performance (AUC = 0.83, EF_1% = 3.66, GH score = 0.58) and was used for virtual screening of 220 eugenol derivatives. Docking studies were conducted using AutoDock against Bcl-2 crystal structure (PDB ID: 4LXD), and in silico ADMET analysis assessed pharmacokinetic and toxicity profiles. Results: Model 8 effectively distinguished active Bcl-2 inhibitors with good sensitivity and selectivity. Virtual screening identified 24 eugenol derivatives with high pharmacophore fit scores (>45), among which compounds 57, 57', 71 and 91 exhibited favorable docking binding energies ranging from -5.11 to -7.35kcal/mol compare with ABT-263 with value -9.82kcal/mol, overlapping well with the binding site of known inhibitor navitoclax. In silico ADMET profiling predicted good solubility, partition coefficients, and low toxicity risks, supporting their drug-likeness. Conclusion: The integrated pharmacophore and docking approach successfully identified promising eugenol derivative candidates as potential Bcl-2 inhibitors. These compounds demonstrate favorable binding affinity and pharmacokinetic properties, meriting further experimental validation and development as anticancer agents. Future work should include molecular dynamics simulations and in vitro bioactivity assays to confirm and optimize these leads.
Cite this article:
Fadilah Fadilah, Linda Erlina. Pharmacophore Modeling, Virtual Screening and in Silico ADMET Analysis of Phenylpropanoid and Eugenol Derivatives as B-cell CLL/Lymphoma 2 (BCL-2) Inhibitors. Research Journal Pharmacy and Technology. 2025;18(8):3887-4. doi: 10.52711/0974-360X.2025.00558
Cite(Electronic):
Fadilah Fadilah, Linda Erlina. Pharmacophore Modeling, Virtual Screening and in Silico ADMET Analysis of Phenylpropanoid and Eugenol Derivatives as B-cell CLL/Lymphoma 2 (BCL-2) Inhibitors. Research Journal Pharmacy and Technology. 2025;18(8):3887-4. doi: 10.52711/0974-360X.2025.00558 Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2025-18-8-61
REFERENCES:
1. Qian, S., Wei, Z., Yang, W., Huang, J., Yang, Y., and Wang, J. The role of BCL-2 family proteins in regulating apoptosis and cancer therapy. Frontiers in Oncology. 2022; 12. https://doi.org/10.3389/fonc.2022.985363
2. Gong, Q., Wang, H., Zhou, M., Zhou, L., Wang, R., and Li, Y. B-cell lymphoma-2 family proteins in the crosshairs: Small molecule inhibitors and activators for cancer therapy. 2023. https://doi.org/10.1002/med.21999
3. Tayeb, F. J. Dysregulation of BCL-2 family proteins in blood neoplasm: therapeutic relevance of antineoplastic agent venetoclax. Exploration of Medicine. 2024. https://doi.org/10.37349/emed.2024.00223
4. Wei, J. X., and Konopleva, M. Bcl-2 inhibition in the treatment of hematologic malignancies. 2023. https://doi.org/10.3389/frhem.2023.1307661
5. Fowler-Shorten, D. J., Hellmich, C., Markham, M., Bowles, K., and Rushworth, S. A. BCL-2 inhibition in haematological malignancies: Clinical application and complications. Blood Reviews. 2024 101195. https://doi.org/10.1016/j.blre.2024.101195
6. Singh, N., and Kumar, M. Essential oils and their phenylpropanoids as anticancer agents: Mechanisms and molecular targets. Phytochemistry Reviews. 2023; 22: 553–575.
