Peptides identification

Over the years, MS/MS duty cycle of modern MS instruments has constantly been improving, but for simplicity we assume it is equal to 1 s. Considering this it is possible to identify up to 60 peptides per minute and up to 3600 peptides in a LC-MS/MS analysis of 1 h. It is important to mention that only a small percentage of MS/MS scans typically yield a spectrum of sufficient quality that can be matched against a protein database and can result in peptide identification. 

It has been argued that in a typical 2DLC proteomic experiment, with only a limited number of fractions submitted for analysis in the second LC dimension, chromatographic peak capacity is less than 1000. This value is considerably lower than the expected sample complexity. Additional resolution is offered by MS, which represents another separation dimension. With the peak capacity defined as the number of MS/MS scans (peptide identifications) accomplished within the LC analysis time, the MS-derived peak capacity was estimated to be in an order of tens of thousands. While the MS peak capacity is virtually independent of LC separation performance, the complexity of the sample entering the MS instrument still defines the quality of MS/MS data acquisition. The primary goal of 2DLC separation is to reduce the complexity of the sample (and concentrate it, if possible) to a level acceptable for MS/MS analysis. What is the acceptable level of complexity to maintain the reliability and the repeatability of DDA experiments remains to be seen. 

Olivova, P., Gilar, M., Dorschel, C. A., Gebler, J.C. (2005). Improved peptide identification and protein coverage for proteomic samples using alternative 2D-HPLC MS/MS approaches. ASMS, 2005, San Antonio, TX Poster TP29. 

FIGURE 16.2 Representative base peak electropherograms from CZE runs of RPLC fractions, (a) Fraction 15 (5 peptide identifications) and (b) fraction 20 (19 peptide identifications). Column, bare fused silica capillary, 60 cm x 180 pm ODx30pm i.d. separation voltage, 15 kV observed CZE current, 1.91 p.A running electrolyte, 200 mm acetic acid + 10% isopropanol temperature, 22°C injection time, 10 s at 2 psi ( 4 nL total injection volume) supplementary pressure, 2 psi flow rate, 25nL/min spray voltage, 1.5 kV (reprinted with permission from Electrophoresis). 

A. Keller, et al., Empirical Statistical Model to Estimate the Accuracy of Peptide Identifications made by MS/MS and Database Search. Anal. Chem., 74, no. 1 (2002) 5383-5392. 

Lehmann, W.D. Bohne, A. von der Lieth, C.W. The Information Encrypted in Accurate Peptide Masses-Improved Protein Identification and Assistance in Glyco-peptide Identification and Characterization. J. Mass Spectrom. 2000, 35. 1335-1341. 

RPC of small peptides can also be used for peptide identification, based on their amino acid composition. Computer programs able to predict peptide retention time are available, thus simplifying peptide identihcation. These programs generally work well with peptide up to 20 amino acids, but fail with larger peptides for which the secondary structure may contribute signihcantly to the retention. 

Different authors used RP-HPLC and UV detection to monitor peptide formation during cheese ripening [174-178], providing valuable information about proteolysis. When large hydrophobic peptide need to be separated an lEC represents the best choice [179]. Nevertheless, the identification of these peptides is essential for the complete understanding of the proteolytic process. The peptides eluted from the LC column can be subjected to ESl-MS for molecular weight determination and MS/MS for amino acid sequence determination, which allow rapid peptide identification [172]. HPLC-ESl-MS and MS/MS techniques have been successfully used for peptide mass fingerprint purposes for sequence analysis of purified albumin from Theobroma cacao seeds [180,181]. 

Bioinformatics tools involving computer-based statistical analyses are essential for data management and analysis. When a complex biological sample containing thousands of different proteins is analyzed by multifaceted approaches, such as multidimensional protein identification technology, the identification of the proteins in the mixture is extremely complicated. Even multiple peptide identification methods, such as using both MS and... 

MS/MS, are often not sufficiently accurate that they can be faithfully relied on [33]. In these cases, a statistical analysis should be introduced that would include more parameters that could assist in protein and peptide identification. For example, the observed and calculated relative retention times from reversed-phase columns could be correlated to provide further validation [34, 35]. 

The capillary HPLC separation from a selected protein spot provides a base-peak profile shown in Figure 6.2A. The base-peak profile is similar to a total ion current (TIC) profile, but it contains only the most abundant mass spectral peak in each scan. The chromatogram is simplified and the contributions from background ion abundances are eliminated, resulting in an enhanced signal-to-ion ratio for an improved visualization of data. The molecular mass for each component is labeled along with corresponding amino acid residues. This format provides a comprehensive approach for peak selection and peptide identification. 

TABLE 2 Mass Spectrometric Approaches for Peptide Identification After Separation By Liquid Chromatography Including Relative Performance Comparisons... 

Aptotoxin VII, from venom of a trap-door spider Rantuerin-2csa, broad-spectrum antibacterial peptide, identification of a full-length helix-turn-helix motif Oral mucosal a-defensin from Rhesus macaque Cobatoxin 1, scorpion venom... 

Signal peptide identification, like DNA intron/exon sequence discrimination, involves the two related problems of signal peptide discrimination (search for content) and cleavage site recognition (search for signal). It is well suited to neural network methods for several reasons. The functional units are encoded by local, linear sequences of amino acids rather than global 3-dimensional structures (Claros et al., 1997). The ambiguity of... 

The latter concept was directly applied to blood plasma, confirming many of the prior peptide identifications (Rose et al., 2004). 

The methods for each study are divided into the initial protein separation step, a second separation step if applicable, the type of mass analysis, and the software used for peptide identification. ID = one dimensional polyacrylamide gel electrophoresis, 2D = two dimensional polyacrylamide gel electrophoresis, MS = mass spectrometry (peptide mass fingerprinting), MS/MS = tandem mass spectrometry, MALDI-TOF = matrix assisted laser desorption/ionization-time of flight, MS FIT = software from Protein Prospector, http //prospector.ucsf edu/, ESI = electrospray ionization, Q-TOF = quadrupole-time of flight, PPSS2 =Protana s Proteomic Software Suite (ProtanaEngineering, Odense, Denmark), Mascot = Matiix Science, http //www.matrixscience.com/, TOF-TOF = MALDI plus TOF tandem mass spectrometry, RP-HPLC = reverse phase high performance liquid chromatography, Q-IT = quadrupole ion trap, LIT = linear ion trap. Bioworks = Thermo Electron Corporation. 

Figure 2. Workflow of an LC-MS/MS experiment. A mixture of peptides from a protein sample digest is separated by reversed-phase chromatography on a nano-flow HPLC. The peptides elute from the RP column and are ionized by an electrospray source. In the first stage of mass spectrometry, m/z values and charge states for each precursor ion are determined and the most abundant precursor ions are selected for analysis in the second stage. The ions are then fragmented with by collision-induced dissociation (CID) a gas to produce fragment ions which are detected. Using the mass (from MS-1) and sequence information (from MS-2) protein sequence databases are searched to provide peptide identifications and protein matches.

Peptide Identification Separate peptides by either rapid microbore RP-HPLC (for... 

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