ArticleJournal of proteome research2026
DigestedProteinDB: A Compact and Scalable Key-Value Database for In Silico Peptide Digestion and Mass-Based Search.
Article in Journal of proteome research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Efficient comparison of experimental peptide masses with theoretical values is a central step in mass spectrometry (MS)-based proteomics, microbial biotyping, and MS imaging. Such analyses increasingly require fast and scalable access to large collections of in silico-digested peptides derived from large-scale and continuously evolving protein-sequence databases. Here, we present DigestedProteinDB, a compact and high-performance key-value database of peptides generated by enzymatic in silico digestion of UniProtKB/Swiss-Prot and TrEMBL sequences. Implemented using RocksDB, the system incorporates multiple optimization layers, such as peptide mass discretization and multistage storage compression, to minimize disk footprint and accelerate mass-range queries. In benchmark tests using 252 million UniProtKB protein sequences (5.9 billion peptides, trypsin; 6-50 aa; two missed cleavages), DigestedProteinDB required approximately 250 GB of disk space and operated within 16 GB of system RAM. Database construction required ∼2 days, and end-to-end mass-range queries (±0.1 Da) achieved a median latency of ∼7 ms per query across a batch of 10,000 randomly sampled queries. The resulting database can be used as a standalone local resource or integrated into bioinformatics pipelines for peptide mass fingerprinting (PMF), MS/MS-based protein identification, and microbial biotyping. Due to its modular design, new databases can be generated rapidly for different proteases, taxonomic subsets, or digestion parameters.
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