Peptide Mass Maps: A Highly Informative Approach to Protein Identification

Abstract

A computer searching algorithm has been used to identify protein sequences in the Protein Information Resource (PIR) database with peptide mass information (mass map) obtained from proteolytic digests of proteins analyzed by microcapillary high-performance liquid chromatography electrospray ionization mass spectrometry. A theoretical analysis of the cytochrome c family demonstrates the ability to identify protein sequences in the PIR database with a high degree of accuracy using a set of six predicted tryptic peptide masses. This method was also applied to experimentally determined peptide masses for a small GTP-binding protein, a protein from pig uterus, the human sex steroid binding protein, and a thermostable DNA polymerase. The results demonstrate that a set of observed masses which is less than 50% of the total number of predicted masses can be used to identify a protein sequence in the database. For the analysis presented in this paper, a mass matching tolerance of 1 amu is used. Under these conditions, mass maps created by fast atom bombardment mass spectrometry and matrix-assisted laser desorption time-of-flight would also be applicable. In cases where multiple matches are observed or verification of the protein identification is needed, tandem mass spectrometry sequencing can be used to establish sequence similarity.

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