Robust identification of binding hot spots using continuum electrostatics: application to hen egg-white lysozyme

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Protein binding hot spots are crucial for molecular interactions.
• Experimental methods like X-ray crystallography and NMR spectroscopy are used to identify these sites.
• Computational approaches are needed for efficient and comprehensive hot spot identification.

Purpose of the Study:

• To introduce FTMap, a computational tool for identifying protein binding hot spots.
• To evaluate FTMap's performance on hen egg-white lysozyme (HEWL) with known binding site characteristics.
• To compare FTMap's predictions with experimental data and other computational methods.

Main Methods:

• FTMap utilizes 16 probe molecules for global protein surface sampling on a dense grid.
• Energy evaluation employs a fast Fourier transform correlation approach with an empirical energy function.
• Off-grid minimization refines identified hot spots using a detailed energy expression.

Main Results:

• FTMap successfully identified the primary hot spot (site C) in all nine HEWL structures.
• Secondary hot spots (sites B and D), important for substrate binding, were also detected.
• Predicted interactions correlated well with experimental data from HEWL-ligand complexes and NMR studies.

Conclusions:

• FTMap accurately identifies known binding hot spots on HEWL.
• The method provides more complete binding site information compared to previous computational approaches.
• FTMap offers a promising tool for drug discovery by predicting binding sites with high accuracy and fewer false positives.