Proteomics

Dataset Information

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HigH-ratiO partiaL proteolysiS with carriER proteome (HOLSER) Enables Global Structure Profiling and Site-resolved Elucidation of Ligand-Protein Interactions


ABSTRACT: Understanding how cellular proteins interact with their environment, including endogenous and exogeneous molecules, is critical for elucidating mechanisms of cellular regulation and drug action. Partial proteolysis-based techniques offer peptide-level resolution of ligand-induced conformational changes but are limited by modest proteome coverage and depth, as well as sensitivity to the experimental conditions. To overcome these limitations, we developed higH ratiO partiaL proteolysiS with carriER proteome (HOLSER), an efficient workflow that features extended digestion time for low peptide yield variability and tandem mass tag (TMT)-based multiplexing that includes full digests for enhanced proteome depth and sequence coverage as well as higher precision of abundance measurements. We demonstrate HOLSER capabilities across diverse usage cases, including global proteome structure profiling, kinase target mapping, and structural mapping of the FKBP-mTOR complex in response to rapamycin. HOLSER reveals domain-specific stabilization and identifies peptides in direct contact with ligands, providing a powerful and scalable platform for simultaneous probing structural changes at the scale of the whole proteome, individual protein domains and specific binding sites.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Hela Cell

SUBMITTER: Massimiliano Gaetani  

LAB HEAD: Massimiliano Gaetani

PROVIDER: PXD069119 | Pride | 2026-06-08

REPOSITORIES: pride

Dataset's files

Source:
Action DRS
20250603_Super-PELSA_fra_.msf Msf
20250603_Super-PELSA_fra_01.raw Raw
20250603_Super-PELSA_fra_02.raw Raw
20250603_Super-PELSA_fra_03.raw Raw
20250603_Super-PELSA_fra_04.raw Raw
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Publications

Peptide-to-Protein Data Aggregation Using Fisher's Method Improves Target Identification in Chemical Proteomics.

Lyu Hezheng H   Gharibi Hassan H   Meng Zhaowei Z   Sokolova Bohdana B   Lundström Susanna S   Zhang Xuepei X   Zubarev Roman A RA  

Analytical chemistry 20260422 17


Protein-level statistical tests in proteomics, aimed at obtaining p-values, are conventionally made on protein abundances aggregated from peptide data. This integral approach overlooks peptide-level heterogeneity and ignores important information coded in individual peptide data, while protein p-values can also be obtained by Fisher's method of combining peptide p-values using chi-square statistics. Here, we test this latter approach across diverse chemical proteomics data sets based on assessme  ...[more]

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