Effect of Water Networks On Ligand Binding: Computational Predictions vs Experiments

Area of Science:

• Computational chemistry
• Structural biology
• Biophysics

Background:

• Water molecules are crucial, yet often overlooked, in protein-ligand binding thermodynamics.
• Accurate prediction and experimental validation of water networks remain challenging for computational drug design.

Purpose of the Study:

• To investigate the thermodynamic impact of binding site water networks on protein-ligand interactions.
• To validate computational water network prediction methods using experimental data.

Main Methods:

• Utilized solvent isotope effects by comparing light (H2O) and heavy water (D2O) in isothermal titration calorimetry experiments.
• Studied trypsin-benzamidine and carbonic anhydrase II-sulfonamide systems.
• Employed WaterFLAP and MobyWat computational methods to predict water networks.

Main Results:

• Significant differences in binding enthalpies between H2O and D2O indicate a substantial role for water networks.
• Computational methods accurately predicted water positions, consistent with X-ray and neutron diffraction data.
• Predicted water network energetics corroborated experimental thermodynamics.

Conclusions:

• Binding site water networks play a significant thermodynamic role in protein-ligand binding.
• Computational tools like WaterFLAP and MobyWat are validated for predicting water networks.
• Considering water networks is essential for effective computational ligand design.