Computational method to identify druggable binding sites that target protein-protein interactions.

Area of Science:

• Biochemistry
• Drug Discovery
• Computational Biology

Background:

• Protein-protein interactions (PPIs) are crucial in disease pathogenesis.
• Targeting PPIs for drug design is challenging due to difficulties in identifying druggable binding sites.
• Identifying these interfaces is key for developing small molecules that inhibit PPIs.

Purpose of the Study:

• To develop a ligand docking-based method, FindBindSite (FBS), for locating protein-protein interacting interface regions and druggable sites.
• To validate the effectiveness of FBS in identifying potential drug targets on protein interfaces.

Main Methods:

• Developed FindBindSite (FBS), a ligand docking-based method using small molecule libraries docked to protein structures.
• Clustered regions of high docked ligand density to identify PPI surfaces.
• Evaluated druggability based on ligand density and mapped PPI surfaces.

Main Results:

• High ligand density regions identified by FBS strongly correlate with known PPI surfaces.
• FBS achieved a 71% high-confidence and 93% lower-confidence hit rate for druggable sites on 41 proteins.
• The method successfully mapped 70% of PPI surfaces in 24 out of 41 structures, showing robustness to library variations.
• Experimentally determined hotspot residues clustered near FBS-identified druggable sites.

Conclusions:

• FindBindSite (FBS) is an effective computational tool for identifying druggable sites within protein-protein interaction interfaces.
• The method aids in rational drug design by pinpointing regions with high potential for interface disruption.
• FBS demonstrates significant potential for advancing the development of therapeutics targeting PPIs.