Evidence map›Paper›PMID 29086197›Full record

ArticleJournal of cheminformatics2017

Beware of ligand efficiency (LE): understanding LE data in modeling structure-activity and structure-economy relationships.

Jaroslaw Polanski, Aleksandra Tkocz, Urszula Kucia

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. 2-Alkyl-Substituted-4-Amino-Thieno[2,3-Molecules (Basel, Switzerland) · 2023
    Article
  2. Review
  3. Article
  4. Article
  5. Homology models of mouse and rat estrogen receptor-Computational toxicology (Amsterdam, Netherlands) · 2019
    Article
  6. The nature of ligand efficiency.Journal of cheminformatics · 2019
    Article
  7. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jaroslaw PolanskiInstitute of Chemistry, University of Silesia, 9 Szkolna Street, 40-006, Katowice, Poland. polanski@us.edu.pl.
Aleksandra TkoczInstitute of Chemistry, University of Silesia, 9 Szkolna Street, 40-006, Katowice, Poland.
Urszula KuciaInstitute of Chemistry, University of Silesia, 9 Szkolna Street, 40-006, Katowice, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOn the one hand, ligand efficiency (LE) and the binding efficiency index (BEI), which are binding properties (B) averaged versus the heavy atom count (HAC: LE) or molecular weight (MW: BEI), have recently been declared a novel universal tool for drug design. On the other hand, questions have been raised about the mathematical validity of the LE approach.

resultsIn fact, neither the critics nor the advocates are precise enough to provide a generally understandable and accepted chemistry of the LE metrics. In particular, this refers to the puzzle of the LE trends for small and large molecules. In this paper, we explain the chemistry and mathematics of the LE type of data. Because LE is a weight metrics related to binding per gram, its hyperbolic decrease with an increasing number of heavy atoms can be easily understood by its 1/MW dependency. Accordingly, we analyzed how this influences the LE trends for ligand-target binding, economic big data or molecular descriptor data. In particular, we compared the trends for the thermodynamic ∆G data of a series of ligands that interact with 14 different target classes, which were extracted from the BindingDB database with the market prices of a commercial compound library of ca. 2.5 mln synthetic building blocks.

conclusionsAn interpretation of LE and BEI that clearly explains the observed trends for these parameters are presented here for the first time. Accordingly, we show that the main misunderstanding of the chemical meaning of the BEI and LE parameters is their interpretation as molecular descriptors that are connected with a single molecule, while binding is a statistical effect in which a population of ligands limits the formation of ligand-receptor complexes. Therefore, LE (BEI) should not be interpreted as a molecular (physicochemical) descriptor that is connected with a single molecule but as a property (binding per gram). Accordingly, the puzzle of the surprising behavior of LE is explained by the 1/MW dependency. This effect clearly explains the hyperbolic LE trend not as a real increase in binding potency but as a physical limitation due to the different population of ligands with different MWs in a 1 g sample available for the formation of ligand-receptor complexes. Graphical abstract .

Indexed as

Avogadro numberBig dataFragmental metricsLigand efficiencyLigand-target binding affinityMolar metricsWeight metrics

Identifiers

PMID29086197
PMCPMC5593805

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.