Global protein-ligand binding affinity profiling via photocatalytic labeling

Area of Science:

• Biochemistry
• Proteomics
• Chemical Biology

Background:

• Protein-ligand interactions are crucial for drug action and cellular signaling.
• Current methods for identifying and quantifying these interactions are often indirect, low-throughput, or limited to specific protein classes.
• Simultaneous target identification and affinity measurement remain a significant challenge in chemical biology.

Purpose of the Study:

• To develop a generalizable platform for global quantitative binding affinity profiling.
• To enable simultaneous target identification and biophysical affinity measurement for diverse ligand types.
• To overcome limitations of existing methods in measuring interactions within native biological environments.

Main Methods:

• Competitive binding analysis coupled with high-fidelity photocatalytic labeling.
• High-throughput proteomics for global quantitative binding affinity profiling.
• Application of the Affinity Map platform to cell lysates, organ extracts, and live cell surfaces.

Main Results:

• Demonstrated the applicability of Affinity Map to major ligand classes: small molecules, linear peptides, cyclic peptides, and proteins.
• Successfully measured binding affinities between unmodified ligands and proteins in complex biological matrices.
• Established a robust method for comprehensive analysis of protein-ligand interactions.

Conclusions:

• Affinity Map provides a versatile and generalizable platform for quantitative binding affinity profiling.
• The method facilitates the study of protein-ligand interactions across diverse biological contexts and ligand types.
• This approach advances the understanding of molecular interactions in drug discovery and cell biology.