ProSight PTM 2.0 (http://prosightptm2.scs.uiuc.edu) is the next generation of the ProSight PTM web-based system for the identification and characterization of proteins using top down tandem mass spectrometry. It introduces an entirely new data-driven interface, integrated Sequence Gazer for protein characterization, support for fixed modifications, terminal modifications and improved support for multiple precursor ions (multiplexing). Furthermore, it supports data import and export for local analysis and collaboration.

ProSight PTM (https://prosightptm.scs.uiuc.edu/) is a web application for identification and characterization of proteins using mass spectra data from 'top-down' fragmentation of intact protein ions (i.e. without any tryptic digestion). ProSight PTM has many tools and graphical features to facilitate analysis of single proteins, proteins in mixtures and proteins fragmented in parallel. Sequence databases from across the phylogenetic tree are supported, with a new database strategy of 'shotgun annotation' used to assist characterization of wild-type proteins. During a database search, data from divergent sources regarding potential mass differences such as polymorphisms, alternate splicing and post-translational modifications are utilized. The user can optionally control how much of this biological variability should be searched.

Intimately associated with DNA, histone proteins serve as both a structural scaffold for DNA packaging into the nucleus and an epigenetic means for the regulation of gene expression. One such histone-based mechanism for transcriptional regulation is posttranslational modification (PTM) of histones H2A, H2B, H3, and H4. 1,2 Combinations of modifications such as acetylation, methylation, and phosphorylation create a "Histone Code" that influences gene transcription, gene silencing, and chromatin formation. 3-5 Essential for complete understanding of this code is an efficient methodology for detection, exact localization, and quantitation of modifications at specific sites. We combine here gas-phase concentration and purification 6 inside a quadrupole-FTMS hybrid (Q-FTMS) with top down fragmentation using electron capture dissociation (ECD) 7,8 and large-scale PTM prediction. This prediction uses a new type of protein database that has been "shotgun annotated" by assigning site-specific posttranslational modifications (and all their combinations) prior to searching for best matches with ECD data. The approach considers PTMs during a database search and enables complete and automated characterization of human histones harboring 2-6 PTMs from asynchronous and butyrate-treated HeLa cells.With its sequence and modification sites extensively studied, human histone H4 was chosen as a model. We generated all possible protein forms by combinatorial modification of the seven known sites 1,2 according to following rules: arginine 3 can be mono-or dimethylated, lysines 5,8,12,16, and 20 can be mono-, di-, trimethylated or acetylated, and serine 1 can be phosphorylated. For a given rule set, the possible number of protein forms was calculated by the following equation:where n i is the number of possible PTMs for amino acid i, and f i is the number of occurrences of amino acid i in the sequence allowed to be modified. For histone H4, this generated 3 1 × 5 5 × 2 1 = 18 750 protein forms. Consideration of possible N-terminal acetylation and start methionine on/off increased the total to 46 875. Perl scripts were written to populate all these protein forms into a relational database (7.8 megabyte, MySQL) stored within the architecture of ProSight PTM, a software environment designed for Top Down Proteomics. searches (typically <6 min) were executed with MS/MS data from particular histone forms using ProSight Retriever, an algorithm for probability-based protein identification. 9An ESI/Q-FTMS spectrum of acid-extracted and RPLC-purified histone H4 10 from asynchronous human HeLa cells revealed many potentially modified forms (Figure 1b). An MS/MS spectrum from ECD of a species +112 Da above unmodified H4 gave 91 observed fragment ion masses (Figure 1c). The calibrated fragment ion masses were used to probe the heavily annotated database using tolerances of 5, 15, and 25 ppm (Supporting Information Table 1) with the top 10 hits from the 5 ppm search shown in Figure 2. Of the 91 fragment ions, 50 and 28 match c and z • ions, respec...

For the identification and characterization of proteins harboring posttranslational modifications (PTMs), a "top down" strategy using mass spectrometry has been forwarded recently but languishes without tailored software widely available. We describe a Web-based software and database suite called ProSight PTM constructed for large-scale proteome projects involving direct fragmentation of intact protein ions. Four main components of ProSight PTM are a database retrieval algorithm (Retriever), MySQL protein databases, a file/data manager, and a project tracker. Retriever performs probability-based identifications from absolute fragment ion masses, automatically compiled sequence tags, or a combination of the two, with graphical rendering and browsing of the results. The database structure allows known and putative protein forms to be searched, with prior or predicted PTM knowledge used during each search. Initial functionality is illustrated with a 36-kDa yeast protein identified from a processed cell extract after automated data acquisition using a quadrupole-FT hybrid mass spectrometer. A +142-Da delta(m) on glyceraldehyde-3-phosphate dehydrogenase was automatically localized between Asp90 and Asp192, consistent with its two cystine residues (149 and 153) alkylated by acrylamide (+71 Da each) during the gel-based sample preparation. ProSight PTM is the first search engine and Web environment for identification of intact proteins (https://prosightptm.scs.uiuc.edu/).

The human proteome is a highly complex extension of the genome wherein a single gene often produces distinct protein forms due to alternative splicing, RNA editing, polymorphisms, and posttranslational modifications. Due to the presence of polymorphisms, alternative splicing, and posttranslational modifications (PTMs) 1 the human proteome is highly complex, often encoding multiple protein forms for a given gene (1). This biological complexity poses a significant analytical and bioinformatic challenge to the detailed analysis of mammalian proteomes by MS and is exacerbated by the presence of gene families sharing high sequence identity (2, 3). Protein modifications are often indicative of changes in cellular or tissue dynamics and therefore play central roles in regulation of the cell cycle or development of disease. Whether for new diagnostics or understanding molecular mechanisms in cell biology, protein identification using tryptic peptides has revolutionized the analysis of complex mixtures by mass spectrometry (1, 4). High throughput platforms based on MALDI (5) and ESI use MS/MS engines capable of spectral acquisition at a rate of Ͼ10 4 /week (6, 7). Recent studies indicate significant inefficiencies associated with such large scale "bottom up" analyses in mammalian systems including imperfect enzymatic cleavage (8, 9) and some MS/MS spectra requiring manual interpretation/validation for identification. Despite the lingering difficulties with peptide analysis, it provides the best and most general method for large scale protein identification today with information on nonsynonymous coding single nucleotide polymorphisms (cSNPs), alternative splicing (10), and PTMs challenging to obtain (2).Recent developments by MacCoss et al. (11), Wu et al. (12), and Zhu et al. (13) use three proteases and multidimensional protein identification technology ("MudPIT") or isoelectric focusing, reversed-phase chromatography, and three mass spectrometers (13), respectively, to obtain mass information on ϳ70 -99% of the primary protein structure. Combining intact protein measurement with near exhaustive peptide analysis of five proteins from human cells allowed detection of N-terminal modifications and one alternatively spliced transcript (13). Although cSNP analysis of abundant blood proteins is possible (14), a general informatic strategy has yet to systematically integrate DNA and RNA level data with the MS-based interrogation of the human proteome. This is accomplished here using a data base of human proteins tailored