DigDig: A Software for In-Depth Analysis and Comparison of Proteolytic Digestion

Proteolysis is a crucial step in both bottom-up and structural proteomics workflows, directly influencing peptide identification and sequence coverage in mass spectrometry-based analyses. While classical proteomics typically relies on highly specific enzymes with well-defined cleavage patterns, structural MS approaches such as hydrogen/deuterium exchange mass spectrometry (HDX-MS) often employ nonspecific or semispecific proteases, producing complex peptide mixtures that require more detailed digestion analysis. To address these needs and streamline the entire process, we developed DigDig, a standalone, Java-based software tool for evaluating and comparing proteolytic digestion across diverse experimental conditions. DigDig processes output files from common search engines and provides customizable visualizations of key digestion metrics, including sequence coverage, reproducibility, peptide redundancy, cleavage site preferences, and peptide length distributions. A distinguishing feature is its ability to detect and report repetitive peptide sequences, which are frequently missed by standard tools. We demonstrate its capabilities using data sets from both specific and nonspecific digestions, highlighting its utility in digestion quality control, protease characterization, and method development, particularly in HDX-MS workflows. DigDig is freely available at https://peterslab.org/DigDig/.

Authors

Institutions

Publication Details

Journal
Analytical Chemistry
Published
2025-09-25
DOI
https://doi.org/10.1021/acs.analchem.5c04217
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DigDig: A Software for In-Depth Analysis and Comparison of Proteolytic Digestion

Daniel Kavan, Z. Kalaninová, Petr Novák, Petr Man et al.
Analytical Chemistry
Advanced Proteomics Techniques and Applications
article

DigDig: A Software for In-Depth Analysis and Comparison of Proteolytic Digestion

Daniel Kavan, Z. Kalaninová, Petr Novák, Petr Man, Jasmína Mária Portašiková
article en

Abstract

Proteolysis is a crucial step in both bottom-up and structural proteomics workflows, directly influencing peptide identification and sequence coverage in mass spectrometry-based analyses. While classical proteomics typically relies on highly specific enzymes with well-defined cleavage patterns, structural MS approaches such as hydrogen/deuterium exchange mass spectrometry (HDX-MS) often employ nonspecific or semispecific proteases, producing complex peptide mixtures that require more detailed digestion analysis. To address these needs and streamline the entire process, we developed DigDig, a standalone, Java-based software tool for evaluating and comparing proteolytic digestion across diverse experimental conditions. DigDig processes output files from common search engines and provides customizable visualizations of key digestion metrics, including sequence coverage, reproducibility, peptide redundancy, cleavage site preferences, and peptide length distributions. A distinguishing feature is its ability to detect and report repetitive peptide sequences, which are frequently missed by standard tools. We demonstrate its capabilities using data sets from both specific and nonspecific digestions, highlighting its utility in digestion quality control, protease characterization, and method development, particularly in HDX-MS workflows. DigDig is freely available at https://peterslab.org/DigDig/.

Analytical ChemistryVol. 97(39)
Charles University (CZ), Institute of Microbiology (BY)
Openalex Percentile: Top 75%
Advanced Proteomics Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.