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Implementation and evaluation of a docking-rescoring method using molecular footprint comparisons.

Trent E Balius1, Sudipto Mukherjee, Robert C Rizzo

  • 1Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794.

Journal of Computational Chemistry
|May 5, 2011
PubMed
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A new footprint similarity (FPS) scoring method improves ligand pose identification and enrichment in virtual screening. This method aids in discovering molecules with interaction patterns similar to known drugs or inhibitors for structure-based drug design.

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Molecular modeling

Background:

  • Structure-based drug design relies on accurate prediction of ligand-target interactions.
  • Existing scoring functions in molecular docking may have limitations in identifying biologically relevant poses.
  • Identifying ligands with specific interaction signatures, or footprints, is crucial for targeted drug discovery.

Purpose of the Study:

  • To develop and validate a novel docking-rescoring method, the footprint similarity (FPS) score, to identify ligands with interaction footprints similar to a biological reference.
  • To enhance the accuracy of ligand pose prediction and improve the efficiency of virtual screening in drug discovery.

Main Methods:

  • Developed a per-residue energy-based rescoring method (FPS) utilizing van der Waals (VDW), electrostatic (ES), and hydrogen bond (HB) energies.
Keywords:
Euclidean distancePearson correlationROC curvesdockingenrichmentmolecular fingerprintsmolecular footprintspose comparisonpose rescoringvirtual screening

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  • Implemented the FPS score within the DOCK program for molecular docking and virtual screening.
  • Validated the method through pose identification, crossdocking, enrichment tests, and virtual screening of large compound databases.

    • Main Results:

    • FPS scoring, particularly FPS(VDW+ES), demonstrated significant improvements in pose identification (6–12%) compared to standard DOCK scoring (DCE(VDW+ES)) on large datasets.
    • FPS achieved higher accuracy in ranking challenging crossdocking ensembles (45.4% or 70.9%) compared to DCE (17.8%).
    • Enrichment tests showed FPSVDW+ES scoring led to significant early enrichment in the top 10% of ranked databases, outperforming DCE by avoiding molecular weight bias.

    Conclusions:

    • The footprint similarity (FPS) score is an effective tool for improving ligand pose identification and virtual screening enrichment.
    • FPS provides a simple yet directed approach to rank ligand poses, aiding in the discovery of molecules with desired interaction profiles.
    • This method is anticipated to be a valuable addition to docking and structure-based design strategies for identifying novel drug candidates.