Generating theoretical spectra for peptide identification

We derive the optimal number of peaks (defined as the minimum number that provides the required efficiency of spectra identification) in the theoretical spectra as a function of: (i) the experimental accuracy, σ, of the measured ratio m/z, (ii) experimental spectrum density, (iii) size of the database, and (iv) fragment detection efficiency. We show that if theoretical spectra are constructed including b and y ions only, then for σ = 0.5, which is typical for high throughput data, peptide chains of 8 amino acids or longer can be identified based on the number of matches alone, at a rate of false identification below 1%. To discriminate between shorter peptides, additional (e.g., intensity-inferred) information is necessary. We derive the dependence of the probability of false identification on the number of peaks in the theoretical spectra and on the types of ions that the peaks represent. Our results suggest that the class of mass spectrum identification problems for which more elaborate development of fragmentation rules (such as intensity model, etc.) is required, can be reduced to the problems that involve homologous peptides.