ArticlePLoS computational biology2017
Simple biochemical networks allow accurate sensing of multiple ligands with a single receptor.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 32 citations in OpenAlex.
- Article
- Individual yeast cells signal at different levels but each with good precision.Royal Society open science · 2025Article
- Cell shape and orientation control galvanotactic accuracy.Soft matter · 2024Article
- Limits on the accuracy of contact inhibition of locomotion.Physical review. E · 2024Article
- Cells function as a ternary logic gate to decide migration direction under integrated chemical and fluidic cues.Lab on a chip · 2023Article
- Optimal ligand discrimination by asymmetric dimerization and turnover of interferon receptors.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Information transmission from NFkB signaling dynamics to gene expression.PLoS computational biology · 2020Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cells use surface receptors to estimate concentrations of external ligands. Limits on the accuracy of such estimations have been well studied for pairs of ligand and receptor species. However, the environment typically contains many ligands, which can bind to the same receptors with different affinities, resulting in cross-talk. In traditional rate models, such cross-talk prevents accurate inference of concentrations of individual ligands. In contrast, here we show that knowing the precise timing sequence of stochastic binding and unbinding events allows one receptor to provide information about multiple ligands simultaneously and with a high accuracy. We show that such high-accuracy estimation of multiple concentrations can be realized with simple structural modifications of the familiar kinetic proofreading biochemical network diagram. We give two specific examples of such modifications. We argue that structural and functional features of real cellular biochemical sensory networks in immune cells, such as feedforward and feedback loops or ligand antagonism, sometimes can be understood as solutions to the accurate multi-ligand estimation problem.
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