ProteaseGuru: A Tool for Protease Selection in Bottom-Up Proteomics.
Rachel M MillerKhairina IbrahimLloyd M SmithPublished in: Journal of proteome research (2021)
Bottom-up proteomics is currently the dominant strategy for proteome analysis. It relies critically upon the use of a protease to digest proteins into peptides, which are then identified by liquid chromatography-mass spectrometry (LC-MS). The choice of protease(s) has a substantial impact upon the utility of the bottom-up results obtained. Protease selection determines the nature of the peptides produced, which in turn affects the ability to infer the presence and quantities of the parent proteins and post-translational modifications in the sample. We present here the software tool ProteaseGuru, which provides in silico digestions by candidate proteases, allowing evaluation of their utility for bottom-up proteomic experiments. This information is useful for both studies focused on a single or small number of proteins, and for analysis of entire complex proteomes. ProteaseGuru provides a convenient user interface, valuable peptide information, and data visualizations enabling the comparison of digestion results of different proteases. The information provided includes data tables of theoretical peptide sequences and their biophysical properties, results summaries outlining the numbers of shared and unique peptides per protease, histograms facilitating the comparison of proteome-wide proteolytic data, protein-specific summaries, and sequence coverage maps. Examples are provided of its use to inform analysis of variant-containing proteins in the human proteome, as well as for studies requiring the use of multiple proteomic databases such as a human:mouse xenograft model, and microbiome metaproteomics.
Keyphrases
- mass spectrometry
- liquid chromatography
- big data
- endothelial cells
- electronic health record
- amino acid
- label free
- health information
- gas chromatography
- induced pluripotent stem cells
- data analysis
- high resolution mass spectrometry
- high performance liquid chromatography
- tandem mass spectrometry
- capillary electrophoresis
- case control
- pluripotent stem cells
- machine learning
- molecular docking
- healthcare
- artificial intelligence
- molecular dynamics simulations
- social media
- deep learning
- binding protein
- simultaneous determination
- living cells
- ms ms