Knowledge Base

GlideScore/Docking Score doesn't correlate with my known activities. What is wrong?

Glide is primarily concerned with generating an accurate pose for each protein-ligand complex and separating ligands with appreciable binding affinity (generally <10uM) from those that don't bind, in a ranked list. Extensive testing, both in-house and by third parties, has shown that Glide is very effective at pose prediction and enriching hit lists in active compounds.

The task of accurately estimating protein-ligand binding affinities remains beyond the capabilities of docking scoring functions. The rigid receptor approximation, limited estimate of the entropy gain or loss upon binding, and other approximations in GlideScore and all other empirical scoring functions omit essential thermodynamics of the free energy of binding. Thus, approaches other than correlation with GlideScore should be applied to predict relative or absolute binding affinities.

  • For congeneric series, where a set of ligands share a common structure, free energy perturbation with FEP+ has been demonstrated to reliably produce binding affinity predictions with approximately 1 kcal/mol accuracy.
  • End-point approaches have demonstrated in some cases the ability to yield reasonable correlations with experimental binding affinities. Prime MM-GBSA was designed to process output from Glide and returns relative free energy estimates of binding using a Generalized Born solvation model.
  • QSAR-based approaches using 3D information from aligned ligand poses in the binding pocket (such as Field-Based QSAR) are sometimes able to identify and explain correlations with experimental binding affinities.
  • Finally, with a set of actives and compounds that don't bind it may be possible to create your own scoring function by fitting a model to experimental binding affinities using AutoQSAR.

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