ProteinScape 527x245px

Powerful Tools for Protein Analysis

ProteinScape uses Mascot as search engine (other engines are supported via mzIdentML) together with expert algorithms that increase the quality and reliability of protein identifications.

 

Compiling protein lists for improved search results

The ProteinExtractor compiles multiple peptide lists from a number of different techniques and instruments, significantly improving overall search results and increasing confidence in identifications.

 

Decoy validation approaches

ProteinScape supports decoy-database approaches to generate protein lists based on defined false-discovery rates.

 

Posttranslational modifications (PTMs)

Labile modifications like phosphorylation require special fragmentation techniques for optimum analysis. Electron Transfer Dissociation (ETD) fragments peptide backbones, leaving labile PTMs intact. ETD specific annotation in the Spectrum and Sequence viewers enables fast and easy interpretation of ETD analyses.

 

Theoretical digest

If the protein sequence is known the database search can be skipped, and a theoretical digest is performed instead with subsequent matching of the theoretical peptide masses to the spectraof an LC-MS/MS dataset. Using theintegrated Sequence Editor, modificationcan be varied in a highly flexible way.

Recalibration

For MALDI PMF spectra, the ScoreBooster module significantly improves the identification success and the scores, by automatically recalibrating spectra based on frequently occurring background masses and removing those during the search routine.

For LC-MS/MS data, all precursor and fragment masses are recalibrated based on peptide ID results. In this way, a successive search can be performed with a narrower mass tolerance window. This keeps False Discovery Rates low, even if more missed cleavages, a less specific enzyme or variable modifications are allowed.

 

Targeted data acquisition

A typical application of a scheduled precursor list (SPL) starts with an initial monitoring LC-MS/MS run, which is used to identify a comprehensive set of proteins. Information on the identified peptides is used to create an exclusion SPL for a second LC-MS/MS run, allowing a much higher protein identification rate based on newly identified peptide species. Protein and peptide tables from both runs are then combined using the ProteinExtractor, giving a search result with significantly increased protein sequence coverages.

Reduced False Discovery Rate of Peptides
The recalibration on identified peptides shifts the maximum of the distribution of mass deviations towards zero. For a successive database search, the mass tolerance can be reduced. This leads to a
significantly reduced False Discovery Rate.

Biological knowledge at your fingertips

Once a protein is identified, ProteinScape automatically assembles information such as taxonomy, GO terms, and structure files from external databases. An interactive three-dimensional display highlights identified regions and modifications and a gene ontology overview gives information on protein function and location.

Gene Ontology Viewer
Gene ontology viewer displays protein function within
biological processes
Protocol (click to enlarge).

Extracting Knowledge through Data Mining

Managing the huge amount of data generated in proteomics projects can be a daunting task. Efficient tools are required to quickly and precisely extract information from the mass of available data. ProteinScape uses queries to search defined data subsets for spectra meeting specific protein or glycan attributes. Protein queries and searches can be compared to find species common to different data sets, a feature especially useful in method optimization.

Interactive Venn Diagram
Interactive Venn diagram displaying a comparison of four protein
search results after enrichment of N-glycopeptides using
different lectin stationary phases. Clicking an intersection
displays the relevant proteins or peptides in a table (click to enlarge)

Protein quantitation

ProteinScape supports a number of labeled and label-free quantitation workflows. Flexible tools for statistical analysis display results in an easy to interpret format. Clicking on a point of interest automatically loads the associated protein or peptide data into the open viewers, giving immediate access to information on regulated species.

 

ProteinScape supports

  • Label-free quantitation
  • Non-isobaric labels (for example, ICPL, SILAC and 16O/18O)
  • Isobaric labels (for example iTRAQ and TMT)
Statistical Data Set Overview
Statistical overview of entire data sets (log ratio vs peptide
intensity) allowing fast detection of regulated species (click to enlarge).
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