title: Mutations and interactions in human ERα and bZIP proteins: An in silico approach for cell signaling in breast oncology.
abstract: I.
  
  
  BACKGROUND
  Metastasis of breast cancer serves the most aggravating cause for transience in breast cancer patients. Accumulating evidences suggest that signal transduction in human breast cancers commences in estrogen-reliant pattern via signaling of the estrogen-receptor α-subunit (ERα) and XBP-1 (bZIP-domain) proteins. Furthermore, earlier investigations from SAGE and GST pull-down assay, also state that a point mutation in ERα leads to a risky factor by resulting into hyper-responsiveness towards estrogen and increased proliferation of breast cancer cells. So, a molecular-level exploration into the signaling mechanism is a prime requisite for future clinical and therapeutic progress. II.
  
  
  RESULTS
  Present study explores primarily the residual participation of the two essential proteins from humans to boost the signaling mechanism in malignant breast tumors. So, 3D structures of the respective monomer proteins were demonstrated and mutated protein was homology modeled after the satisfaction of the stereo-chemical features. The functionality was observed to be conserved after mutation. Abrupt increment in protein-protein interactions was studied for the individual optimized and Molecular Dynamics simulated protein complexes. Revelation from supportive statistical significances for several energy calculations, solvent accessibility areas, electrostatic surface potentials and interaction studies led to confer that after mutation, the complex and the individual protein were the most stable and the best interactive one. For metastasis in breast cancer cells, polar charged residues hold a significant contribution. III.
  
  
  CONCLUSIONS
  Therefore, this investigation provides a cogent framework for the interactive studies associated with breast cancer and an exposure towards the lethal impact on mutation.
authors.affiliation: Department of Biotechnology, National Institute of Technology, Mahatma Gandhi Avenue, Durgapur, West Bengal, India. Electronic address: arundhati.92star@gmail.com.
authors.forename: Arundhati
authors.initials: A
authors.lastname: Banerjee
authors.affiliation: Department of Biochemistry and Biophysics, University of Kalyani, Kalyani, Nadia, West Bengal, India; Amity Institute of Biotechnology, Amity University, Kolkata, West Bengal, India. Electronic address: raysujay@gmail.com.
authors.forename: Sujay
authors.initials: S
authors.lastname: Ray
mesh_terms: D003198:Computer Simulation; D018360:Crystallography, X-Ray; D047628:Estrogen Receptor alpha / Q000737:chemistry* / Q000378:metabolism*; D006801:Humans; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D009687:Nuclear Proteins / Q000737:chemistry* / Q000378:metabolism*; D011487:Protein Conformation; D000072417:Protein Domains; D055550:Protein Stability; D016601:RNA-Binding Proteins / Q000737:chemistry* / Q000378:metabolism*; D015398:Signal Transduction; D014157:Transcription Factors / Q000737:chemistry* / Q000378:metabolism*
chemical_list: C105242:ALYREF protein, human; C506487:ESR1 protein, human; D047628:Estrogen Receptor alpha; D009687:Nuclear Proteins; D016601:RNA-Binding Proteins; D014157:Transcription Factors
keywords: Docked protein-protein interaction; Molecular Dynamics simulated complexes; Mutation; Optimized tertiary structures; Statistically significant stability parameters and breast cancer metastasis