Informatics for protein identification by mass spectrometry
peer-reviewed · Methods · 2005
| Date | 2005-03-01 |
| Type | peer-reviewed |
| Venue | Methods |
| Publisher | Elsevier BV |
| Contribution | review |
| DOI | 10.1016/j.ymeth.2004.08.014 |
| Citations (OpenAlex) | 126 |
Abstract
High throughput protein analysis (i.e., proteomics) first became possible when sensitive peptide mass mapping techniques were developed, thereby allowing for the possibility of identifying and cataloging most 2D gel electrophoresis spots. Shortly thereafter a few groups pioneered the idea of identifying proteins by using peptide tandem mass spectra to search protein sequence databases. Hence, it became possible to identify proteins from very complex mixtures. One drawback to these latter techniques is that it is not entirely straightforward to make matches using tandem mass spectra of peptides that are modified or have sequences that differ slightly from what is present in the sequence database that is being searched. This has been part of the motivation behind automated de novo sequencing programs that attempt to derive a peptide sequence regardless of its presence in a sequence database. The sequence candidates thus generated are then subjected to homology-based database search programs (e.g., BLAST or FASTA). These homology search programs, however, were not developed with mass spectrometry in mind, and it became necessary to make minor modifications such that mass spectrometric ambiguities can be taken into account when comparing query and database sequences. Finally, this review will discuss the important issue of validating protein identifications. All of the search programs will produce a top ranked answer; however, only the credulous are willing to accept them carte blanche.
Methods and tools
- Informatics for protein identification by MS (review): Reviews protein identification informatics from mass mapping to database search, with a focus on automated de novo sequencing, MS-aware homology search and validation.