KlaDB: a multi‑species database of protein Lysine Lactylation with benchmarking of prediction models

Abstract Lysine lactylation (Kla), a lactate-derived lysine post-translational modification (PTM), has emerged as an important mechanistic interface between cellular metabolism and gene regulation. Kla has been implicated in diverse biological processes, including tumorigenesis, immune regulation, inflammation, and plant growth and development. Advances in high-resolution mass spectrometry (MS)-based proteomics have led to the identification of a rapidly expanding number of Kla sites. However, a dedicated and comprehensive resource for lysine lactylation remains lacking. Here, we present KlaDB, a manually curated Lysine Lactylation Database comprising 64,072 experimentally identified Kla sites from nine species. KlaDB provides a user-friendly and interactive web interface that enables intuitive browsing, searching, and retrieval of site-level information for each Kla event. Based on the curated dataset, we further performed cross-species motif and background-corrected enrichment analyses, showing lysine-rich flanking regions and differences in local sequence patterns among the analysed datasets. In addition, we performed a systematic multi-species comparative evaluation of four published Kla-site prediction models under a standardized benchmarking framework. By consolidating experimentally identified Kla sites with standardized model benchmarking, KlaDB provides a valuable resource for the lactylation research community and will facilitate future studies on the biological functions and regulatory mechanisms of Kla. The database is publicly accessible at https://kladb.wuxl-group.com .

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Publication Details

Journal
BMC Bioinformatics
Published
2026-11-06
DOI
https://doi.org/10.1186/s12859-026-06736-1
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

KlaDB: a multi‑species database of protein Lysine Lactylation with benchmarking of prediction models

Cong Wang, Xiaolin Wu, Xuesong Liu, Guiyue Wu
6 links
BMC Bioinformatics
Advanced Proteomics Techniques and Applications
article

KlaDB: a multi‑species database of protein Lysine Lactylation with benchmarking of prediction models

Cong Wang, Xiaolin Wu, Xuesong Liu, Guiyue Wu
article en

Abstract

Abstract Lysine lactylation (Kla), a lactate-derived lysine post-translational modification (PTM), has emerged as an important mechanistic interface between cellular metabolism and gene regulation. Kla has been implicated in diverse biological processes, including tumorigenesis, immune regulation, inflammation, and plant growth and development. Advances in high-resolution mass spectrometry (MS)-based proteomics have led to the identification of a rapidly expanding number of Kla sites. However, a dedicated and comprehensive resource for lysine lactylation remains lacking. Here, we present KlaDB, a manually curated Lysine Lactylation Database comprising 64,072 experimentally identified Kla sites from nine species. KlaDB provides a user-friendly and interactive web interface that enables intuitive browsing, searching, and retrieval of site-level information for each Kla event. Based on the curated dataset, we further performed cross-species motif and background-corrected enrichment analyses, showing lysine-rich flanking regions and differences in local sequence patterns among the analysed datasets. In addition, we performed a systematic multi-species comparative evaluation of four published Kla-site prediction models under a standardized benchmarking framework. By consolidating experimentally identified Kla sites with standardized model benchmarking, KlaDB provides a valuable resource for the lactylation research community and will facilitate future studies on the biological functions and regulatory mechanisms of Kla. The database is publicly accessible at https://kladb.wuxl-group.com .

BMC Bioinformatics
Jiangsu University (CN), China Pharmaceutical University (CN), ShanghaiTech University (CN)
Jiangsu University
Openalex Percentile: Top 29%
Advanced Proteomics Techniques and Applications
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