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Ligand Strain Energy in Large Library Docking.

Shuo Gu1, Matthew S Smith1,2, Ying Yang1

  • 1Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 Fourth Street, San Francisco, California 94143-2550, United States.

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|September 1, 2021
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This study introduces a fast method to calculate small molecule strain energy using torsional populations. Incorporating strain energy into molecular docking significantly improves the identification of true drug ligands by down-ranking strained decoys.

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Area of Science:

  • Computational Chemistry
  • Structural Biology
  • Drug Discovery

Background:

  • Small molecule internal strain is critical for molecular docking accuracy.
  • Evaluating ligand scores based on strain energy has been a persistent challenge.

Purpose of the Study:

  • To develop and validate a rapid method for calculating strain energies.
  • To assess the impact of strain energy inclusion on molecular docking performance.

Main Methods:

  • Utilized relative torsional populations from the Cambridge Structural Database to calculate strain.
  • Applied the method to retrospective docking screens (dopamine D4 receptor, AmpC β-lactamase) and a DUD-E benchmark subset.
  • Investigated strain energy thresholds for distinguishing ligands from decoys.

Main Results:

  • Improved hit rates in experimental validation by down-ranking strained decoy molecules.
  • Identified effective strain energy thresholds for ligand-decoy discrimination.
  • Achieved up to 75% improved enrichment across benchmark targets after strain filtering.

Conclusions:

  • The developed strain energy calculation method is rapid and effective for enhancing molecular docking.
  • This approach is pragmatic for large-scale virtual screening and compatible with various docking methods.
  • The method is openly available and facilitates more accurate drug discovery pipelines.