Predicting the bioactive conformations of macrocycles: a molecular dynamics-based docking procedure with DynaDock

Area of Science:

• Computational chemistry
• Drug discovery
• Molecular modeling

Background:

• Macrocyclic compounds are emerging as therapeutics, particularly for inhibiting protein-protein interactions.
• Accurate prediction of macrocycle binding modes is crucial for drug design.
• Standard docking methods struggle with the conformational flexibility of macrocycles.

Purpose of the Study:

• To develop an efficient molecular dynamics-based docking protocol for macrocycles.
• To address the challenge of sampling macrocycle ring conformations.
• To improve the accuracy of predicting macrocycle binding modes.

Main Methods:

• A molecular dynamics-based docking protocol was designed.
• Conventional molecular dynamics simulations (750 ns) at 370 K were used for sampling.
• Flexible docking with the DynaDock approach utilized pre-sampled conformations.
• Molecular dynamics-based complex stability estimations were employed for pose selection.

Main Results:

• The protocol achieved highly accurate poses with ligand RMSD values below 1.8 Å.
• Efficient sampling of macrocycle conformations was successfully addressed.
• Molecular dynamics-based stability estimations proved valuable for pose selection.

Conclusions:

• The developed molecular dynamics-based docking protocol enhances the prediction of macrocycle binding modes.
• This method offers a significant improvement for computational drug design involving macrocycles.
• Combining stability and binding free energy estimations can further refine pose assessment in blind docking studies.