Global Protein-Ligand Binding Affinity Profiling via Photocatalytic Labeling

Area of Science:

• Biochemistry and Molecular Biology
• Chemical Biology
• Proteomics

Background:

• Protein-ligand interactions are crucial for drug action and cellular signaling.
• Current methods for identifying interactions and measuring binding affinity 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 simultaneous protein target identification and quantitative binding affinity profiling.
• To overcome the limitations of existing methods in terms of scope and throughput.
• To enable the study of protein-ligand interactions in native biological environments.

Main Methods:

• Development of the Affinity Map platform, integrating competitive binding analysis, photocatalytic labeling, and high-throughput proteomics.
• Application of the platform to diverse ligand classes including small molecules, peptides, and proteins.
• Validation of the method using cell lysates, organ extracts, and live cell surfaces.

Main Results:

• Demonstrated the capability of Affinity Map for global quantitative binding affinity profiling.
• Showcased the platform's applicability across a wide range of ligand types (small molecules, linear peptides, cyclic peptides, proteins).
• Successfully measured binding affinities between unmodified ligands and proteins in complex biological matrices.

Conclusions:

• Affinity Map provides a generalizable and high-throughput approach for comprehensive protein-ligand interaction analysis.
• The platform enables accurate measurement of binding affinities in native cellular contexts, advancing drug discovery and biological research.
• This technology significantly expands the toolkit for characterizing molecular interactions in complex biological systems.