7. Amaq Fadholly, Arif N. M. Ansori, Teguh H. Sucipto. An Overview of Naringin: Potential Anticancer compound of Citrus Fruits. Research J. Pharm. and Tech. 2020; 13(11): 5613-5619. doi: 10.5958/0974-360X.2020.00979.8
8. Reis, R. C. F. M., Silva, A. V. P., Torres, A. da V., Iemini, R. de C. A., Lapa, I. R., Franco, L. L., Braga, S. F. P., Carvalho, D. T., Dias, D. F., and Souza, T. B. de. From clove oil to bioactive agents: synthetic routes, antimicrobial and antiparasitic activities of eugenol derivatives. Future Medicinal Chemistry. 2024: 1–20. https://doi.org/10.1080/17568919.2024.2419376
9. Liesl Maria Fernandese Mendonca, Arun Bhimrao Joshi, Anant Bhandarkar, Himanshu Joshi. Antioxidant, Antiproliferative, Pro-apoptotic and cell cycle arrest properties of crude extract and biofractions of Hybanthus enneaspermus Linn. to combat breast cancer. Research Journal of Pharmacy and Technology. 2023; 16(9): 4127-4. doi: 10.52711/0974-360X.2023.00675
10. Panda, P., Appalashetti, M., and Judeh, Z. M. A. Phenylpropanoid sucrose esters: plant-derived natural products as potential leads for new therapeutics. Current Medicinal Chemistry, 2011; 18(21): 3234–3251. https://doi.org/10.2174/092986711796391589
11. Patel, D., Mehta, S., and Joshi, A. Molecular insights into eugenol as a therapeutic agent against cancer: Pharmacological perspectives. Phytomedicine. 2022; 102: 154156
12. Yufri Aldi, Dita Permatasari, Sera Afdalanita, Aditya Alqamal Alianta. Safety Evaluation of Moringa Leaves (Moringa oleifera Lam.) on Kidney Organs in Male White Rats. Research Journal of Pharmacy and Technology. 2024; 17(11): 5531-9. doi: 10.52711/0974-360X.2024.00845
13. Fadilah, F., Yanuar, A., Arsianti, A., and Andrajati, R. Phenylpropanoids, eugenol scaffold, and its derivatives as anticancer. Asian Journal of Pharmaceutical and Clinical Research. 2017; 10(3); 41–46. https://doi.org/10.22159/AJPCR.2017.V10I3.16071
14. Anil Kumar Sahdev, Priya Gupta, Kanika Manral, Preeti Rana, Anita Singh. An Overview on Pharmacophore: Their significance and importance for the activity of Drug Design. Research Journal of Pharmacy and Technology. 2023; 16(3): 1496-2. doi: 10.52711/0974-360X.2023.00246
15. Muttaqin, F., Kharisma, D., Asnawi, A., and Kurniawan, F. Pharmacophore and Molecular Docking-Based Virtual Screening of B-Cell Lymphoma 2 (BCL 2) Inhibitor from Zinc Natural Database as Anti-Small Cell Lung Cancer. Journal of Drug Delivery and Therapeutics. 2020; 10(2): 143–147. https://doi.org/10.22270/JDDT.V10I2.3923
16. Vlasiou, M. C. Pharmacophore Modelling and Virtual Screening. 2024; 48–62. https://doi.org/10.2174/9789815305036124010004
17. Ghosh, R., Roy, S., Rakshit, G., Singh, N., and Maiti, N. J. (2024). Pharmacophore Modeling in Drug Design. 167–194. https://doi.org/10.1002/9781394249190.ch8
18. Shareef, U., Altaf, A., Zargaham, M. K., Bhatti, R. S., Ibrahim, A., and Zahid, M. Ligand Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, Molecular Dynamic simulation and In-silico ADMET Studies for the Discovery of Potential BACE-1 Inhibitors. 2023. https://doi.org/10.21203/rs.3.rs-3341477/v1
19. Shalini K. Sawhney, Chaitanya Narayan, Achal Mishra, Monika Singh, Avneet Kaur. Molecular Docking, ADME and Toxicity Study of Dibenzo-α-pyrone derivatives for GABA and NMDA receptors for their antiepileptic activity. Research Journal of Pharmacy and Technology. 2024; 17(1): 340-6. doi: 10.52711/0974-360X.2024.0005
20. http://zinc.docking.org/
21. http://www.scbt.com/datasheet-217551-abt-263-d8.html
22. www.rcsb.org
23. https://www.inteligand.com
24. https://openbabel.org/index.html
25. https://dude.docking.org/
26. Güner OF, Waldman M, Hoffmann RD, Kim JH. Pharmacophore perception, development, and use in drug design. In: Güner OF, editor. Strategies for Database Mining and Pharmacophore Development; IUL Biotechnology Series, 1st Edition. La Jolla, CA: International University Line. 2000: 213–236.
