skip to main content

Molecular Interaction Analysis of COX-2 Against Aryl Amino Alcohol Derivatives from Isoeugenol as Anti Breast Cancer using Molecular Docking

1Master Program of Chemistry, Chemistry Department, Universitas Islam Indonesia, Kampus Terpadu UII, Jl. Kaliurang Km 14, Sleman, Yogyakarta, Indonesia

2Department of Chemistry, Universitas Islam Indonesia, Jl. Kaliurang Km 14, Sleman, Yogyakarta, 55584, Indonesia

Received: 8 Feb 2021; Revised: 1 Jun 2021; Accepted: 2 Jun 2021; Published: 30 Sep 2021; Available online: 3 Jun 2021.
Open Access Copyright (c) 2021 by Authors, Published by BCREC Group
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Cover Image

Breast cancer occurs due to uncontrolled cells proliferation. The Proliferation causes severe inflammatory which can be the initial stages of cancer symptoms. Aryl amino alcohol compounds from isoeugenol derivatives are proposed for the potential drugs of breast cancer. This study was conducted on iso-eugenol derivatives by adding carbonyl groups, hydroxyl groups, halide compounds and amines to determine the effect on anticancer activity through molecular docking studies. The molecular docking approach is carried out to see the interaction of ligands with protein compounds by using the minimized ligand energy bind with protein active site using protein data bank ID 5GMN. The docking result show that IE-Benzanilide-Cl (11) and IE-Benzanilide-OH (10) have the lowest binding energy (−8.3 kcal/mol and −8.6 kcal/mol) compare to another compounds. AdmetSAR computer simulations show that all compounds have very few toxic effects. The use of aryl amino alcohol derivatives (10 and 11) may be suggested as anti-breast cancer drugs. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (


Fulltext View|Download
Keywords: Breast Cancer; Molecular Docking; Aryl Amino Alcohol; Iso-Eugenol; Proliferation
Funding: Biomass Drug Food Development (BioDFD) Research Group ; the Ministry of Higher Education Research and Technology Republic of Indonesia

Article Metrics:

