PepFinder Software

PepFinder Software 

Deep Protein Characterization Is Crucial

Pharmaceuticals have historically been small molecules. Today however, many newly approved drugs are derived from proteins. For protein therapeutics to be effective, they must be produced in biologically active forms, which require proper folding, and post-translation modifications (PTMs). Detailed characterization of these modifications is crucial. A comprehensive verification of the protein's (amino acid) sequence, assessment of purity and identification of impurities in a recombinant protein drug product along with a detailed characterization of the existing PTMs, is a regulatory requirement prior to its approval for clinical use.

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Thermo Scientific™ PepFinder™ software provides accurate characterization of biologics and uses multidimensional dynamic search capabilities to automatically reduce complex data into a concise and informative report. With this new paradigm for peptide mapping, confidence in the results is increased while significantly reducing the data analysis time.

Automated identification and relative quantitation of proteins and variants

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PepFinder software is a powerful new tool for in-depth characterization of biotherapeutic proteins. It automates the analysis of LC-MS and MS/MS data to provide identity and relative quantitation of proteins, variants, and low level post translational modifications (PTMs). Using the industry-leading, high-resolution, accurate-mass Thermo Scientific™ Orbitrap™ technology with PepFinder software, the most accurate and confident PTM profiles and identifications can be achieved more quickly than ever before. This novel software allows for:

  • Fast automated component detection- peptide mass, retention time and abundance, with background subtraction to improve overall signal to noise.
  • Peptide identification is performed using full MS data or MS/MS.
  • Extra confidence in peptide identification is achieved by using a novel ms/ms predictive algorithm.
  • Quantification of modifications, including glycoforms, deamidation, oxidation, custom modification (e.g. drug conjugates) and many more.
  • Error tolerant search allows for identification of unspecified modifications and amino acid substitutions.
  • Characterization of disulfide linkages including non predictive bonds and disulfide scrambling.
  • Automated modification summary report for rapid monitoring of modification site in a single sample or across multiple samples in a study.
  • Comprehensive sequence coverage map for target proteins
PepFinder Software Basic Workflow
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Step 1: Experimental Setup - Target proteins and data file selection:

  • Define target protein sequence, and PTM's to search including mass window for unspecified modifications.
  • Select raw data file
    - Multiple files can be processed at the same time allowing for comparison across studies.

 

 

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Step 2: Data Processing

  • Component detection:
    - Fast intelligent peak detection and integration.
  • Peptide identification
    - A novel identification algorithm predicts MS/MS fragmentation which provides more confidence in peptide identification for all modes of fragmentation types such as CID, ETD and HCD.

 

 

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Step 3: Report Generation and Manual Review

  • Reports:
    -Automated sequence coverage map and modification site summary report with recovery information and abundance of specific modifications in one sample or comparison across samples.
  • Data review:
    - Interactive visual display of software predicted and experimental MS/MS spectrum.

 

 

Increased confidence using the kinetic model for peptide MS/MS fragmentation prediction

PepFinder software uses a novel predicted MS/MS algorithm to identify peptide sequences. Other algorithms are available which calculate the m/z of the frame ion. But unlike others, PepFinder software also determines the fragment's relative abundance using the unique kinetic model , which is vital when fragmentation is limited.

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Peptide identification for a Glycopeptide CSRFPNATDKE (N34+A4G0). The identification of this glycopeptide was assigned by comparing the measured spectra (B) to the kinetic model predicted spectra (A). Notice how the fragmentation comes almost exclusively from the sugar, and with other search engines the lack of the peptide sequence information would cause this peptides to not be identified. Because PepFinder software is able to predict the spectra extremely well, even though the MS/MS spectra has very few fragment ions and does not have any peptide backbone ions, the software makes a confident assignment because it matches the prediction. In this case the lack of information in the MS/MS spectra proves the match.

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Peptide identification for a medium size peptide LRPICGTDGV TYTND. The identification was assigned by comparing the measured spectrum (C) to the kinetic model predicted spectrum (B) unique to PepFinder software displayed. Notice the difference between the relative abundance of the fragment ions in the kinetic model compared to the empirical model (A) commonly found in other software programs.

Determination of disulfide linkage

Using PepFinder software, disulfide mapping is easily achieved by processing a non-reduced peptide map data file. No previous knowledge of linkage sites is required, therefore novel linkages and potential disulfide bond scrambling can be identified and confirmed by MS/MS. A non-reduced and reduced data set can be compared at the same time for
additional confidence.

Below is an example of a disulfide bond identified by PepFinder software. As shown, PepFinder software is able to display the coverage of each peptide individually from within the mixed MS/MS spectrum.

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Fragment ion spectrum for the disulfide bonded species. The fragment evidence for each of the two peptides involved in a disulfide-bonded dipeptide are highlighted. The top pane shows the unlabeled, HCD spectrum of the +3 parent ion, and the fragment evidence supporting the Light Chain Peptide 1 (LC01) is shown on the same spectrum in the middle pane. In the bottom pane fragment evidence for LC02 is highlighted. In each of the middle and bottom panes, the heavy lines are multiply charged fragment ions which identifies and confirms the location of the disulfide bond.

Identification of glycoforms

Finder software automatically identifies N-linked glycosylated peptides and provides a report of the glycoforms that are present and their relative abundances. Glycoforms anticipated by PepFinder software include N-glycans with 1-4 antenna, each antenna terminating with sialic acid, galactose, or N-acetylgucosamine, with and without core-fructose, plus hybrid-type and high-mannose type; a total of 147 possible N-glycans commonly observed in IgG monoclonal antibodies.

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PepFinder software modification site summary for different glycoforms is compared to three specific glycoforms in Qual Browser. The relative abundance order of different glycoforms reported by PepFinder (automatic) match the raw results from Qual Broswer (manual). PepFinder software modification site summary can significantly increase data processing by eliminating the need for manual calculations.

Comparison

PepFinder software automatically performs a comparison when more than one data file is uploaded into the software. This workflow includes retention alignment for shifts in chromatography along with gap filling, so that a peptide identified in one file will be automatically detected and integrated in other files, even if it was below the designated threshold. Relative abundance of each site-specific modification is reported across each sample, along with the component peak area values, for easy export into other software packages for further statistical and trend analysis.

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Shown above is modification site summary report for a four sample comparison. Sample 2 was untreated, sample 1 was oxidized, and samples 3 and 4 were treated with different amounts of glycine. The relative abundance for several different modifications are shown in the columns. Highlighted in red are lysine glycation which is elevated in samples 3 and 4 as expected. Highlighted in green are two different oxidations which are increased in sample 1.

Error tolerant/amino acid substitution

PepFinder software automatically performs error tolerant searches and will identify unspecified modifications and amino acid substitutions with confidence. Shown in this example is the CID spectra of a peptide with a substitution of V->F. The fragmentation
coverage map is easily generated for additional confirmation.

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Amino acid substitution of V->F is confirmed by the CID spectra (B) and the peptide fragmentation map (C) shows both y9 and b13 (site of substitution) were identified for extra confidence in the assignment. The unmodified peptide spectra is displayed in (A).

Proteome Discoverer User Meeting 2017

Reserve the date for this year’s Proteome Discoverer Users’ Meeting.  It will take place at the Atlantic Grand Hotel Bremen, Germany, on December 11-12.  More info to come soon!