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A Protocol for Computer-Based Protein Structure and Function Prediction
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Enabling structure-based drug discovery utilizing predicted models.

Edward B Miller1, Howook Hwang1, Mee Shelley2

  • 1Schrödinger New York, 1540 Broadway, 24th Floor, New York, NY 10036, USA.

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|February 2, 2024
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Summary
This summary is machine-generated.

High-quality predicted protein structures, when combined with free energy perturbation (FEP) calculations, can reliably guide drug design. This approach was demonstrated using structure-based modeling of hERG inhibition for drug discovery.

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Accurate protein structures are crucial for structure-based drug design.
  • Existing methods face challenges in reliably utilizing predicted structures.

Purpose of the Study:

  • To demonstrate the utility of free energy perturbation (FEP) with predicted protein structures for drug design.
  • To validate FEP's capability in achieving drug design goals using computational modeling.

Main Methods:

  • Utilized predicted protein structures as input for molecular modeling.
  • Applied free energy perturbation (FEP) calculations to assess binding affinities.
  • Focused on structure-based modeling of hERG channel inhibition.

Main Results:

  • High-quality predicted structures can be confidently used with FEP for drug design.
  • FEP successfully guided structure-based modeling of hERG inhibition.
  • Demonstrated the value of FEP in drug discovery programs.

Conclusions:

  • Free energy perturbation (FEP) enhances the value of predicted structures in drug discovery.
  • Structure-based modeling combined with FEP offers a reliable approach for achieving drug design objectives.
  • This methodology supports the expanding use of computational approaches in pharmaceutical research.