title: Predicted B-cell epitopes of HER-2 oncoprotein by a bioinformatics method: a clue for breast cancer vaccine development.
abstract: Breast cancer is one of the most common cancers in the world and is on the increase. Vaccines are new hopes for primary prevention of this cancer. In the breast cancer case, HER2 is a focus as a target for vaccine development. Here, preliminary data from a computation analysis of this outer membrane protein to find potential B-cell epitopes are described using a new bioinformatics tool. According to the results, 947SRMARDPQRFVVIQNE262 is the peptide with the best binding affinity. These data may be useful for further vaccine development because promiscuous peptide binders allow the total number of predicted epitopes to be minimized without compromising the population coverage required in the design of vaccines.
authors.affiliation: Department of Laboratory Medicine, Chulalongkorn University, Bangkok, Thailand. wviroj@yahoo.com
authors.forename: Viroj
authors.initials: V
authors.lastname: Wiwanitkit
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000517:prevention & control*; D019496:Cancer Vaccines / Q000276:immunology*; D019295:Computational Biology; D018985:Epitopes, B-Lymphocyte / Q000276:immunology*; D006801:Humans; D010446:Peptide Fragments / Q000737:chemistry / Q000276:immunology* / Q000378:metabolism; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000276:immunology*; D012984:Software
chemical_list: D019496:Cancer Vaccines; D018985:Epitopes, B-Lymphocyte; D010446:Peptide Fragments; D018719:Erb-b2 Receptor Tyrosine Kinases