title: EpiDOCK: a molecular docking-based tool for MHC class II binding prediction.
abstract: Cellular peptide vaccines contain T-cell epitopes. The main prerequisite for a peptide to act as a T-cell epitope is that it binds to a major histocompatibility complex (MHC) protein. Peptide MHC binder identification is an extremely costly experimental challenge since human MHCs, named human leukocyte antigen, are highly polymorphic and polygenic. Here we present EpiDOCK, the first structure-based server for MHC class II binding prediction. EpiDOCK predicts binding to the 23 most frequent human, MHC class II proteins. It identifies 90% of true binders and 76% of true non-binders, with an overall accuracy of 83%. EpiDOCK is freely accessible at http://epidock.ddg-pharmfac.net.
authors: School of Pharmacy, Medical University of Sofia, 2 Dunav street, 1000 Sofia, Bulgaria.
authors: Mariyana
authors: M
authors: Atanasova
authors: Atanas
authors: A
authors: Patronov
authors: Ivan
authors: I
authors: Dimitrov
authors: Darren R
authors: DR
authors: Flower
authors: Irini
authors: I
authors: Doytchinova
mesh_terms: D000483:Alleles; D019295:Computational Biology / Q000379:methods*; D000949:Histocompatibility Antigens Class II / Q000737:chemistry* / Q000235:genetics / Q000276:immunology*; D006801:Humans; D020407:Internet; D062105:Molecular Docking Simulation / Q000379:methods*; D011487:Protein Conformation; D015203:Reproducibility of Results; D014612:Vaccines / Q000276:immunology
chemical_list: D000949:Histocompatibility Antigens Class II; D014612:Vaccines
keywords: MHC class II binding prediction; docking; peptide vaccines; quantitative matrices