Article Info
Section: The 3rd International Conference on Chemistry, Chemical Process and Engineering 2020) (IC3PE 2020)
Language : EN
  1. Nagai, H., Kim, Y.H. (2017). Cancer prevention from the perspective of global cancer burden patterns. Journal of Thoracic Disease, 9, 448–451. DOI: 10.21037/jtd.2017.02.75
  2. Siegel, R.L., Miller, K.D., Jemal, A. (2020). Cancer statistics, 2020. CA: A Cancer Journal for Clinicians, 70, 7–30. DOI: 10.3322/caac.21590
  3. National Cancer Management Committee. (2013). Guidelines for Breast Cancer Management. Jakarta
  4. DeNardo, D.G., Coussens, L.M. (2007). Inflammation and breast cancer. Balancing immune response: Crosstalk between adaptive and innate immune cells during breast cancer progression. Breast Cancer Research, 9, 212. DOI: 10.1186/bcr1746
  5. Allen, M.D., Jones, L.J. (2015). The role of inflammation in progression of breast cancer: Friend or foe? (Review). International
  6. Journal of Oncology, 47, 797–805. DOI: 10.3892/ijo.2015.3075
  7. Mills, R.C. (2017). Breast Cancer Survivors, Common Markers of Inflammation, and Exercise: A Narrative Review
  8. Breast Cancer: Basic and Clinical Research, 11, 1–12. DOI: 10.1177/1178223417743976
  9. Harris, R.E., Casto, B.C., Harris, Z.M. (2014). Cyclooxygenase-2 and the inflammogenesis of breast cancer. World Journal of Clinical Oncology, 5, 677–692. DOI: 10.5306/wjco.v5.i4.677
  10. Colin, B. (2013). Vascular and upper gastrointestinal eff ects of non-steroidal anti-inflammatory drugs : meta-analyses of individual. The Lancet, 382, 769–779. DOI: 10.1016/S0140-6736(13)60900-9
  11. Morris, G., Marguerita, L.-W. (2006). Molecular Docking. Encyclopedic Reference of Genomics and Proteomics in Molecular Medicine, 443, 1149–1153. DOI: 10.1007/3-540-29623-9_3820
  12. Fadilah, F., Yanuar, A., Arsianti, A., Andrajati, R., Purwaningsih, E.H. (2017). In silico study of aryl eugenol derivatives as anti-colorectal cancer by inducing of apoptosis. Asian Journal of Pharmaceutical and Clinical Research, 10, 345–349. DOI: 10.22159/ajpcr.2017.v10i12.21233
  13. Atsumi, T., Fujisawa, S., Satoh, K., Sakagami, H., Iwakura, I., Ueha, T., Sugita, Y., Yokoe, I. (2000). Cytotoxicity and radical intensity of eugenol, isoeugenol or related dimers. Anticancer Research, 20, 2519–2524. DOI: 10.1016/s0300-483x(02)00194-4
  14. Atsumi, T., Fujisawa, S., Tonosaki, K. (2005). A comparative study of the antioxidant/prooxidant activities of eugenol and isoeugenol with various concentrations and oxidation conditions. Toxicology in Vitro, 19, 1025–1033. DOI: 10.1016/j.tiv.2005.04.012
  15. Kim, S.J., Kim, H.S., Seo, Y.R. (2019). Understanding of ROS-Inducing Strategy in Anticancer Therapy. Oxidative Medicine and Cellular Longevity, 2019, 5381692. DOI: 10.1155/2019/5381692
  16. Bezerra, D.P., Militão, G.C.G., De Morais, M.C., De Sousa, D.P. (2017). The dual antioxidant/prooxidant effect of eugenol and its action in cancer development and treatment. Nutrients, 9(12), 1367. DOI: 10.3390/nu9121367
  17. Lipinski, C.A., Lombardo, F., Dominy, B.W., Feeney, P.J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23, 3–25. DOI: 10.1016/S0169-409X(96)00423-1
  18. Vyas, V.K., Gupta, N., Ghate, M., Patel, S. (2014). Design, synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II-AT1 receptor antagonists based on predictive 3D QSAR models. SAR and QSAR in Environmental Research, 25, 117–146. DOI: 10.1080/1062936X.2013.868825
  19. Hanwell, M.D., Curtis, D.E., Lonie, D.C., Vandermeersch, T., Zurek, E., Hutchison, G.R. (2012). Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. Journal of Cheminformatics, 262, 476–483. DOI: 10.1186/1758-2946-4-17
  20. Yang, H., Lou, C., Sun, L., Li, J., Cai, Y., Wang, Z., Li, W., Liu, G., Tang, Y. (2019). AdmetSAR 2.0: Web-service for prediction and optimization of chemical ADMET properties. Bioinformatics, 35, 1067–1069. DOI: 10.1093/bioinformatics/bty707
  21. Kim, H.T., Cha, H., Hwang, K.Y. (2016). Structural insight into the inhibition of carbonic anhydrase by the COX-2-selective inhibitor polmacoxib (CG100649). Biochemical and Biophysical Research Communications, 478, 1–6. DOI: 10.1016/j.bbrc.2016.07.114
  22. Trott, O., Olson, A.J. (2010). Autodock vina: improving the speed and accuracy of docking. Journal of Computational Chemistry, 31, 455–461.
  23. Pratama, R., Ambarsari, L., Sumaryada, T.I. (2017). Molecular Interaction Analysis of COX-2 against Curcuminoid and Xanthorizol Ligand as Anti Breast Cancer using Molecular Docking. Current Biochemistry, 2, 139–149. DOI: 10.29244/cb.2.3.139-149
  24. Blake, J.F. (2000). Chemoinformatics - Predicting the physicochemical properties of “drug-like” molecules. Current Opinion in Biotechnology, 11, 104–107. DOI: 10.1016/S0958-1669(99)00062-2
  25. Zhou, P.Z., Babcock, J., Liu, L.Q., Li, M., Gao, Z.B. (2011). Activation of human ether-a-go-go related gene (hERG) potassium channels by small molecules. Acta Pharmacologica Sinica, 32, 781–788. DOI: 10.1038/aps.2011.70
  26. Hansen, K., Mika, S., Schroeter, T., Sutter, A., ter Laak, A., Steger-Hartmann, T., Heinrich, N., Müller, K.-R. (2009). Benchmark data set for in silico prediction of Ames mutagenicity. Journal of Chemical Information and Modeling, 49, 2077–2081. DOI: 10.1021/ci900161g
  27. Lagunin, A., Filimonov, D., Zakharov, A., Xie, W., Huang, Y., Zhu, F., Shen, T., Yao, J., Poroikov, V. (2009). Computer-aided prediction of rodent carcinogenicity by PASS and CISOC-PSCT. QSAR & Combinatorial Science, 28, 806–810. DOI: 10.1002/qsar.200860192

Last update:

No citation recorded.

Last update:

No citation recorded.