Evaluating peptide mass fingerprinting-based protein identification

Abstract

Identification of proteins by mass spectrometry (MS) is an essential step in proteomic studies and is typically accomplished by either peptide mass fingerprinting (PMF) or amino acid sequencing of the peptide. Although sequence information from MS/MS analysis can be used to validate PMF-based protein identification, it may not be practical when analyzing a large number of proteins and when high- throughput MS/MS instrumentation is not readily available. At present, a vast majority of proteomic studies employ PMF. However, there are huge disparities in criteria used to identify proteins using PMF. Therefore, to reduce incorrect protein identification using PMF, and also to increase confidence in PMF-based protein identification without accompanying MS/MS analysis, definitive guiding principles are essential. To this end, we propose a value-based scoring system that provides guidance on evaluating when PMF-based protein identification can be deemed sufficient without accompanying amino acid sequence data from MS/MS analysis.

Fig. 1

Effect of α value and the number of sequences in a database on the distribution of threshold Mowse scores. The threshold Mowse score was calculated as —10 lg(P), where P is α value/number of sequences in the database. A protein match above a particular Mowse threshold score indicates that the match is less likely to be random and is likely to be significant. The bars represent the threshold Mowse scores for theoretical database sequences at different α values (0.05, 0.01, and 0.001).