Role of Accurate Mass Measurement (±10 ppm) in Protein Identification Strategies Employing MS or MS/MS and Database Searching

Karl R. Clauser(Ludwig Cancer Research), Peter R. Baker(Ludwig Cancer Research), Alma L. Burlingame(Ludwig Cancer Research)
Analytical Chemistry
May 27, 1999
Cited by 1,099

Abstract

We describe the impact of advances in mass measurement accuracy, +/- 10 ppm (internally calibrated), on protein identification experiments. This capability was brought about by delayed extraction techniques used in conjunction with matrix-assisted laser desorption ionization (MALDI) on a reflectron time-of-flight (TOF) mass spectrometer. This work explores the advantage of using accurate mass measurement (and thus constraint on the possible elemental composition of components in a protein digest) in strategies for searching protein, gene, and EST databases that employ (a) mass values alone, (b) fragment-ion tagging derived from MS/MS spectra, and (c) de novo interpretation of MS/MS spectra. Significant improvement in the discriminating power of database searches has been found using only molecular weight values (i.e., measured mass) of > 10 peptide masses. When MALDI-TOF instruments are able to achieve the +/- 0.5-5 ppm mass accuracy necessary to distinguish peptide elemental compositions, it is possible to match homologous proteins having > 70% sequence identity to the protein being analyzed. The combination of a +/- 10 ppm measured parent mass of a single tryptic peptide and the near-complete amino acid (AA) composition information from immonium ions generated by MS/MS is capable of tagging a peptide in a database because only a few sequence permutations > 11 AA's in length for an AA composition can ever be found in a proteome. De novo interpretation of peptide MS/MS spectra may be accomplished by altering our MS-Tag program to replace an entire database with calculation of only the sequence permutations possible from the accurate parent mass and immonium ion limited AA compositions. A hybrid strategy is employed using de novo MS/MS interpretation followed by text-based sequence similarity searching of a database.


Related Papers