title: Prediction of the antigenic sites of the cystic fibrosis transmembrane conductance regulator protein by molecular modelling.
abstract: Antibodies are powerful tools for studying the in situ localization and physiology of proteins. The prediction of epitopes by molecular modelling has been used successfully for the papilloma virus, and valuable antibodies have been raised [Müller et al. (1990) J. Gen. Virol., 71, 2709-2717]. We have improved the modelling approach to allow us to predict epitopes from the primary sequences of the cystic fibrosis transmembrane conductance regulator. The procedure involves searching for fragments of primary sequences likely to make amphipathic secondary structures, which are hydrophilic enough to be at the surface of the folded protein and thus accessible to antibodies. Amphipathic helices were predicted using the methods of Berzofsky, Eisenberg and Jähnig. Their hydrophobic-hydrophilic interface was calculated and drawn, and used to predict the orientation of the helices at the surface of the native protein. Amino acids involved in turns were selected using the algorithm of Eisenberg. Tertiary structures were calculated using 'FOLDING', a software developed by R. Brasseur for the prediction of small protein structures [Brasseur (1995) J. Mol. Graphics, in press]. We selected sequences that folded as turns with at least five protruding polar residues. One important property of antibodies is selectivity. To optimize the selectivity of the raised antibodies, each sequence was screened for similarity (FASTA) to the protein sequence from several databanks. Ubiquitous sequences were discarded. This approach led to the identification of 13 potential epitopes in the cystic fibrosis transmembrane conductance regulator: seven helices and six loops.
authors.affiliation: INSERM U10, Hôpital Bichat-Claude Bernard, Paris, France.
authors.forename: X
authors.initials: X
authors.lastname: Gallet
authors.forename: N
authors.initials: N
authors.lastname: Benhabiles
authors.forename: M
authors.initials: M
authors.lastname: Lewin
authors.forename: R
authors.initials: R
authors.lastname: Brasseur
authors.forename: A
authors.initials: A
authors.lastname: Thomas-Soumarmon
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000954:Antigens, Surface / Q000737:chemistry* / Q000276:immunology; D019005:Cystic Fibrosis Transmembrane Conductance Regulator / Q000737:chemistry* / Q000276:immunology; D000939:Epitopes / Q000737:chemistry*; D005583:Fourier Analysis; D006801:Humans; D008838:Microcomputers; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010446:Peptide Fragments / Q000737:chemistry; D011237:Predictive Value of Tests; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000276:immunology; D017386:Sequence Homology, Amino Acid; D012984:Software
chemical_list: D000954:Antigens, Surface; C505032:CFTR protein, human; D000939:Epitopes; D010446:Peptide Fragments; D011506:Proteins; D019005:Cystic Fibrosis Transmembrane Conductance Regulator