title: Identification of short terminal motifs enriched by antibodies using peptide mass fingerprinting.
abstract: BACKGROUND
  Mass spectrometry-based protein profiling has become a key technology in biomedical research and biomarker discovery. Sample preparation strategies that reduce the complexity of tryptic digests by immunoaffinity substantially increase throughput and sensitivity in proteomic mass spectrometry. The scarce availability of peptide-specific capture antibodies limits these approaches. Recently antibodies directed against short terminal motifs were found to enrich subsets of peptides with identical terminal sequences. This approach holds the promise of a significant gain in efficiency. TXP (Triple X Proteomics) and context-independent motif specific/global proteome survey binders are variants of this concept. Principally the binding motifs of such antibodies have to be elucidated after generating these antibodies. This entails a substantial effort in the lab, as it requires synthetic peptide libraries and numerous mass spectrometry experiments.
  
  
  RESULTS
  We present an algorithm for predicting the antibody-binding motif in a mass spectrum obtained from a tryptic digest of a common cell line after immunoprecipitation. The epitope prediction, based on peptide mass fingerprinting, reveals the most enriched terminal epitopes. The tool provides a P-value for each potential epitope, estimated by sampling random spectra from a peptide database. The second algorithm combines the predicted sequences to more complex binding motifs. A comparison with library screenings shows that the predictions made by the novel methods are reliable and reproducible indicators of the binding properties of an antibody.
authors.affiliation: Natural and Medical Sciences Institute (NMI) at the University of Tübingen, Markwiesenstr. 55, D-72770 Reutlingen and Center for Bioinformatics, University of Tübingen, Sand 1, D-72076 Tuebingen, Germany.
authors.forename: Hannes
authors.initials: H
authors.lastname: Planatscher
authors.forename: Frederik
authors.initials: F
authors.lastname: Weiß
authors.forename: David
authors.initials: D
authors.lastname: Eisen
authors.forename: B H J
authors.initials: BH
authors.lastname: van den Berg
authors.forename: Andreas
authors.initials: A
authors.lastname: Zell
authors.forename: Thomas
authors.initials: T
authors.lastname: Joos
authors.forename: Oliver
authors.initials: O
authors.lastname: Poetz
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000906:Antibodies / Q000737:chemistry / Q000276:immunology*; D030562:Databases, Protein; D000939:Epitopes / Q000032:analysis / Q000737:chemistry; D013058:Mass Spectrometry / Q000379:methods*; D010449:Peptide Mapping / Q000379:methods*; D040901:Proteomics / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods*; D012985:Software Design
chemical_list: D000906:Antibodies; D000939:Epitopes