Abstract
Abstract*Motivation:* In current proteome research, peptide sequencing is probably the most widely used method for protein mixture identification. However, this peptide-centric method has its own disadvantages such as the immense volume of tandem Mass Spectrometry (MS) data for sequencing peptides. With the fast development of technology, it is possible to investigate other alternative techniques. Peptide Mass Fingerprinting (PMF) has been widely used to identify single purified proteins for more than 15 years. Unfortunately, this technique is less accurate than peptide sequencing method and cannot handle protein mixtures, which hampers the widespread use of PMF technique. If we can remove these limitations, PMF will become a useful tool in protein mixture identification. *Results:* We first formulate the problem of PMF protein mixture identification as an optimization problem. Then, we show that the use of some simple heuristics enables us to find good solutions. As a result, we obtain much better identification results than previous methods. Moreover, the result on real MS data can be comparable with that of the peptide sequencing method. Through a comprehensive simulation study, we identify a set of limiting factors that hinder the performance of PMF method in protein mixtures. We argue that it is feasible to remove these limitations and PMF can be a powerful tool in the analysis of protein mixtures.
Highlights
The identification and quantification of proteins expressed in a cell or tissue is an explicit goal of proteomics
(2) What are the limiting factors in the use of Peptide Mass Fingerprinting (PMF) method in protein mixture identification? Through a comprehensive simulation study, we show that the performance of PMF is mainly affected by the mass accuracy of mass spectrometer, the number of component proteins in the mixture, the sequence coverage of each protein and the noise level in MS data
3.1 Evaluation Criteria and PMF Algorithms Since we know the ground-truth proteins in both simulation and real data, each protein in the final protein list Y is counted as a true positive (TP) if it belongs to ground-truth proteins or as a false positive (FP) otherwise
Summary
The identification and quantification of proteins expressed in a cell or tissue is an explicit goal of proteomics. Among existing protein identification strategies, peptide mass fingerprinting (PMF) has been widely used to identify single purified proteins since 1993 (James et al, 1993; Mann et al, 1993; Pappin et al, 1993; Yates et al, 1993). PMF has begun to fall out of favor in much of proteomics community (Yang et al, 2008) because of recent advances in the analysis of complex protein mixtures using shotgun proteomics (Aebersold and Mann, 2003; Link et al, 1999; Gygi et al, 1999; Washburn et al, 2001). The shotgun proteomic strategy combines protein digestion and tandem MS (MS/MS) based peptide sequencing to perform peptide-centric identification. If we can overcome these limitations, there will be great potential to use PMF method as an alternative or supplement of the peptide sequencing method in analyzing complex protein mixtures
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