IN SILICO INVESTIGATION AND DOCKING STUDIES OF E2F3 TUMOR MARKER: DISCOVERY AND EVALUATION OF POTENTIAL INHIBITORS FOR PROSTATE AND BREAST CANCER

Authors

  • Sinosh Skariyachan Department of Biotechnology, Dayananda Sagar College of Engineering, Bangalore, India
  • Shruthi Krishnan Rao Department of Biotechnology, Dayananda Sagar College of Engineering, Bangalore, India
  • Usha B. Biradar Department of Biotechnology, Dayananda Sagar College of Engineering, Bangalore, India

Abstract

E2F3 encodes a transcription factor important for cell cycle regulation and DNA replication. It plays a significant role in the development of various types of human cancer. Genomics and proteomics features of the tumor marker have a pronounced significance in the pharmainformatics studies. The crystal structure of E2F3 is not available in any structural database; hence a 3D structure is very essential for structural studies and discovery of potential inhibitors against tumour proteins. In this study we modelled a 3D structure of E2F3 by X-ray crystal structure of Bovine Bc1 with Azoxystrobin of Bos taurus (PDB ID: 1SQB, Chain B) used as the template. Our study found that E2F3 predominantly consists of α helix. The RMSD value of modelled protein was found to be 0.5 Ao and steriochemical validation shows 86. 1% residues are in allowed region of Ramachandran plot. Further validation was done by various empirical force fields. Overall quality factor of the model identified to be 57.36 and error values of individual residues are negligible. The modeled protein was submitted to Protein Model Database and can be downloaded with PMDID 0076554.With the help of docking studies the best ligand against E2F3 was found to be Vinblastine, an antitumor alkaloid isolated from Vinca rosea, with binding energy -4558.33.The ligand interacts with the modeled protein at residues Glu-432, Asp-433, Tyr-434, Leu-435 and 436.The other best inhibitors identified from our study were Oncovin, Navelbine, Taxol and Taxotere. The investigation concluded that these drugs could be used as the potential inhibitors against E2F3 tumor marker in prostate and breast cancer.

Keywords:

