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Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks
The interactions between cells and their extracellular matrix (ECM) are critically important for homeostatic control of cell growth, proliferation, differentiation and apoptosis. Transmembrane integrin molecules facilitate the communication between ECM and the cell. Since the characterization of int...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779863/ https://www.ncbi.nlm.nih.gov/pubmed/33425258 http://dx.doi.org/10.1016/j.csbj.2020.12.025 |
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author | Karagöz, Zeynep Rijns, Laura Dankers, Patricia Y.W. van Griensven, Martijn Carlier, Aurélie |
author_facet | Karagöz, Zeynep Rijns, Laura Dankers, Patricia Y.W. van Griensven, Martijn Carlier, Aurélie |
author_sort | Karagöz, Zeynep |
collection | PubMed |
description | The interactions between cells and their extracellular matrix (ECM) are critically important for homeostatic control of cell growth, proliferation, differentiation and apoptosis. Transmembrane integrin molecules facilitate the communication between ECM and the cell. Since the characterization of integrins in the late 1980s, there has been great advancement in understanding the function of integrins at different subcellular levels. However, the versatility in molecular pathways integrins are involved in, the high diversity in their interaction partners both outside and inside the cell as well as on the cell membrane and the short lifetime of events happening at the cell–ECM interface make it difficult to elucidate all the details regarding integrin function experimentally. To overcome the experimental challenges and advance the understanding of integrin biology, computational modeling tools have been used extensively. In this review, we summarize the computational models of integrin signaling while we explain the function of integrins at three main subcellular levels (outside the cell, cell membrane, cytosol). We also discuss how these computational modeling efforts can be helpful in other disciplines such as biomaterial design. As such, this review is a didactic modeling summary for biomaterial researchers interested in complementing their experimental work with computational tools or for seasoned computational scientists that would like to advance current in silico integrin models. |
format | Online Article Text |
id | pubmed-7779863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-77798632021-01-08 Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks Karagöz, Zeynep Rijns, Laura Dankers, Patricia Y.W. van Griensven, Martijn Carlier, Aurélie Comput Struct Biotechnol J Review The interactions between cells and their extracellular matrix (ECM) are critically important for homeostatic control of cell growth, proliferation, differentiation and apoptosis. Transmembrane integrin molecules facilitate the communication between ECM and the cell. Since the characterization of integrins in the late 1980s, there has been great advancement in understanding the function of integrins at different subcellular levels. However, the versatility in molecular pathways integrins are involved in, the high diversity in their interaction partners both outside and inside the cell as well as on the cell membrane and the short lifetime of events happening at the cell–ECM interface make it difficult to elucidate all the details regarding integrin function experimentally. To overcome the experimental challenges and advance the understanding of integrin biology, computational modeling tools have been used extensively. In this review, we summarize the computational models of integrin signaling while we explain the function of integrins at three main subcellular levels (outside the cell, cell membrane, cytosol). We also discuss how these computational modeling efforts can be helpful in other disciplines such as biomaterial design. As such, this review is a didactic modeling summary for biomaterial researchers interested in complementing their experimental work with computational tools or for seasoned computational scientists that would like to advance current in silico integrin models. Research Network of Computational and Structural Biotechnology 2020-12-29 /pmc/articles/PMC7779863/ /pubmed/33425258 http://dx.doi.org/10.1016/j.csbj.2020.12.025 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Karagöz, Zeynep Rijns, Laura Dankers, Patricia Y.W. van Griensven, Martijn Carlier, Aurélie Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks |
title | Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks |
title_full | Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks |
title_fullStr | Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks |
title_full_unstemmed | Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks |
title_short | Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks |
title_sort | towards understanding the messengers of extracellular space: computational models of outside-in integrin reaction networks |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779863/ https://www.ncbi.nlm.nih.gov/pubmed/33425258 http://dx.doi.org/10.1016/j.csbj.2020.12.025 |
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