Analysis of protein binding sites by computational solvent mapping.

Area of Science:

• Computational biology
• Structural biology
• Drug discovery

Background:

• Protein binding sites are crucial for molecular interactions and drug development.
• Experimental methods like X-ray and NMR screening reveal that protein binding sites accommodate various small molecules.
• Computational solvent mapping offers a way to explore these binding sites globally.

Purpose of the Study:

• To develop and validate a computational method for identifying potentially favorable ligand-binding positions on protein surfaces.
• To assess the accuracy of the method in reproducing experimental mapping results.
• To identify "druggable" sites on proteins with high potential for therapeutic ligand binding.

Main Methods:

• Developed the FTMap algorithm, a multistage mapping approach utilizing fast Fourier transform (FFT) correlation.
• Employed molecular probes (small molecules or functional groups) to systematically sample protein surfaces.
• Focused on identifying low free energy regions rather than specific low-energy conformations.

Main Results:

• FTMap successfully reproduces available experimental solvent mapping results.
• Molecular probes consistently cluster in important subsites within protein binding sites.
• Amino acid residues interacting with multiple probes correlate with specific ligand binding sites.

Conclusions:

• The "consensus" sites identified by probe clustering are likely "druggable" and can bind drug-sized ligands with high affinity.
• FTMap is a sensitive tool for comparing binding sites across different protein structures, including conformational changes.
• The method aids in understanding protein-ligand interactions and facilitates drug design.