Title:MDO: A Computational Protocol for Prediction of Flexible Enzyme-ligand
Binding Mode
Volume: 18
Issue: 6
Author(s): Amar Y. Al-Ansi and Zijing Lin*
Affiliation:
- Hefei National Laboratory for Physical Sciences at Microscale & CAS Key Laboratory of Strongly-coupled Quantum
Matter Physics, Department of Physics, University of Science and Technology of China, Hefei 230026, China
Keywords:
Molecular dynamics, molecular docking, clustering analysis, binding pose prediction, structure-based drug design, molecule.
Abstract:
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.
