Proteins characterization, databases

Number of Proteins and Residues in Databases of Intrinsically Disordered Protein Characterized by Various Methods... 

In parallel with these advances in mRNA detection and assessment, significant advances in the detection, characterization, and quantitation of proteins have been made. This is not only a result of the rapidly expanding database of protein sequences but also of the extraordinary advances in sensitivity of mass spectrometry techniques. It is proposed, with some real sense of expected success, that protein characterization at the whole genome level will be forthcoming (Domon and Aebersold, 2006). 

Data-dependent switching between a survey-MS mode and the product-ion MS-MS mode (Ch. 2.4.2) in the LC-MS analysis of tryptic digest on a triple-quadrapole instrument was pioneered by Stahl et al. [140]. The MS-MS spectra obtained were correlated wiA a protein sequence database by using the SEQUEST program. DDA (also called SmartSelect, or Information-Dependent Acquisition, IDA) on ion-trap, Q-LIT, and Q-TOF instruments have become important tools in high-throughput protein characterization. 

The discussion in this chapter focussed at developments in the field of protein characterization, and provided an overview of the technology developed to enable proteomics studies (Ch. 18). The strategies outline above have been applied to increasingly complex samples. Some examples are the detection and identification of human leucocyte antigen peptides related to the major histocompatibility complex [166], and the unattended identification of 90 proteins from the yeast Saccharomyces cerevisiae by means of an integrated workstation for LC-MS-MS under DDA and with database searching [34]. 

Sigrist CJA, Cerutti L, de Castro E et al (2010) PROSITE, a protein domain database for functional characterization and annotation. Nucleic Acids Res 38 D161-D166... 

These protein attributes are then submitted to a database search. This search identifies a protein by looking at the best match between experimental data and data obtained by in-silico processing and digestion of a protein sequence database. The identification and characterization procedures using bioinformatics tools will be the topic of Section 4.4. 

Typically, identification tools in proteomics focus on one or more experimentally obtained protein properties and try to achieve protein identification by matching their values against the corresponding theoretical values computed for all sequences in a protein sequence database. Characterization tools are using a more predictive approach in the sense that they do not only match experimental data with data extracted from a database. They perform a predictive calculation to propose PTMs, splicing events or other features. 

Comprehensive interpretation of the experimental proteomic data is only reachable in a step-by-step approach. This means that the experimentalist must have the possibility to come back to the original data at any time, in order to complete its characterization and in order to perform efficient comparison studies. In fact, as protein sequence databases are not complete, a number of identifications are failing, especially in eukaryotes. As the databases are regularly updated, identification must be regularly re-run with the incorporated data. This must regularly and automatically launch new calls to the identification tools and then update the results and the interpretation. 

BLOCKS [22,23] is an automatically generated protein family database closely related to PRINTS like the latter, it represents patterns characterizing family membership as sets of multiply aligned, ungapped sequence segments (BLOCKS). 

Saposin-like proteins (SAPLIP), a diverse family of lipid-interacting proteins characterized by a conserved pattern of cysteine residues. They show various cellular functions of which most are only partly understood. More than 200 different SAPLIP have been found in relevant databases occurring from amoebozoans to mammals [R. S. Munford et al., J. Lipid Res. 1995, 36, 1653 H. Bruhn, Biochem.J. 2005, 389, 249]. 

Topological proteomics means visualization of the abnormal cellular protein networks, cell by cell. Conventional proteomics is performed in three steps separation of complex protein mixtures, characterization of the separated proteins, and database searching to identify the composition of the complex. The employed techniques such as 2-D electrophoresis and mass spectrometry use tissue homogenates. Therefore, only quantitative changes of the most abundant proteins with particular biochemical properties can be detected. Any topological information, information on the cellular and sub-cellular distribution of proteins, that determines protein-interactions in networks, is lost. 

Neubauer, G., King, A., Rappsilber, J., Calvio, C., Watson, M., Ajuh, P., Sleeman, J., Lamond, A., and Mann, M. (1998). Mass spectrometry and EST-database searching allows characterization of the multi-protein spliceosome complex. Nat. Genet. 20, 46-50. 

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