• Corpus ID: 253018409

Enrichment Score: a better quantitative metric for evaluating the enrichment capacity of molecular docking models

@inproceedings{Knight2022EnrichmentSA,
  title={Enrichment Score: a better quantitative metric for evaluating the enrichment capacity of molecular docking models},
  author={Ian Scott Knight and Slava Naprienko and John J. Irwin},
  year={2022}
}
The standard quantitative metric for evaluating enrichment capacity known as LogAUC depends on a cutoff parameter that controls what the minimum value of the log-scaled x-axis is. Unless this parameter is chosen carefully for a given ROC curve, one of the two following problems occurs: either (1) some fraction of the first interdecoy intervals of the ROC curve are simply thrown away and do not contribute to the metric at all, or (2) the very first inter-decoy interval contributes too much to the… 
[PDF] Semantic Reader

Figures from this paper

References

SHOWING 1-10 OF 22 REFERENCES

Community benchmarks for virtual screening

  • J. Irwin
  • Chemistry
    J. Comput. Aided Mol. Des.
  • 2008
Several ways that DUD can be improved to provide better telemetry to investigators seeking to understand both the strengths and the weaknesses of current docking methods are outlined.

Evaluating Virtual Screening Methods: Good and Bad Metrics for the "Early Recognition" Problem

This work formally generalizes the ROC metric to the early recognition problem and proposes a novel metric called Boltzmann-enhanced discrimination of receiver operating characteristic that turns out to contain the discrimination power of the RIE metric but incorporates the statistical significance from ROC and its well-behaved boundaries.

A Discussion of Measures of Enrichment in Virtual Screening: Comparing the Information Content of Descriptors with Increasing Levels of Sophistication

Surprisingly, structure-unaware atom count vectors as descriptors in combination with the Euclidean distance measure are able to achieve "enrichment factors" over random selection of around 4 (depending on the particular class of active compounds), putting the enrichment factors reported for more sophisticated virtual screening methods in a different light.

Scoring functions for protein-ligand docking.

Virtual screening by molecular docking has become established as a method for drug lead discovery and optimization and in many cases, performance is good enough to yield high enrichments of true ligands versus non-ligands in screening across a wide variety of protein types.

Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking

An improved benchmarking set that includes more diverse targets such as GPCRs and ion channels, totaling 102 proteins with 22886 clustered ligands drawn from ChEMBL, each with 50 property-matched decoys drawn from ZINC, is described.

On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors

Four of the most well-known, commercially available docking programs, FlexX, GOLD, GLIDE, and ICM, have been examined for their ligand-docking and virtual-screening capabilities and the capability of the four programs to correctly rank-order target-specific active compounds over alternative binders and nonbinders and thereby enrich a small subset of a screening library is compared.

Property-Unmatched Decoys in Docking Benchmarks

An optimized version of the DUD-E set (DUDE-Z), as well as Extrema and sets representing broad features of the library (Goldilocks), is developed here, and the variability that one can encounter in enrichment calculations is explored.

Improving Docking-Based Virtual Screening Ability by Integrating Multiple Energy Auxiliary Terms from Molecular Docking Scoring

EAT-Score model can capture important binding pattern information from protein-ligand complexes by Shapley additive explanations (SHAP) analysis, which may be very helpful in interpreting the ligand binding mechanism for a certain target and thereby guiding drug design.

A practical guide to large-scale docking.

Best practices and control docking calculations that help evaluate docking parameters for a given target prior to undertaking a large-scale prospective screen are outlined, with exemplification in one particular target, the melatonin receptor, where following this procedure led to direct docking hits with activities in the subnanomolar range.

Principles of docking: An overview of search algorithms and a guide to scoring functions

The docking field has come of age, and the time is ripe to present the principles of docking, reviewing the current state of the field from both the computational and the biological points of view.