In Silico Investigation and Docking Studies of E2F3 Tumor Marker: Discovery and Evaluation of Potential Inhibitors for Prostate and Breast Cancer

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 A 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.