HDX Workbench is an established feature-rich software platform for the analysis of hydrogen/deuterium exchange (HDX) mass spectrometry data from Waters or Thermo instruments. Our software allows users to quickly calculate deuteration levels for peptides, it integrates intuitive visualization tools to provide everything you need to understand and report protein conformation in the presence of HDX.
Take single amide resolution to the next level with ETD HDX analysis. Examine ETD MS2 peaks, auto detect scrambling, view bar charts and see deuterium uptake at the peptide fragment scale. Integrate ETD and conventional HDX data into existing single residue models.
Cross compare result data from one or many experiments to show localized differences in protein conformation in a color coded table view. Show data from any combination of time points, delete rows, and group experiments according to similarity. Show underlying plots for any group of experiments. Export results as a table or a graphic.
Data from single amide resolution calculations are plotted onto a structure in a single click in PyMol. Represent the data from all time points faithfully using established consolidation strategies that make sense. Don't randomly pick individual peptides or time points for this step. Take the guesswork out of 3D plots!
See deuteration changes in at the residue level stacked across multiple experiments. The colored heat map reveals and presents differences between many states or differential experiments in whatever order you like.
See your XICs over multiple selected replicates color coded and displayed in a single view, facilitating validation of the peptide assignments and providing feedback regarding chromatographic consistency over several runs. Multiple mass ranges from peptide peak sub windows are used, providing more accurate and representative chromatographic peaks for the peptide of interest.
Have all data from multiple sources available in one place, organized by project, and associated with the specific user login. Projects can be shared and tied to multiple user logins. A wide range of functions are available contextually from each tree node such as launching a detect job, editing experiment information, editing protein information, and loading result data. As the number of user experiments grows this feature becomes indispensable for the organization of HDX data.
Find your peptides automatically using our detection algorithm, which initially compares the the theoretical distribution for the peptide with the experimental spectra using least squares regression. Many additional tests are added to this process / recipe we have been developing our over several years. More accurate detection = less adjustment = less time curating data = happy users.
Define of single and multiple point mutations in the peptide set and track them through HDX analysis. Results are merged and rendered in the visualization tools.
Export all underlying data in a single file and generate your own plots or apply statistics. Copy underlying plot data from a group of peptides and paste directly into Prism for advanced statistics and vector graphic plots. Export all uptake plots in a single click. All graphics can be exported.
View exactly where peptide peaks are expected, automatically disregard "non-peptide" peaks in convoluted regions, and understand exactly how your centroid calculations are calculated from the averaged mass spectrum using the sub range windows approach. Visually inspect, and adjust retention times, mz limits and more for all peptide spectra at once and get through your data much faster than one spectra at a time.
Throughout the software robust statistics are relevantly applied for each sample-peptide-charge combination (replicate). In the deuterium uptake plots, p-value results from t-tests between samples are displayed above each time point. Non significant colors are automatically rendered onto heat map data in the sequence coverage and experiment comparison based on statistical tests. The data filter tool allows for the automated discarding/inclusion of peptide replicates based on statistical or fixed thresholds for intensity, score and retention time. This tool can be applied to selected or all peptides, and any combination of parameters is allowed. The peptide replicate will be discarded if it fails any of the tests and included if all tests are passed. Application of these filters allows for the quick identification and removal of outliers removing the need to curate them manually, so users can gain that next step in speed for rapid HDX data analysis.
View each peptide/charge separately with fine gradation heat map coloring and values for deuterium incorporation, error and charge. Customize font size, wrap number, bar height and view secondary structure features. View sample heat maps, differential heat maps, stacked heat maps or simple sequence coverage. Consolidate sample or differential data to single amide resolution using multiple established approaches that make sense. Non significant peptides can be colored grey using automated statistical tests.
Software improvements have greatly reduced the time it takes to complete data analysis of HDX data but there remains much room for improvement. The statistical filter tool allows for quick and automatic identification and removal of outliers. The bulk discard tool, native library access and ability to curate multiple peptide data simultaneously allows you to get through your data as fast as possible.
Improvements in the detection algorithm have produced more true positive identifications. The spectral view tools provide the means to understand and calculate centroids accurately so you can have confidence in your downstream results.
View your data from the raw spectra to sequence coverage heat maps and tabular views in a way that is relevant. Understand exactly how to get from averaged isotopic envelopes, to centroids, to individual peptides on sequence coverage maps, to residue calculated results in an easy to use interface.
Presentation is everything when trying to distill information from large data sets. Present your results in sequence coverage heat maps, residue consolidated heat maps across multiple differential experiments, color coded tables or onto a 3D protein structure. View your results in a way that makes sense.