Identification of mutant proteins in biological samples is one of the emerging areas of proteogenomics. Despite the fact that only a limited number of studies have been published up to now, it has the potential to recognize novel disease biomarkers that have unique structure and desirably high specificity. Such properties would identify mutant proteoforms related to diseases as optimal drug targets useful for future therapeutic strategies. While mass spectrometry has demonstrated its outstanding analytical power in proteomics, the most frequently applied bottom-up strategy is not suitable for the detection of mutant proteins if only databases with consensus sequences are searched. It is likely that many unassigned tandem mass spectra of tryptic peptides originate from single amino acid variants (SAAVs). To address this problem, a couple of protein databases have been constructed that include canonical and SAAV sequences, allowing for the observation of mutant proteoforms in mass spectral data for the first time. Since the resulting large search space may compromise the probability of identifications, a novel concept was proposed that included identification as well as verification strategies. Together with transcriptome based approaches, targeted proteomics appears to be a suitable method for the verification of initial identifications in databases and can also provide quantitative insights to expression profiles, which often reflect disease progression. Important applications in the field of mutant proteoform identification have already highlighted novel biomarkers in large-scale investigations.
Keywords: Bottom-up proteomics; Mass spectrometry; Mutant protein identification; Mutation; Non-synonymous single nucleotide polymorphism; Protein databases; Single amino acid variant; Tandem mass spectra.