Application of signal processing in computational analysis of HSP interactions

Heat shock proteins (HSPs) are a group of proteins that are present in all cells. HSP immunotherapy is believed to be one of the most promising areas of developed cancer treatment technology that is characterized by a unique approach to every tumor. HSPs are induced when a cell is influenced by environmental stresses like heat, cold and oxygen deprivation. Under perfectly normal conditions HSPs act like `chaperones' helping new or distorted proteins fold into shape essential for their function, shuttle proteins and transport old proteins to `garbage disposals' inside the cell. HSPs also play a significant role in helping the immune system recognize diseased cells. Twenty years ago HSPs were identified as the element responsible for protecting animals from cancer, and studies towards anti-tumor vaccine development still continue today. Here we have computationally analyzed HSPs, EGF and oncogene proteins aiming to find structural similarities of EGF, EGFR, oncogene and proto-oncogene proteins that can underline possible interaction of these proteins with HSPs. The resonant recognition model (RRM) was employed in this study to perform structure-function analysis of selected proteins and determine the RRM frequencies that represent the characteristic feature of protein biological behavior.