• Tulasi Kasilingam Department of Science and Biotechnology, Faculty of Engineering and Life Sciences, Universiti Selangor, 45600 Bestari Jaya, Selangor, Malaysia.
  • Asita Elengoe Department of Biotechnology, Faculty of Science, Lincoln University College, 47301 Petaling Jaya, Selangor, Malaysia.


Objective: In this study, three-dimensional (3D) structures of lung cancer cell line proteins (cellular tumor antigen [p53], caspase 3, and mucosal addressin cell adhesion molecule 1) were generated, and their binding affinities with apigenin through local docking were studied.

Methods: The lung cancer cell line proteins were built using Swiss model and visualized by the PyMol software. The physicochemical characterization of the protein models was evaluated by Expasy’s ProtParam Proteomics server. Then, they were validated by PROCHECK, ProQ, ERRAT, and Verify 3D programs. Finally, the protein models were docked with apigenin using BSP-Slim server.

Results: All the protein models were acceptable and of good quality. The apigenin showed the binding energy with cellular tumor antigen (p53), caspase 3, and mucosal addressin cell adhesion molecule 1 at −4.611, −5.750, and −5.307 kcal/mol, respectively.

Conclusion: The caspase 3 had the strongest bond with apigenin. These potential drug candidates can further be validated in laboratory experiments for its proper function.

Keywords: Cellular tumor antigen (p53), Caspase 3, Mucosal addressin cell adhesion molecule 1, Apigenin, Docking.


1. Brambt IE, Travis WD. Lung Cancer. World Cancer Report. World Health Organization; 2014. p. 489-508.
2. Koo LC, Ho JH. Worldwide epidemiological patterns of lung cancer in non-smokers. Int J Epidemiol 1990;19:S14-23.
3. Toh CK, Wong EH, Lim WT. The impact of smoking status on the behaviour and survival outcome of patients with advanced non-small cell lung cancer: A retrospective analysis. Chest 2004;126:1750-6.
4. Chong KL, Kim HL, Catherine MM. Lung cancer in patients younger than 40 years in a multiracial Asian country. Respiratory 2000;5:355-61.
5. Gupta S, Afaq F, Mukhtar H. Selective growth-inhibitory, cell-cycle deregulatory and apoptotic response of apigenin in normal versus human prostate carcinoma cells. Biochem Biophys Res Commun 2001;287:914-20.
6. Kim HY, Kim OH, Sung MK. Effects of phenol-depleted and phenol-rich diets on blood markers of oxidative stress, and urinary excretion of quercetin and kaempferol in healthy volunteers. J Am Coll Nutr 2003;22:217-23.
7. Yang CS, Landau JM, Huang MT, Newmark HL. Inhibition of carcinogenesis by dietary polyphenolic compounds. Annu Rev Nutr 2001;21:381-406.
8. Johnson JL, Rupasinghe SG, Stefani F, Schuler MA, Gonzalez de Mejia, E. Citrus flavonoids luteolin, apigenin, and quercetin inhibit glycogen synthase kinase-3β enzymatic activity by lowering the interaction energy within the binding cavity. J Med Food 2011;14:325-33.
9. Way TD, Kao MC, Lin JK. Apigenin induces apoptosis through proteasomal degradation of HER2/neu in HER2/neu-overexpressing breast cancer cells via the phosphatidylinositol 3-kinase/Akt-dependent pathway. J Biol Chem 2004;279:4479-89.
10. Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, et al. SWISS-MODEL: Modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res 2014;42:W252-8.
11. Delano WL. The PyMOL Molecular Graphics System. Palo Alto, CA: DeLano Scientific; 2001. Available from:
12. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, et al. Protein identification and analysis tools on the ExPASy server. In: Walker JM, editor. The Proteomics Protocols Handbook. Totowa: Humana Press; 2005.
13. Prabi LG. Color Protein Sequence Analysis; 1998.Avaliable from: color.html.
14. Costantini S, Colonna G, Facchiano AM. ESBRI: A web server for evaluating salt bridges in proteins. Bioinformation 2008;3:137-8.
15. Roy S, Maheshwari N, Chauhan R, Sen NK, Sharma A. Structure prediction and functional characterization of secondary metabolite proteins of Ocimum. Bioinformation 2011;6:315-9.
16. Geourjon C, Deleage G. SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Comput Appl Biosci 1995;11:681-4.
17. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: A program to check the stereo chemical quality of protein structures. J Appl Crystallogr 1993;26:283-91.
18. Wallner B, Elofsson A. Can correct protein models be identified? Protein Sci 2003;12:1073-86.
19. Colovos C, Yeates TO. Verification of protein structures: Patterns of non-bonded atomic interactions. Protein Sci 1993;2:1511-9.
20. Eisenberg D, Luthy R, Bowie JU. VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods Enzymol 1977;277:396-404.
21. Jayaram B. Active Site Prediction server; 2004. Available from: http://
22. Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, Han L, He J, He S, Shoemaker BA, Wang J, Yu B, Zhang J, Bryant SH. PubChem Substance and Compound databases. Nucleic Acids Res 2016;44:D1202-13.
23. Hui SL, Yang Z. BSP-SLIM: A blind low-resolution ligand-protein docking approach using theoretically predicted protein structures. Proteins 2012;80:93-110.
24. Purwanggana A, Mumpuni E, Mulatsari E. In vitro and in silico antibacterial activity of 1.5-Bis (3’-ethoxy-4-hydroxyphenyl)-1-4- Pentadiene-3-one. Int J Pharm Pharm Sci 2018;10:70-6.
25. Kumar S, Tsai CJ, Ma B, Nussinov, R. Contribution of salt bridges toward protein thermo stability. J Biomol Struct Dyn 2000;1:79-86.
26. Kumar S, Nussinov R. Salt bridge stability in monomeric proteins. J Mol Bio 2009;293:1241-55.
27. Kumar S, Nussinov R. Relationship between ion pair geometries and electrostatic strengths in proteins. Biophys J 2002;83:1595-612.
28. Parvizpour S, Shamsir MS, Razmara J, Ramli AN, Md Illias R. Structural and functional analysis of a novel psychrophilic b-mannanase from Glaciozyma antarctica PI12. J Comput Aided Mol Des 2014;28:685-98.
29. Shaikh F, Sanehi P, Rawal R. Molecular screening of compounds to the predicted protein-protein interaction site of Rb1-E7 with p53- E6 in HPV. Bioinformation 2012;8:607-12.
30. Lourthuraji A, Masilamani S, Ravikrishnan B, Vinoth M, Hopper W. Analysis of molecular docking efficiency of Cleistanthin-A, as an alternative for nicotine addiction. Int J Pharm Pharm Sci 2018;10:98-100.
31. Barua H, Bhagat N, Toraskar M. Study of binding interactions of human carbonic anhydrase XII. Int J Curr Pharm Res 2017;9:118-25.
192 Views | 338 Downloads
How to Cite
Kasilingam, T., and A. Elengoe. “IN SILICO MOLECULAR MODELING AND DOCKING OF APIGENIN AGAINST THE LUNG CANCER CELL PROTEINS”. Asian Journal of Pharmaceutical and Clinical Research, Vol. 11, no. 9, Sept. 2018, pp. 246-52, doi:10.22159/ajpcr.2018.v11i9.26649.
Original Article(s)