Rethinking Ligand Efficiency: Normalization Pitfalls, Uncertainty, and State-Invariant Metrics

Ligand efficiency (LE), defined as the negative binding free energy per heavy atom, is a widely used metric in medicinal chemistry. Yet its mathematical construction embeds a strong size bias that distorts cross-size comparisons, and size-independent variants inherit sensitivity to the arbitrary choice of standard state. This study reviews normalization pitfalls, addresses uncertainty propagation, and introduces a state-invariant, size-normalized metric for efficiency-guided optimization from fragments to leads.

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Publication Details

Journal
ACS Medicinal Chemistry Letters
Published
2025-11-11
DOI
https://doi.org/10.1021/acsmedchemlett.5c00652
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Rethinking Ligand Efficiency: Normalization Pitfalls, Uncertainty, and State-Invariant Metrics

Hongtao Zhao
1 citations
ACS Medicinal Chemistry Letters
Computational Drug Discovery Methods
1.50
article

Rethinking Ligand Efficiency: Normalization Pitfalls, Uncertainty, and State-Invariant Metrics

Hongtao Zhao
article en
1 citations

Abstract

Ligand efficiency (LE), defined as the negative binding free energy per heavy atom, is a widely used metric in medicinal chemistry. Yet its mathematical construction embeds a strong size bias that distorts cross-size comparisons, and size-independent variants inherit sensitivity to the arbitrary choice of standard state. This study reviews normalization pitfalls, addresses uncertainty propagation, and introduces a state-invariant, size-normalized metric for efficiency-guided optimization from fragments to leads.

ACS Medicinal Chemistry LettersVol. 16(12)
AstraZeneca (Brazil) (BR), Medicina (PL), AstraZeneca (Sweden) (SE)
Openalex Percentile: Top 12%
Computational Drug Discovery Methods
1.50
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