MODi : a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra

Identification of post-translational modifications (PTMs) is important to understanding the biological functions of proteins. MS/MS is a useful tool to identify Most proteins undergo PTMs1 at multiple sites. The types and sites of PTMs in a protein vary widely and affect its cellular functions. Identification of all PTMs present in a protein is a key step toward understanding its biological functions and interactions inside a cell (1, 2). MS/MS (3, 4) allows rapid identification of many types of PTMs. However, data analysis and interpretation of MS/MS spectra for identification of PTMs remain a major challenge.Early approaches to PTM identification using MS/MS involved exhaustive searches of all possible combinations of PTMs for each peptide from a protein database (5, 6). Because the search space grows exponentially as the number of PTMs increases, these early approaches performed a restrictive search that takes into account only a few types of PTMs during data analysis, ignoring all others. Investigators were obliged to guess the PTMs expected to exist in a sample prior to a search, and many potentially important PTMs may have been overlooked.Various new approaches have been developed to increase the number of PTMs that can be identified during data analyses. VEMS (7) introduced an improved algorithm to reduce the search space, OpenSea (8) implemented a mass-based sequence alignment between database peptides and de novo interpretation, and TwinPeaks (9) improved the basic scoring scheme of SEQUEST (5), a popular database search program. But none of these approaches fully addressed the current limitations in the number of PTMs. A few tools were recently introduced for blind PTM search. MS-Alignment (10) predicts PTMs expected in a sample by spectral alignment between a database peptide and a spectrum followed by InsPecT (11) search. ModifiComb (12) introduced a ⌬M histogram between unassigned spectra and base peptides found in a database. These blind approaches predict PTMs based on the frequency of mass shifts (indicating potential PTMs) in a sample. Thus, they all have the intrinsic weakness of missing rare PTMs infrequently observed that might provide important clues to understanding the function of a protein. Although many approaches have been developed to take into account many types of PTMs, most assume that there will be a single variable PTM per peptide and ignore multiply modified peptides. On the contrary, our studies with human glyceraldehyde-3-phosphate dehydrogenase (GAPDH) showed that there are many multiply modified peptides in a biological sample.Here we describe a new algorithm, named MOD i , that identifies multiple PTMs in a peptide while placing virtually no limit From the ‡Department

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“…A graphical tool to annotate MS/MS spectra is available (34). It is recommended to use MOD i for data sets from high mass accuracy instruments.…”

Section: Modmentioning

confidence: 99%

Unrestrictive Identification of Multiple Post-translational Modifications from Tandem Mass Spectrometry Using an Error-tolerant Algorithm Based on an Extended Sequence Tag Approach

Jeong

Park

et al. 2008

Molecular & Cellular Proteomics

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“…Identification of unknown modifications in the oxidized CA and BSA digests analyzed by LC-MS/MS was done using MOD i , a search engine that uses mass spectrometry data to identify protein modifications [9]. A local database containing the BSA and CA FASTA files was used for sequence matching.…”

Section: Protein and Ptm Identificationmentioning

confidence: 99%

Iodination on Tyrosine Residues During Oxidation with Sodium Periodate in Solid Phase Extraction of N-linked Glycopeptides

Cohen

Kostyleva

Chisholm

et al. 2011

J. Am. Soc. Mass Spectrom.

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Solid-phase extraction of N-linked glycopeptides (SPEG) using hydrazide-modified supports has become a common sample preparation procedure in glycoproteomic experiments. We demonstrate that iodination of tyrosine residues occur in SPEG as a side reaction during an oxidation step with sodium periodate. MS/MS analysis of oxidized bovine serum albumin and carbonic anhydrase digests revealed a characteristic shift of m/z 125.9 on all y and b fragment ions containing the modified tyrosine residues. Selected reaction monitoring (SRM) measurements showed that the peak intensity from of the iodinated peptides increased during the course of oxidation. After an hour of oxidation, SRM analysis revealed that the strongest signal from an iodinated peptide was approximately one-tenth of the intensity of the corresponding unmodified peptide. Iodinated tyrosine residues were also identified in serum samples subjected to SPEG and analyzed by LC-ESI-MS/MS. We recommend assessing this side reaction by including iodotyrosine as a variable modification when performing database searches on SPEG experiments. For SRM-based acquisitions, we encourage the avoidance of tyrosine-containing glycopeptides or, if this is not practical, monitoring transitions that contain the potential modified iodinated tyrosine residue to monitor the presence of the iodinated form of the glycopeptide.

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“…However, these database search tools are not well-suited for the identification of various types of PTM peptides, and thus, other tools like MODi (40), which have been specially designed for the identification of post-translationally modified proteins (PTM peptides), are used.…”

Section: Integrative Proteomics Data Analysismentioning

confidence: 99%

From proteomics toward systems biology: integration of different types of proteomics data into network models

Rho

You²,

Kim³

et al. 2008

BMB Reports

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Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples. [BMB reports 2008; 41(3): [184][185][186][187][188][189][190][191][192][193]

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MODi : a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra

Cited by 53 publications

References 19 publications

Unrestrictive Identification of Multiple Post-translational Modifications from Tandem Mass Spectrometry Using an Error-tolerant Algorithm Based on an Extended Sequence Tag Approach

Unrestrictive Identification of Multiple Post-translational Modifications from Tandem Mass Spectrometry Using an Error-tolerant Algorithm Based on an Extended Sequence Tag Approach

Iodination on Tyrosine Residues During Oxidation with Sodium Periodate in Solid Phase Extraction of N-linked Glycopeptides

From proteomics toward systems biology: integration of different types of proteomics data into network models

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