PELSA-Decipher: A Software Tool for the Processing and Interpretation of Ligand–Protein Interaction Data Sets Acquired by PELSA
Understanding protein-ligand interactions is fundamental to life sciences, including the elucidation of drug action mechanisms and regulatory processes in cellular metabolism and signaling. Recently, a robust ligand modification-free method, termed peptide-centric local stability assay (PELSA), has been developed to identify the protein targets and binding regions of diverse ligands at the proteome scale. This method has unprecedented sensitivity and can be broadly applied to ligands such as drugs, metabolites, metal ions, antibodies, and others. However, extracting key information on ligand-protein interactions, including the binding proteins, binding sites, and binding affinities, is a nontrivial task, which has limited the widespread adoption of the PELSA strategy by the research community. To address this, we developed a software tool, PELSA-Decipher, to facilitate the efficient processing of data sets obtained in the PELSA experiment, including raw data processing, result visualization, and the generation of reports and high-quality images, thereby greatly promoting the broader applications of the PELSA strategy. The PELSA-Decipher software can be downloaded free of charge from the Web site https://github.com/DICP-1809/PELSA-Decipher.
Authors
- Mingliang Ye (ORCID: https://orcid.org/0000-0002-5872-9326)
- Kejia Li (ORCID: https://orcid.org/0000-0001-9989-2069)
- Xue Li (ORCID: https://orcid.org/0000-0001-9793-8844)
- Zheng Fang (ORCID: https://orcid.org/0000-0002-3767-6341)
- Jiahua Zhou (ORCID: https://orcid.org/0000-0002-7664-7148)
- Haiyang Zhu
- Keyun Wang
Institutions
- Dalian Institute of Chemical Physics (CN)
- Chinese Academy of Sciences (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2025-08-14
- DOI
- https://doi.org/10.1021/acs.jproteome.5c00365
- Citations
- 3
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 4.51