Aim: The aim of the study was to develop a method for use in computer-aided drug design.
Background: Predicting the structure of enzyme-ligand binding mode is essential for understanding the properties, functions, and mechanisms of the bio-complex, but is rather difficult due to the enormous sampling space involved.
Objective: The objective was to conduct accurate prediction of enzyme-ligand binding mode conformation.
Methods: A new computational protocol, MDO, is proposed for finding the structure of the ligand binding pose. MDO consists of sampling enzyme sidechain conformations via molecular dynamics simulation of the enzyme-ligand system and clustering of the enzyme configurations, sampling ligand binding poses via molecular docking and clustering of the ligand conformations, and the optimal ligand binding pose prediction via geometry optimization and ranking by the ONIOM method. MDO is tested on 15 enzyme-ligand complexes with known accurate structures.
Results: The success rate of MDO predictions, with RMSD < 2 Å, is 67%, substantially higher than the 40% success rate of conventional methods. The MDO success rate can be increased to 83% if the ONIOM calculations are applied only for the starting poses with ligands inside the binding cavities.
Conclusion: The MDO protocol provides high-quality enzyme-ligand binding mode prediction with reasonable computational cost. The MDO protocol is recommended for use in the structurebased drug design.
Keywords: Molecular dynamics, molecular docking, clustering analysis, binding pose prediction, structure-based drug design