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Updated: Jul 19, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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A critical assessment of docking programs and scoring functions.

Gregory L Warren1, C Webster Andrews, Anna-Maria Capelli

  • 1GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, USA. Gregory.L.Warren@gsk.com

Journal of Medicinal Chemistry
|September 29, 2006
PubMed
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Computational docking programs can predict how molecules bind to proteins, but scoring functions struggle to rank them accurately. No current method reliably predicts binding affinity for drug discovery.

Area of Science:

  • Computational chemistry
  • Molecular modeling
  • Drug discovery

Background:

  • Molecular docking is crucial for predicting small molecule conformations within protein binding sites.
  • Scoring functions evaluate these conformations to determine the best fit.
  • Accurate docking and scoring are vital for identifying and optimizing drug candidates.

Purpose of the Study:

  • To evaluate the performance of 10 docking programs and 37 scoring functions.
  • To assess their effectiveness in binding mode prediction, virtual screening, and affinity prediction.
  • To determine their utility across diverse protein targets.

Main Methods:

  • Tested 10 docking programs and 37 scoring functions against eight proteins from seven types.
  • Evaluated performance on three tasks: binding mode prediction, virtual screening, and affinity ranking.

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  • Compared docked poses against crystallographically determined structures.

    • Main Results:

    • Docking programs generated accurate ligand conformations for some targets.
    • Scoring functions showed limited success in identifying correct binding poses.
    • No single docking program excelled across all tested proteins.
    • Active compounds were identified in virtual screening, but performance varied.
    • No method accurately predicted ligand binding affinity.

    Conclusions:

    • Current docking programs show promise in pose generation but lack universal applicability.
    • Scoring functions require improvement for reliable binding mode and affinity prediction.
    • Further development is needed to enhance the accuracy and consistency of docking and scoring methods in drug discovery.