Monte Carlo simulations of receptor dynamics: Insights into cell signaling
dc.contributor.author | Brinkerhoff, Christopher J. | en_US |
dc.contributor.author | Woolf, Peter J. | en_US |
dc.contributor.author | Linderman, Jennifer J. | en_US |
dc.date.accessioned | 2006-09-08T20:48:08Z | |
dc.date.available | 2006-09-08T20:48:08Z | |
dc.date.issued | 2004-09 | en_US |
dc.identifier.citation | Brinkerhoff, Christopher J.; Woolf, Peter J.; Linderman, Jennifer J.; (2004). "Monte Carlo simulations of receptor dynamics: Insights into cell signaling." The Histochemical Journal 35(7): 667-677. <http://hdl.handle.net/2027.42/42859> | en_US |
dc.identifier.issn | 1567-2379 | en_US |
dc.identifier.issn | 1573-6865 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/42859 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=15614622&dopt=citation | en_US |
dc.description.abstract | Many receptor-level processes involve the diffusion and reaction of receptors with other membrane-localized molecules. Monte Carlo simulation is a powerful technique that allows us to track the motions and discrete reactions of individual receptors, thus simulating receptor dynamics and the early events of signal transduction. In this paper, we discuss simulations of two receptor processes, receptor dimerization and G-protein activation. Our first set of simulations demonstrates how receptor dimerization can create clusters of receptors via partner switching and the relevance of this clustering for receptor cross-talk and integrin signaling. Our second set of simulations investigates the activation and desensitization of G-protein coupled receptors when either a single agonist or both an agonist and an antagonist are present. For G-protein coupled receptor systems in the presence of an agonist alone, the dissociation rate constant of agonist is predicted to affect the ratio of G-protein activation to receptor phosphorylation. Similarly, this ratio is affected by the antagonist dissociation rate constant when both agonist and antagonist are present. The relationship of simulation predictions to experimental findings and potential applications of our findings are also discussed. | en_US |
dc.format.extent | 297479 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Life Sciences | en_US |
dc.subject.other | Biomedicine General | en_US |
dc.subject.other | Cell Biology | en_US |
dc.subject.other | Animal Anatomy / Morphology / Histology | en_US |
dc.subject.other | Biological Microscopy | en_US |
dc.title | Monte Carlo simulations of receptor dynamics: Insights into cell signaling | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Chemical Engineering, University of Michigan, 48109, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Department of Chemical Engineering, University of Michigan, 48109, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Department of Chemical Engineering, University of Michigan, 48109, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.identifier.pmid | 15614622 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/42859/1/10735_2004_Article_DO00002663.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/s10735-004-2663-y | en_US |
dc.identifier.source | The Histochemical Journal | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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