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Probability of autocrine ligand capture by cell-surface receptors: implications for ligand secretion measurements.

Authors :
Forsten KE
Lauffenburger DA
Source :
Journal of computational biology : a journal of computational molecular cell biology [J Comput Biol] 1994 Spring; Vol. 1 (1), pp. 15-23.
Publication Year :
1994

Abstract

Autocrine ligands regulate important cell behavioral functions in both physiological and pathological conditions. Binding of these ligands to cell-surface receptors involves more subtle considerations than that of exogenous (endocrine or paracrine) ligands. Autocrine secretion leads to a release of molecules in the local microenvironment proximal to the cell surface, thus allowing interaction with receptors to compete directly with diffusive loss to the bulk extracellular medium. Complications in autocrine systems due to this binding vs. transport competition arise in at least three aspects: (i) experimental measurement of autocrine ligand secretion rates is compromised; (ii) kinetics of autocrine ligand binding to cell-surface receptors are difficult to follow; and (iii) inhibition by exogenous blockers of autocrine ligand binding to cell receptors is problematic. At the heart of all these complications is the need to determine the fractional distribution of the secreted autocrine ligand between cell-surface receptor capture and diffusive loss to the bulk media. In this paper we offer a theoretical treatment of this problem using Brownian dynamics simulation techniques to calculate the capture probability of the cell receptors for the autocrine ligand. A major result is that the capture probability is significantly lower than the predicted by the Berg-Purcell steady-state diffusion approach. Another is that the capture probability is essentially independent of release location. Implications of these results for the complications found in autocrine systems are discussed.

Details

Language :
English
ISSN :
1066-5277
Volume :
1
Issue :
1
Database :
MEDLINE
Journal :
Journal of computational biology : a journal of computational molecular cell biology
Publication Type :
Academic Journal
Accession number :
8790450
Full Text :
https://doi.org/10.1089/cmb.1994.1.15