A docking score function for estimating ligand-protein interactions: application to acetylcholinesterase inhibition

Area of Science:

• Biochemistry
• Computational Chemistry
• Pharmacology

Background:

• Acetylcholinesterase (AChE) inhibition is crucial for addressing various health conditions.
• Understanding ligand-receptor interactions is key to developing effective AChE inhibitors.

Purpose of the Study:

• To develop a receptor-specific scoring function for predicting binding affinities of human AChE (huAChE) inhibitors.
• To identify key interactions contributing to ligand binding within huAChE.

Main Methods:

• Developed a statistically trained weighted sum scoring function based on electrostatic and van der Waals interactions.
• Validated the function using a training set of 53 ligands and a separate test set of 16 compounds.
• Performed cross-validation and analyzed residue contributions to binding.

Main Results:

• Achieved a strong correlation (R2 = 0.89) between computed and experimental inhibition constants in the training set.
• Demonstrated high predictive power with leave-one-out cross-validation (Q2 = 0.72).
• Obtained good correlation (R2 = 0.69) with experimental data on the independent test set.

Conclusions:

• The developed scoring function accurately predicts huAChE inhibitor binding affinities.
• Identified critical electrostatic and van der Waals interactions at specific receptor sites (active site, gorge, acyl pocket, peripheral site).
• Findings align with existing crystallographic and mutagenesis data, validating the scoring function's utility.