HDXBoxeR: an R package for statistical analysis and visualization of multiple Hydrogen-Deuterium Exchange Mass-Spectrometry datasets of different protein states.

SUMMARY: Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) is a powerful protein characterization technique that provides insights into protein dynamics and flexibility at the peptide level. However, analyzing HDX-MS data presents a significant challenge due to the wealth of information it generates. Each experiment produces data for hundreds of peptides, often measured in triplicate across multiple time points. Comparisons between different protein states create distinct datasets containing thousands of peptides that require matching, rigorous statistical evaluation, and visualization. Our open-source R package, HDXBoxeR, is a comprehensive tool designed to facilitate statistical analysis and comparison of multiple sets among samples and time points for different protein states, along with data visualization. AVAILABILITY AND IMPLEMENTATION: HDXBoxeR is accessible as the R package (https://cran.r-project.org/web//packages/HDXBoxeR) and GitHub: mkajano/HDXBoxeR.

High-Performance Workflow for Identifying Site-Specific Crosslinks Originating from a Genetically Incorporated, Photoreactive Amino Acid.

In conventional crosslinking mass spectrometry, proteins are crosslinked using a highly selective, bifunctional chemical reagent, which limits crosslinks to residues that are accessible and reactive to the reagent. Genetically incorporating a photoreactive amino acid offers two key advantages: any site can be targeted, including those that are inaccessible to conventional crosslinking reagents, and photoreactive amino acids can potentially react with a broad range of interaction partners. However, broad reactivity imposes additional challenges for crosslink identification. In this study, we incorporate benzoylphenylalanine (BPA), a photoreactive amino acid, at selected sites in an intrinsically disordered region of the human protein HSPB5. We report and characterize a workflow for identifying and visualizing residue-level interactions originating from BPA. We routinely identify 30 to 300 crosslinked peptide spectral matches with this workflow, which is up to ten times more than existing tools for residue-level BPA crosslink identification. Most identified crosslinks are assigned to a precision of one or two residues, which is supported by a high degree of overlap between replicate analyses. Based on these results, we anticipate that this workflow will support the more general use of genetically incorporated, photoreactive amino acids for characterizing the structures of proteins that have resisted high-resolution characterization.