The Mascot score (M-score) is one of the conventional validity measures in data base identification of peptides and proteins by MS/MS data. Although tremendously useful, M-score has a number of limitations. For the same MS/MS data, M-score may change if the protein data base is expanded. A low M-value may not necessarily mean poor match but rather poor MS/MS quality. In addition M-score does not fully utilize the advantage of combined use of complementary fragmentation techniques collisionally activated dissociation (CAD) and electron capture dissociation (ECD). To address these issues, a new data base-independent scoring method (S-score) was designed that is based on the maximum length of the peptide sequence tag provided by the combined CAD and ECD data. The quality of MS/MS spectra assessed by S-score allows poor data (39% of all MS/MS spectra) to be filtered out before the data base search, speeding up the data analysis and eliminating a major source of false positive identifications. Spectra with below threshold M-scores (poor matches) but high S-scores are validated. Spectra with zero M-score (no data base match) but high S-score are classified as belonging to modified sequences. As an extension of S-score, an extremely reliable sequence tag was developed based on complementary fragments simultaneously appearing in CAD and ECD spectra. Comparison of this tag with the data base-derived sequence gives the most reliable peptide identification validation to date. The combined use of M- and S-scoring provides positive sequence identification from >25% of all MS/MS data, a 40% improvement over traditional M-scoring performed on the same Fourier transform MS instrumentation. The number of proteins reliably identified from Escherichia coli cell lysate hereby increased by 29% compared with the traditional M-score approach. Finally S-scoring provides a quantitative measure of the quality of fragmentation techniques such as the minimum abundance of the precursor ion, the MS/MS of which gives the threshold S-score value of 2.