E2F3, Tumor marker, Homology Modeling, Refinement, Docking, Vinblastine

DOI

https://doi.org/10.25004/IJPSDR.2010.020405

References

1. Yan Lu, Yijun Yi, Pengyuan Liu, Weidong Wen, Michael James, Daolong Wang, Ming You. Common Human Cancer Genes Discovered by Integrated Gene-Expression Analysis. PLoS ONE. 2007; 2: e1149.
2. Eric J. Kort, Leslie Farber, Maria Tretiakova, David Petillo, Kyle A. Furge, Ximing J. Yang, Albert Cornelius, Bin T. The E2F3—Oncomir 1 axis is activated in Wilms Tumor. Cancer Res. 2008; 68: 4034-4038.
3. Tsantoulis PK, Gorgoulis VG. Involvement of E2F transcription factor family in cancer. Eur J Cancer. 2005; 41:2403-2414.
4. Rakha EA, Pinder SE, Paish EC, Robertson JF, Ellis IO. Expression of E2F-4 in invasive breast carcinomas is associated with poor prognosis. J Pathol. 2004; 203:754-761.
5. Sandeep Sanga, Hermann B. Frieboes, Xiaoming Zheng, Robert Gatenby, Elaine L.Bearer, Vittorio Cristini. Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth. Neuroimage. 2007; 37: 120-134.
6. Bong-Hyun Kim,Hua Cheng, Nick V. Grishin, Hor A. Web server to infer homology between proteins using sequence and structural similarity. Nucleic Acids Res. 2009; 37: 532-538.
7. Christiam Camacho, George Coulouris, Vahram Avagyan, Ning Ma, Jason Papadopoulos, Kevin Bealer, Thomas L Madden. BLAST+: Architecture and applications. BMC Bioinformatics. 2009; 10: 421 doi: 10.1186/1471-2105-10-421.
8. Anne Friedrich, Raymond Ripp, Nicolas Garnier, Emmanuel Bettler, Gilbert Deléage, Olivier Poch, Luc Moulinier, Blast sampling for structural and functional analyses. BMC Bioinformatics 2007; 8: 62 doi: 10.1186/1471-2105-8-62.
9. David Piedra, Sergi Lois, Xavier De La Cruz. Preservation of protein clefts in comparative models. BMC Struct Biol. 2008; 8: 2. doi:10.1186/1472-6807-8-2.
10. Martin Zachairias. Protein–protein docking with a reduced protein model accounting for side-chain flexibility. Protein Sci. 2003; 1271-1282.
11. Lyskov S, Gray JJ. The Rosetta Dock server for local protein-protein docking, Nucleic Acids Res. 2008; 36: 233-238.
12. Rolf Apweiler. UniProt: the Universal Protein knowledgebase. Nucleic Acids Res. 2004; 32: 115-119.
13. Mark Johnson. NCBI BLAST: a better web interface. Nucleic Acids Res. 2008; 36: 5-9.
14. Sagl B Needleman, Christus D, Wuksch A. General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins. J. Mol. Bwl. 1970; 48: 443-453.
15. Notredame C, Higgins DG, Heringa J. T-Coffee: A novel method for fast and accurate multiple sequence alignment. J Mol Biol. 2000; 302:205-17.
16. McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics. 2000; 16: 404-5.
17. Claros MG, von Heijne G. TopPred II: An improved software for membrane protein structure predictions. Comput Appl Biosci 1994; 10: 685-6.
18. Ivica Letunic, Richard R. Copley, Birgit Pils, Stefan Pinkert, Jörg Schultz, Peer Bork. SMART 5: domains in the context of genomes and networks. Nucleic Acids Res. 2006; 1: 257-260.
19. Sali A, Blundell TL. Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol. 1993; 234:779-81.
20. Holm L, Park J. DaliLite workbench for protein structure comparison. Bioinformatics. 2000; 16: 566-7.
21. Daniel Seeliger, Bert L. De Groot. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des. 2010; 24: 417-422.
22. Melo F, Devos D, Depiereux E, Feytmans E, ANOLEA: a www server to assess protein structures. Proc Int Conf Intell Syst Mol Biol. 1997; 5:187-90.
23. Markus Christen. The GROMOS Software for Biomolecular Simulation: GROMOS05. J Comput Chem 26. 1719-1751, 2005.
24. David Eisenberg, Roland Lüthy, James U. Bowie VERIFY3D: Assessment of protein models with three dimensional profile. Methods in Enzymology. 1997; 277: 396-404
25. Laskowski, R.A. PROCHECK: a program to check the stereiochemical quality of protein structures. J. Appl. Cryst. 1993; 26:283–291.
26. Colovos C, Yeates TO. Verification of protein structures: patterns of non-bonded atomic interactions. Protein Sci. 1993; 2:1511-1519.
27. Tiziana Castrignanò. The PMDB Protein Model Database. Nucleic Acids Res. 2006; 34: 306–309.
28. Yanli Wang. An overview of the PubChem BioAssay resource. Nucleic Acids Res. 2010; 38: 255-266.
29. Minoru Kanehisa, Susumu Goto, Miho Furumichi, Mao Tanabe, Mika Hirakawa. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 2010; 38: 355-360.
30. David S. Wishart, Craig Knox, An Chi Guo, Dean Cheng, Savita Shrivastava, Dan Tzur, Bijaya Gautam, Murtaza Hassanali. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 2008; 36: 901-906.
31. Gary Macindoe, Lazaros Mavridis, Vishwesh Venkatraman, Marie-Dominique Devignes, David W. Ritchie. HexServer: an FFT-based protein docking server powered by graphics processors. Nucleic Acids Res. 38: 445-449.
32. Lingling Duan, Kristen Sterba, Sergey Kolomeichuk, Heetae Kim, Powel H. Brown, Timothy C. Chambers. Inducible over expression of c-Jun in MCF7 cells causes resistance to vinblastine via inhibition of drug-induced apoptosis and senescence at a step subsequent to mitotic arrest. Biochem Pharmacol. 2007; 73: 481-90.
33. Johnson I S, Armstrong JG, Gorman M, Burnett J P, The Vinca alkaloids: a new class of oncolytic agents. Cancer Res. 1963; 23: 1390-427.
34. Marty M, Fumoleau P, Adenis A, Rousseau Y, Merrouche Y, Robinet G, Senac I, Puozzo C: Oral vinorelbine pharmacokinetics and absolute bioavailability study in patients with solid tumors. Ann Oncol. 2001; 12:1643.
35. Fuchs DA, Johnson RK. Cytologic evidence that taxol, An antineoplastic agent from Taxus brevifolia, acts as a mitotic spindle poison. Cancer Treat Rep. 1978; 62:1219-22.
36. Ritchie DW. Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2. Proteins. 2003; 98-106.

Published

01-10-2010
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“IN SILICO INVESTIGATION AND DOCKING STUDIES OF E2F3 TUMOR MARKER: DISCOVERY AND EVALUATION OF POTENTIAL INHIBITORS FOR PROSTATE AND BREAST CANCER”. International Journal of Pharmaceutical Sciences and Drug Research, vol. 2, no. 4, Oct. 2010, pp. 254-60, https://doi.org/10.25004/IJPSDR.2010.020405.

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How to Cite

“IN SILICO INVESTIGATION AND DOCKING STUDIES OF E2F3 TUMOR MARKER: DISCOVERY AND EVALUATION OF POTENTIAL INHIBITORS FOR PROSTATE AND BREAST CANCER”. International Journal of Pharmaceutical Sciences and Drug Research, vol. 2, no. 4, Oct. 2010, pp. 254-60, https://doi.org/10.25004/IJPSDR.2010.020405.