Related Experiment Video
Updated: Jul 6, 2026

10:37
Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Drugging the proteome via large-scale chemoproteomics
Yushu Li1, Jiaqi Wang1, Tiantian Wang1
1Center for Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, P.R. China.
Trends in Biochemical Sciences
|July 4, 2026
Summary
Many difficult-to-drug proteins, including intrinsically disordered proteins, can be targeted. Cellular protein-based strategies and chemoproteomics offer new opportunities for drug discovery against these challenging targets.
Area of Science:
- Biochemistry
- Drug Discovery
- Proteomics
Background:
- Genomic and proteomic initiatives have improved therapeutic target identification.
- Many proteins, especially intrinsically disordered proteins, are difficult to drug due to lack of structural information.
- Cellular context (modifications, interactions, aggregation) creates druggable states for these proteins.
Purpose of the Study:
- To review current strategies for targeting 'undruggable' proteins.
- To highlight the advantages of cellular protein-based approaches over traditional structure-based drug design.
- To introduce large-scale chemoproteomics for broad proteome targeting.
Main Methods:
- Review of structure-based drug design limitations.
- Discussion of cellular protein-based strategies.
- Highlighting large-scale chemoproteomics.
Main Results:
- Structure-based drug design has limitations for certain protein classes.
- Cellular context provides unique opportunities for ligand identification.
- Chemoproteomics enables targeting of a wider range of proteins.
Conclusions:
- Targeting 'undruggable' proteins is feasible through understanding their cellular states.
- Cellular and chemoproteomics approaches offer promising avenues for novel drug discovery.
- Expanding drug discovery beyond traditional structure-based methods is crucial.
