The Deuterium Calculator: An Open-Source Tool for Hydrogen-Deuterium Exchange Mass Spectrometry Analysis

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is a powerful protein footprinting technique to study protein dynamics and binding; however, HDX-MS data analysis is often challenging and time-consuming. Moreover, the HDX community is expanding to investigate multiprotein and highly complex protein systems which further complicates data analysis. Thus, a simple, open-source software package designed to analyze large and highly complex protein systems is needed. In this vein, we have developed The Deuterium Calculator, a Python-based software package for HDX-MS data analysis. The Deuterium Calculator is capable of differential and nondifferential HDX-MS analysis, produces standardized data files according to recommendations from the International Conference on Hydrogen-Exchange Mass Spectrometry (IC-HDX) to increase transparency in data analysis, and generates Woods' plots for statistical analysis and data visualization. This standard output can be used to perform time dependent deuteration studies and for the study of protein folding kinetics or differential uptake. Moreover, The Deuterium Calculator is capable of performing these analyses on large HDX-MS data sets (e.g., LC-HDX-MS from cell lysate digest). The Deuterium Calculator is freely available for download at https://github. com/OUWuLab/TheDeuteriumCalculator.git. Data are available via ProteomeXchange with identifier PXD036813.

Automated summary

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is a powerful technique to study protein dynamics and binding, but its data analysis can be challenging and time-consuming. Therefore, there is a need for a simple, open-source software package to analyze large and highly complex protein systems. In this regard, The Deuterium Calculator, a Python-based software package for HDX-MS data analysis, has been developed. It allows for differential and nondifferential HDX-MS analysis, generates standardized data files for increased transparency, and provides statistical analysis and data visualization through Woods' plots.