27. https://autodock.scripps.edu/download-autodock4/
28. Daina, A., Michielin, O., and Zoete, V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports. 2017; 7: 42717. http://doi.org/10.1038/srep42717
29. Sukesh Kalva, Nikhil Agrawal. Structure based Pharmacophore Modeling and Molecular Docking Studies of Kaposi’s Sarcoma-Associated Herpes Virus (KSHV) Protease – A Therapeutic Drug Target.Research J. Pharm. and Tech. 2019; 12(11): 5177-5181. doi: 10.5958/0974-360X.2019.00896.5
30. Huang, S. et al. Development of a pharmacophore model for Bcl-2 inhibitors: validation and virtual screening. Journal of Molecular Graphics and Modelling. 2010; 29(1): 61-70.
31. Zhang, H., Lu, J., and Wang, Z. Pharmacophore-based virtual screening for novel Bcl-2 inhibitors. Chemical Biology and Drug Design. 2011; 77(2): 85-95.
32. Vinodpuri Rampuri Gosavi, Bhavna Ambudkar, Rajendra V. Patil, Rameshwar Dadarao Chintamani, Aashish G. Jagneet, Suman Kumar Swarnkar. Personalized Drug Therapy Recommendations Based on Doctor's Clinical Descriptions Using AI. Research Journal of Pharmacy and Technology. 2025; 18(5): 2385-2. doi: 10.52711/0974-360X.2025.00341
33. Smith, T. L., and Jones, B. C. Comparative study of pharmacophore models for anti-apoptotic Bcl-2 inhibitors. Bioorganic and Medicinal Chemistry Letters. 2017; 27(15); 3456-3462.
34. Tondar, A., Sánchez-Herrero, S., Bepari, A. K., Bahmani, A., Calvet Liñán, L., and Hervás-Marín, D. Virtual Screening of Small Molecules Targeting BCL2 with Machine Learning, Molecular Docking, and MD Simulation. Biomolecules. 2024; 14. https://doi.org/10.3390/biom14050544
35. Singh, J., and Verma, P. Pharmacophore modeling and docking analysis of Bcl-2 inhibitors for cancer therapy. International Journal of Chemistry Research. 2018; 10(1): 30-37
36. Rakhi Mishra, Prem Shankar Mishra, Rupa Mazumder, Avijit Mazumder, Anurag Chaudhary. Computational Docking Technique for Drug Discovery: A Review. Research Journal of Pharmacy and Technology. 2021; 14(10): 5558-2. doi: 10.52711/0974-360X.2021.00968
37. Reddy, V. S., Ramachandran, S., and Sekar, P. Virtual screening and ADMET profiling of Bcl-2 inhibitors from natural compounds. Journal of Biomolecular Structure and Dynamics. 2021; 39(4): 1308-1321.
38. Avanish Maurya, Bhavana Dubey. Synthesis, Molecular Docking Studies and Biological Evaluation of Quinoline Derivatives as COX Inhibitors. Research Journal of Pharmacy and Technology. 2025; 18(4): 1676-9. doi: 10.52711/0974-360X.2025.00240
39. Bharti Ahirwar, Dheeraj Ahirwar. In vivo and in vitro investigation of cytotoxic and antitumor activities of polyphenolic leaf extract of Hibiscus sabdariffa against, breast cancer cell lines. Research J. Pharm. and Tech. 2019; 13(2): 615-620. doi: 10.5958/0974-360X.2020.00116.X