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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Relationship between Protein Flexibility and Binding: Lessons for Structure-Based Drug Design.

Daniel Alvarez-Garcia1,2, Xavier Barril1,2,3

  • 1Departament de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona , Av. Joan XXIII s/n, 08028 Barcelona, Spain.

Journal of Chemical Theory and Computation
|November 19, 2015
PubMed
Summary
This summary is machine-generated.

Ignoring protein flexibility in drug discovery can lead to inaccurate binding free energy calculations. While rigid models offer practical advantages, considering protein dynamics is crucial for reliable results, especially in flexible regions.

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • The lock and key model of molecular recognition is outdated.
  • Current drug discovery often uses static receptor structures, neglecting protein dynamics.
  • Guidelines for incorporating protein flexibility are lacking.

Purpose of the Study:

  • Investigate the impact of protein flexibility on binding free energy.
  • Determine when and to what extent protein flexibility should be considered in computational studies.

Main Methods:

  • Molecular dynamics simulations of hen egg-white lysozyme (HEWL).
  • Used explicit solvent mixtures and varied restraint conditions.
  • Analyzed the effect of restricted mobility on binding hot spots.

Main Results:

  • Decreased protein mobility artifactually lowers binding free energies.
  • A logarithmic relationship exists between mobility and binding free energy, mitigating errors.
  • Errors are larger in flexible regions compared to rigid ones.

Conclusions:

  • Ignoring protein flexibility may be acceptable for rigid enzyme active sites.
  • Flexibility should be considered in other protein regions to avoid significant errors.
  • Local conformational sampling offers accurate predictions and practical advantages over full sampling.