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Published on: June 9, 2017
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Between Descriptors and Properties: Understanding the Ligand Efficiency Trends for G Protein-Coupled Receptor and
Jaroslaw Polanski1, Aleksandra Tkocz1
1Institute of Chemistry, University of Silesia , 9 Szkolna Street, 40-006 Katowice, Poland.
Journal of Chemical Information and Modeling
|May 11, 2017
Summary
Ligand efficiency (LE) is a statistical property, not a molecular descriptor. This finding reevaluates its use in drug optimization by considering Avogadro statistics and non-binding effects.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Pharmacology
Background:
- Ligand efficiency (LE) is widely used in early drug optimization as an estimator of binding potency.
- Controversy exists regarding the mathematical validity and performance of LE metrics in drug discovery.
- Current interpretations of LE often misunderstand its chemical meaning, linking it to single molecular properties.
Purpose of the Study:
- To clarify the chemical meaning of ligand efficiency (LE) metrics.
- To explain the statistical basis of LE using G protein-coupled receptor (GPCR) and kinase structure-activity data.
- To address the common misinterpretation of LE as a descriptor of a single molecule's binding potency.
Main Methods:
- Analysis of a large dataset of G protein-coupled receptor (GPCR) and kinase structure-activity relationships (IC50, Ki).
- Statistical regression of binding properties against heavy atom count (HAC).
- Investigation of the correlation between LE and molecular weight due to Avogadro statistics.
Main Results:
- Ligand efficiency (LE) is demonstrated to be a statistical property, not a descriptor of a single molecule.
- LE is correlated with the reciprocal of molecular weight due to Avogadro statistics.
- The observed hyperbolic model of LE arises from a non-binding effect related to ligand availability, not increased binding potency per HAC.
Conclusions:
- The interpretation of LE as a molecular descriptor for a single molecule is fundamentally flawed.
- LE should be understood as a statistical property influenced by molecular size and ligand pool effects.
- Reevaluation of LE-based molecular comparisons is necessary for accurate drug optimization strategies.
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