dorsal/arxiv
View SchemaClustering and Signalling of Cell Receptors
| Authors | Y. Shi |
|---|---|
| Categories | |
| ArXiv ID | physics/0007050 |
| URL | https://arxiv.org/abs/physics/0007050 |
| DOI | 10.1016/S0378-4371(02)00834-8 |
| Journal | Physica A 311, 199 (2002) |
Abstract
As a response to ligand binding, transmembrane cell receptors often enhance their clustering, or oligomerization, during the signalling process. Here we present a statistical mechanical model which combines the aspects of clustering and signalling. In this model, receptors float on the surface, while for two neighboring receptors, there is an interaction energy dependent on their conformational states. On the other hand, ligand binding of a receptor shifts the energy difference between the two conformational states. Due to thermal fluctuation, the effects of clustering and signalling are statistical average quantities. This model reduces to a floating Ising model with a random field. We calculate the signalling in a grand canonical ensemble mean field approach, using Hubbard-Stratonovich transformation and replica method. Monte Carlo simulations are also performed. Essential biological features are obtained in our model.
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"abstract": "As a response to ligand binding, transmembrane cell receptors often enhance\ntheir clustering, or oligomerization, during the signalling process. Here we\npresent a statistical mechanical model which combines the aspects of clustering\nand signalling. In this model, receptors float on the surface, while for two\nneighboring receptors, there is an interaction energy dependent on their\nconformational states. On the other hand, ligand binding of a receptor shifts\nthe energy difference between the two conformational states. Due to thermal\nfluctuation, the effects of clustering and signalling are statistical average\nquantities. This model reduces to a floating Ising model with a random field.\nWe calculate the signalling in a grand canonical ensemble mean field approach,\nusing Hubbard-Stratonovich transformation and replica method. Monte Carlo\nsimulations are also performed. Essential biological features are obtained in\nour model.",
"arxiv_id": "physics/0007050",
"authors": [
"Y. Shi"
],
"categories": [
"physics.bio-ph",
"cond-mat.stat-mech",
"q-bio.MN"
],
"doi": "10.1016/S0378-4371(02)00834-8",
"journal_ref": "Physica A 311, 199 (2002)",
"title": "Clustering and Signalling of Cell Receptors",
"url": "https://arxiv.org/abs/physics/0007050"
},
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