Group Competition Strategy for Covalent Ligand Discovery.

Area of Science:

• Chemoproteomics
• Chemical Biology
• Drug Discovery

Background:

• Activity-based protein profiling (ABPP) is crucial for covalent ligand discovery.
• Current ABPP methods indirectly assess ligand competition and lack head-to-head comparison.
• Directly comparing ligand binding preferences across the proteome is challenging.

Purpose of the Study:

• To develop a novel chemoproteomic strategy for direct, proteome-wide comparison of multiple ligand binding affinities.
• To establish a group competition-based activity-based protein profiling (GC-ABPP) method.
• To enable iterative selection of high-affinity covalent ligands for specific protein targets.

Main Methods:

• Developed a group competition-based ABPP (GC-ABPP) strategy using libraries of fully functionalized probes (FFPs).
• Simultaneously labeled proteomes with probe subgroups to enable direct competition and affinity metric calculation.
• Employed an iterative screening process with 65 FFPs to assess ligand-protein reactivity across >6000 cysteine sites.

Main Results:

• Successfully implemented GC-ABPP for direct, proteome-wide comparison of ligand binding.
• Identified high-affinity ligands targeting BCAT2 and UGDH after three rounds of screening.
• Demonstrated the capability to screen multiple ligands against multiple proteins simultaneously.

Conclusions:

• GC-ABPP provides a powerful paradigm for direct head-to-head comparison of covalent ligands.
• This method significantly advances covalent ligand and drug discovery.
• The strategy offers a scalable approach for identifying potent ligands against various protein targets.