Evidence map›Paper›PMID 31444916›Full record

ArticleBritish journal of pharmacology2019

Considerations for improved performance of competition association assays analysed with the Motulsky-Mahan's "kinetics of competitive binding" model.

Victoria Georgi, Alexey Dubrovskiy, Stephan Steigele, Amaury E Fernández-Montalván

Open access · hybridAbstract read
In one paragraph

Article in British journal of pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. On the structural identifiability of nonlinear models of ligand binding dynamics.Journal of pharmacokinetics and pharmacodynamics · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 3 countries.

Victoria GeorgiDrug Discovery, Pharmaceuticals, Bayer AG, Berlin, Germany.ORCID 0000-0001-6647-8056
Alexey DubrovskiyResearch and Development, Genedata AG, Basel, Switzerland.ORCID 0000-0001-6169-6804
Stephan SteigeleResearch and Development, Genedata AG, Basel, Switzerland.
Amaury E Fernández-MontalvánDrug Discovery, Pharmaceuticals, Bayer AG, Berlin, Germany.ORCID 0000-0001-9156-0000
Genedata (Switzerland) · CHAVL (France) · FRBayer (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeTarget engagement dynamics can influence drugs' pharmacological effects. Kinetic parameters for drug:target interactions are often quantified by evaluating competition association experiments-measuring simultaneous protein binding of labelled tracers and unlabelled test compounds over time-with Motulsky-Mahan's "kinetics of competitive binding" model. Despite recent technical improvements, the current assay formats impose practical limitations to this approach. This study aims at the characterisation, understanding and prevention of these experimental constraints, and associated analytical challenges. EXPERIMENTAL APPROACH: Monte Carlo simulations were used to run virtual kinetic and equilibrium tracer binding and competition experiments in both normal and perturbed assay conditions. Data were fitted to standard equations derived from the mass action law (including Motulsky-Mahan's) and to extended versions aiming to cope with frequently observed deviations of the canonical traces. Results were compared to assess the precision and accuracy of these models and identify experimental factors influencing their performance. KEY

resultsKey factors influencing the precision and accuracy of the Motulsky-Mahan model are the interplay between compound dissociation rates, measurement time and interval frequency, tracer concentration and binding kinetics and the relative abundance of equilibrium complexes in vehicle controls. Experimental results produced recommendations for better design of tracer characterisation experiments and new strategies to deal with systematic signal decay. CONCLUSIONS AND IMPLICATIONS: Our data advances our comprehension of the Motulsky-Mahan kinetics of competitive binding models and provides experimental design recommendations, data analysis tools, and general guidelines for its practical application to in vitro pharmacology and drug screening.

Indexed as

Models, BiologicalPharmaceutical PreparationsBinding, CompetitiveComputer SimulationDrug InteractionsHumansKineticsLigandsMonte Carlo MethodProtein BindingSolubilityLigandsPharmaceutical Preparations

Identifiers

PMID31444916
PMCPMC7029771
OpenAlexW2969344840

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.