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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Performance evaluation of flexible macrocycle docking in AutoDock.

Matthew Holcomb1, Diogo Santos-Martins1, Andreas F Tillack1

  • 1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.

QRB Discovery
|August 2, 2023
PubMed
Summary
This summary is machine-generated.

This study validates a flexible macrocycle docking method for drug design. The approach accurately predicts macrocycle conformations, improving ligand preparation pipelines like Meeko.

Keywords:
autodockdockingmacrocycles

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Area of Science:

  • Computational chemistry
  • Medicinal chemistry
  • Drug discovery

Background:

  • Macrocycles are crucial ligands in natural products and drug design.
  • Macrocyclization can stabilize specific ligand conformations and enhance cell permeability.
  • Flexible modeling of macrocyclic ligands is computationally challenging.

Purpose of the Study:

  • To evaluate the performance of a flexible macrocycle docking method.
  • To assess the accuracy of AutoDock-GPU and Vina for macrocyclic compounds.
  • To validate the Meeko ligand preparation pipeline for macrocycles.

Main Methods:

  • A pseudoatom approach was used to model macrocyclic ring geometry and closure forces.
  • The method was tested on diverse small molecule and peptide macrocycles (7- to 33-membered rings).
  • Performance was compared to rigid redocking of X-ray conformers.

Main Results:

  • The flexible docking method showed minimal accuracy loss compared to rigid redocking.
  • The approach effectively handles macrocyclic compounds in docking simulations.
  • Accurate prediction of macrocycle conformation was achieved.

Conclusions:

  • The validated method enables flexible modeling of macrocyclic ligands.
  • This approach is suitable for conformationally flexible macrocycles with unknown binding modes.
  • Meeko's default macrocycle preparation is effective for drug design.