AutoPELSA: An Automated Sample Preparation System for Proteome-Wide Identification of Target Proteins of Diverse Ligands

Protein-ligand interactions are fundamental to cellular function and drug discovery, and ligand-modification-free strategies have emerged as powerful tools for proteome-wide interrogation of these interactions. Among these, the peptide-centric local stability assay (PELSA) stands out for its high sensitivity. It uses a single digestion step to detect ligand-induced local stability shifts, enabling precise binding region localization and affinity estimation. However, manual PELSA workflows suffer from multiple labor-intensive steps that introduce variability and constrain throughput, limiting large-scale applications. To address these limitations, we developed AutoPELSA, an automated platform that streamlines the PELSA workflow including the limited proteolysis step and the following peptide separation step. AutoPELSA completes 96 samples in ∼4 h, enabling high-throughput analysis under native conditions. AutoPELSA reliably detected targets of both strong-affinity ligands (e.g., staurosporine, identifying 114 kinase targets) and low-affinity ligands, including α-ketoglutarate (30 known targets). Furthermore, a mixed-ligand dose-response strategy enabled simultaneous determination of binding affinities for multiple ligand-protein interaction regions in a single experiment. Overall, AutoPELSA provides a scalable and modification-free platform for proteome-wide identification and affinity profiling of ligand-protein interactions.

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Publication Details

Journal
Analytical Chemistry
Published
2026-06-29
DOI
https://doi.org/10.1021/acs.analchem.6c00180
Primary Topic
Click Chemistry and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

AutoPELSA: An Automated Sample Preparation System for Proteome-Wide Identification of Target Proteins of Diverse Ligands

Mingliang Ye, Jie Zhou, Haiqian Yang, Hao Zhu et al.
Analytical Chemistry
Click Chemistry and Applications
article

AutoPELSA: An Automated Sample Preparation System for Proteome-Wide Identification of Target Proteins of Diverse Ligands

Mingliang Ye, Jie Zhou, Haiqian Yang, Hao Zhu, Ruijun Tian, Weina Gao, Jinhua Shen, Lianji Xue, Xi Wang, Yan Wang
article en

Abstract

Protein-ligand interactions are fundamental to cellular function and drug discovery, and ligand-modification-free strategies have emerged as powerful tools for proteome-wide interrogation of these interactions. Among these, the peptide-centric local stability assay (PELSA) stands out for its high sensitivity. It uses a single digestion step to detect ligand-induced local stability shifts, enabling precise binding region localization and affinity estimation. However, manual PELSA workflows suffer from multiple labor-intensive steps that introduce variability and constrain throughput, limiting large-scale applications. To address these limitations, we developed AutoPELSA, an automated platform that streamlines the PELSA workflow including the limited proteolysis step and the following peptide separation step. AutoPELSA completes 96 samples in ∼4 h, enabling high-throughput analysis under native conditions. AutoPELSA reliably detected targets of both strong-affinity ligands (e.g., staurosporine, identifying 114 kinase targets) and low-affinity ligands, including α-ketoglutarate (30 known targets). Furthermore, a mixed-ligand dose-response strategy enabled simultaneous determination of binding affinities for multiple ligand-protein interaction regions in a single experiment. Overall, AutoPELSA provides a scalable and modification-free platform for proteome-wide identification and affinity profiling of ligand-protein interactions.

Analytical Chemistry
Dalian Institute of Chemical Physics (CN), Chinese Academy of Sciences (CN), National Medical Products Administration (CN), Shenzhen Bay Laboratory (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Dalian Institute of Chemical Physics, National Key Research and Development Program of China, Dalian Science and Technology Innovation Fund
Decent work and economic growth
Openalex Percentile: Top 13%
Click Chemistry and Applications
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