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Dynamic Undocking: A Novel Method for Structure-Based Drug Discovery.

Maciej Majewski1, Sergio Ruiz-Carmona1, Xavier Barril2,3

  • 1Institut de Biomedicina de la Universitat de Barcelona (IBUB) and Facultat de Farmàcia , Universitat de Barcelona, Barcelona, Spain.

Methods in Molecular Biology (Clifton, N.J.)
|July 25, 2018
PubMed
Summary
This summary is machine-generated.

We developed dynamic undocking (DUck), a novel computational method for drug discovery. DUck assesses ligand-receptor complex stability by measuring the work to break key interactions, aiding virtual screening and drug design.

Keywords:
Drug discoveryHydrogen bondsMolecular dockingMolecular dynamicsStructural stabilityStructure-based drug designVirtual screening

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Structural biology

Background:

  • Computer-aided drug design (CADD) commonly uses binding affinity predictions.
  • Existing CADD methods often rely on approximate thermodynamic properties.
  • There is a need for complementary methods in virtual screening.

Purpose of the Study:

  • To introduce dynamic undocking (DUck), a novel computational method for evaluating ligand-receptor complex stability.
  • To present a protocol for applying DUck in drug design strategies.
  • To provide guidance for common user challenges with DUck.

Main Methods:

  • Developed dynamic undocking (DUck), a fast computational method.
  • DUck calculates the work required to disrupt critical native contacts (e.g., hydrogen bonds) in a ligand-receptor complex.
  • Evaluates structural stability as a measure of interaction strength.

Main Results:

  • DUck effectively distinguishes true ligands from decoys based on complex stability.
  • The method provides a property orthogonal to traditional docking approaches.
  • DUck is highly useful for enhancing virtual screening efficiency.

Conclusions:

  • Dynamic undocking (DUck) offers a complementary and effective approach to traditional CADD methods.
  • DUck's focus on structural stability provides valuable insights for drug design.
  • The method shows promise for improving the accuracy and efficiency of virtual screening processes.