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Hopfgartner, G.

Publications and source records attributed to Hopfgartner, G..

2 recordsLinked to original sources

Differentiating specific and non-specific protein-metabolite interactions using gradient open port probe electrospray ionization mass spectrometry

Native electrospray ionization mass spectrometry (ESI-MS) using nano ESI or desorption electrospray ionization (DESI) has been widely used to study interactions between macromolecules and ligands, usually protein-metabolite interactions (PMIs). In MS spectra the charge state distributions (CSD) of proteins differ between native and non-native conditions and based on this, we report a method that can differentiate specific protein-metabolite interactions from non-specific binding. Our approach is based on a 3D-printed open port probe electrospray system (gOPP-ESI) using mobile phase gradients (aqueous to methanol) for the ionization of protein/protein-metabolite complex. Notably, we found that a true protein-metabolite complex is more resistant to the denaturing effect of methanol compared to the free protein. This is corroborated by the observation that forming high charge states of protein-metabolite complexes requires higher proportions of methanol than free protein while, for non-specific complexes, there is no obvious difference in the CSD. Therefore, by comparing the changes in the CSD of free protein and protein-metabolite complex versus the increase of methanol, we can distinguish metabolites that specifically interact with the target protein. The approach is evaluated with well-characterized protein-ligand pairs, and we confirmed that cytidine phosphates, N, N', N''-triacetylchitotriose, and fluvastatin are specific ligands for ribonuclease A, lysozyme, and beta-lactoglobulin respectively. However, cytidine-5-triphosphate (CTP) interacts non-specifically with lysozyme and beta-lactoglobulin. We believe that after first-round native-MS assays to identify which metabolites cause mass shifts to the free protein, the gOPP-ESI-MS could be used as a quick second-round check to exclude non-specific binding and discover metabolites truly interacting with the protein of interest, reducing the number of candidates for subsequent validation experiments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/583904v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@e2aad7org.highwire.dtl.DTLVardef@13e287borg.highwire.dtl.DTLVardef@1d3c6c0org.highwire.dtl.DTLVardef@9da2a8_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

GlycansToGraphs: visualizing and simplifying complex mass spectra

1.We describe a software tool, GlycansToGraphs, used to identify and visualize relationships between masses in MS or MS/MS spectra and illustrate its application to data dependent acquisition (DDA) spectra of glycopeptides. The software is written in python 3.11 and uses the streamlit package (1.29) to generate a User Interface (UI) in a web browser. It uses simple text input files, does not require databases (glycan or protein) and the user can define any mass difference that the software searches for in an unbiased manner. Located mass differences generate graphs with edges that correspond to the relationships between nodes (masses) and collections of connected nodes, known as components, which can be analyzed to extract sequences of relationships.

bioinformatics↗