ArticleThe Journal of general physiology2017
The structure of binding curves and practical identifiability of equilibrium ligand-binding parameters.
Article in The Journal of general physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 19 citations in OpenAlex.
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- Using Bayesian priors to overcome non-identifiablility issues in Hidden Markov models.bioRxiv : the preprint server for biology · 2025Article
- Bioelectricity and molecular signaling.Biophysical journal · 2024Article
- Classical structural identifiability methodology applied to low-dimensional dynamic systems in receptor theory.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Identifiability of equilibrium constants for receptors with two to five binding sites.The Journal of general physiology · 2023Article
- A strategy for determining the equilibrium constants for heteromeric ion channels in a complex model.The Journal of general physiology · 2022Article
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- Deciphering cell-cell interactions and communication from gene expression.Nature reviews. Genetics · 2021Review
- Non-Additive Effects of Binding Site Mutations in Calmodulin.Biochemistry · 2019Article
- Models to determine the kinetic mechanisms of ion-coupled transporters.The Journal of general physiology · 2019Article
- Coordination to lanthanide ions distorts binding site conformation in calmodulin.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Identifiability, reducibility, and adaptability in allosteric macromolecules.The Journal of general physiology · 2017Article
- Structural identifiability of equilibrium ligand-binding parameters.The Journal of general physiology · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A critical but often overlooked question in the study of ligands binding to proteins is whether the parameters obtained from analyzing binding data are practically identifiable (PI), i.e., whether the estimates obtained from fitting models to noisy data are accurate and unique. Here we report a general approach to assess and understand binding parameter identifiability, which provides a toolkit to assist experimentalists in the design of binding studies and in the analysis of binding data. The partial fraction (PF) expansion technique is used to decompose binding curves for proteins with n ligand-binding sites exactly and uniquely into n components, each of which has the form of a one-site binding curve. The association constants of the PF component curves, being the roots of an n-th order polynomial, may be real or complex. We demonstrate a fundamental connection between binding parameter identifiability and the nature of these one-site association constants: all binding parameters are identifiable if the constants are all real and distinct; otherwise, at least some of the parameters are not identifiable. The theory is used to construct identifiability maps from which the practical identifiability of binding parameters for any two-, three-, or four-site binding curve can be assessed. Instructions for extending the method to generate identifiability maps for proteins with more than four binding sites are also given. Further analysis of the identifiability maps leads to the simple rule that the maximum number of structurally identifiable binding parameters (shown in the previous paper to be equal to n) will also be PI only if the binding curve line shape contains n resolved components.
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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.