Quantitative mapping of binding specificity landscapes for homologous targets by using a high-throughput method

Area of Science:

• Biochemistry
• Molecular Biology
• Structural Biology

Background:

• Protein-protein interactions (PPIs) are crucial for cellular functions.
• Understanding PPIs is essential for drug discovery and development.
• Current methods for mapping PPIs have limitations in quantitative analysis.

Purpose of the Study:

• To develop a novel platform for quantitative mapping of protein binding specificity landscapes.
• To generate accurate models predicting affinity and specificity for mutations within protein complexes.
• To facilitate the rational design of specific inhibitors for target proteins.

Main Methods:

• Multi-target screening of mutagenesis libraries.
• High- and low-affinity population selection.
• Next-generation sequencing analysis.
• Quantitative modeling of binding affinity and specificity.
• Experimental validation using purified proteins.

Main Results:

• Mapped quantitative landscapes for interactions between N-TIMP2 and MMPs (MMP-1, MMP-3, MMP-14).
• Identified optimized and non-optimized PPIs based on mutation effects.
• Detected hot-spot and cold-spot residues, as well as specificity-switch mutations.
• Demonstrated the platform's ability to predict mutation impacts on affinity and specificity.

Conclusions:

• The novel platform provides unprecedented quantitative analysis of binding specificity landscapes.
• This methodology enhances understanding of PPI mechanisms and evolutionary origins.
• Facilitates rational design of inhibitors for structurally similar proteins.