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Updated: Jun 30, 2026

Automated Sample Multiplexing by using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT)
Published on: December 18, 2020
AutoPELSA: An Automated Sample Preparation System for Proteome-Wide Identification of Target Proteins of Diverse
Lianji Xue1,2, Xi Wang3, Haiqian Yang1,2
1State Key Laboratory of Medical Proteomics, CAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R&A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian 116023, China.
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.

