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Computational modeling reveals molecular details of epidermal growth factor binding
BACKGROUND: The ErbB family of receptors are dysregulated in a number of cancers, and the signaling pathway of this receptor family is a critical target for several anti-cancer drugs. Therefore a detailed understanding of the mechanisms of receptor activation is critical. However, despite a plethora...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1322221/ https://www.ncbi.nlm.nih.gov/pubmed/16318625 http://dx.doi.org/10.1186/1471-2121-6-41 |
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author | Mayawala, Kapil Vlachos, Dionisios G Edwards, Jeremy S |
author_facet | Mayawala, Kapil Vlachos, Dionisios G Edwards, Jeremy S |
author_sort | Mayawala, Kapil |
collection | PubMed |
description | BACKGROUND: The ErbB family of receptors are dysregulated in a number of cancers, and the signaling pathway of this receptor family is a critical target for several anti-cancer drugs. Therefore a detailed understanding of the mechanisms of receptor activation is critical. However, despite a plethora of biochemical studies and recent single particle tracking experiments, the early molecular mechanisms involving epidermal growth factor (EGF) binding and EGF receptor (EGFR) dimerization are not as well understood. Herein, we describe a spatially distributed Monte Carlo based simulation framework to enable the simulation of in vivo receptor diffusion and dimerization. RESULTS: Our simulation results are in agreement with the data from single particle tracking and biochemical experiments on EGFR. Furthermore, the simulations reveal that the sequence of receptor-receptor and ligand-receptor reaction events depends on the ligand concentration, receptor density and receptor mobility. CONCLUSION: Our computer simulations reveal the mechanism of EGF binding on EGFR. Overall, we show that spatial simulation of receptor dynamics can be used to gain a mechanistic understanding of receptor activation which may in turn enable improved cancer treatments in the future. |
format | Text |
id | pubmed-1322221 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-13222212006-01-09 Computational modeling reveals molecular details of epidermal growth factor binding Mayawala, Kapil Vlachos, Dionisios G Edwards, Jeremy S BMC Cell Biol Research Article BACKGROUND: The ErbB family of receptors are dysregulated in a number of cancers, and the signaling pathway of this receptor family is a critical target for several anti-cancer drugs. Therefore a detailed understanding of the mechanisms of receptor activation is critical. However, despite a plethora of biochemical studies and recent single particle tracking experiments, the early molecular mechanisms involving epidermal growth factor (EGF) binding and EGF receptor (EGFR) dimerization are not as well understood. Herein, we describe a spatially distributed Monte Carlo based simulation framework to enable the simulation of in vivo receptor diffusion and dimerization. RESULTS: Our simulation results are in agreement with the data from single particle tracking and biochemical experiments on EGFR. Furthermore, the simulations reveal that the sequence of receptor-receptor and ligand-receptor reaction events depends on the ligand concentration, receptor density and receptor mobility. CONCLUSION: Our computer simulations reveal the mechanism of EGF binding on EGFR. Overall, we show that spatial simulation of receptor dynamics can be used to gain a mechanistic understanding of receptor activation which may in turn enable improved cancer treatments in the future. BioMed Central 2005-11-30 /pmc/articles/PMC1322221/ /pubmed/16318625 http://dx.doi.org/10.1186/1471-2121-6-41 Text en Copyright © 2005 Mayawala et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Mayawala, Kapil Vlachos, Dionisios G Edwards, Jeremy S Computational modeling reveals molecular details of epidermal growth factor binding |
title | Computational modeling reveals molecular details of epidermal growth factor binding |
title_full | Computational modeling reveals molecular details of epidermal growth factor binding |
title_fullStr | Computational modeling reveals molecular details of epidermal growth factor binding |
title_full_unstemmed | Computational modeling reveals molecular details of epidermal growth factor binding |
title_short | Computational modeling reveals molecular details of epidermal growth factor binding |
title_sort | computational modeling reveals molecular details of epidermal growth factor binding |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1322221/ https://www.ncbi.nlm.nih.gov/pubmed/16318625 http://dx.doi.org/10.1186/1471-2121-6-41 |
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