Evidence map›Paper›PMID 17034642›Full record

ArticleTheoretical biology & medical modelling2006

Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling.

Kouroush Sadegh Zadeh, Hubert J Montas, Adel Shirmohammadi

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Article in Theoretical biology & medical modelling, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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10citing papers in PubMed
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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Image based validation of dynamical models for cell reorientation.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2015
    Article
  6. Article
  7. Article
  8. Article
  9. A finite element model for protein transport in vivo.Biomedical engineering online · 2007
    Article
  10. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Kouroush Sadegh ZadehFischell Department of Bioengineering, University of Maryland, College Park, Maryland 20742, USA. kouroush@eng.umd.edu
Hubert J Montas
Adel Shirmohammadi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching (FRAP) is becoming more important. METHODS AND

resultsThe Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching (FRAP) protocol, and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells, to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy, one can also uniquely estimate the individual values of the binding rate coefficients if the molecular diffusion coefficient is known. One can also simultaneously estimate the dissociation rate parameter and molecular diffusion coefficient given the pseudo-association rate parameter is known. However, the protocol provides insufficient information for unique simultaneous estimation of three parameters (diffusion coefficient and binding rate parameters) owing to the high intercorrelation between the molecular diffusion coefficient and pseudo-association rate parameter. Attempts to estimate macromolecule mass transport and binding rate parameters simultaneously from FRAP data result in misleading conclusions regarding concentrations of free macromolecule and bound complex inside the cell, average binding time per vacant site, average time for diffusion of macromolecules from one site to the next, and slow or rapid mobility of biomolecules in cells.

conclusionTo obtain unique values for molecular diffusion coefficient and binding rate parameters from FRAP data, we propose conducting two FRAP experiments on the same class of macromolecule and cell. One experiment should be used to measure the molecular diffusion coefficient independently of binding in an effective diffusion regime and the other should be conducted in a reaction dominant or reaction-diffusion regime to quantify binding rate parameters. The method described in this paper is likely to be widely used to estimate in-vivo biomolecule mass transport and binding rate parameters.

Indexed as

Biological TransportModels, BiologicalAlgorithmsAnimalsCell Line, TumorCell SurvivalDiffusionFluorescence Recovery After PhotobleachingKineticsMiceReceptors, GlucocorticoidRecombinant Fusion ProteinsReceptors, GlucocorticoidRecombinant Fusion Proteins

Identifiers

PMID17034642
PMCPMC1635038

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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.