Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process
Abstract Background In cell signaling pathways, proteins interact with each other to determine cell fate in response to either cell-extrinsic (micro-environmental) or intrinsic cues. One of the well-studied pathways, the mitogen-activated protein kinase (MAPK) signaling pathway, regulates cell proce...
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| Format: | Article |
| Language: | English |
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BMC
2022-11-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-022-05077-z |
| _version_ | 1811207576138809344 |
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| author | Minsoo Kim Eunjung Kim |
| author_facet | Minsoo Kim Eunjung Kim |
| author_sort | Minsoo Kim |
| collection | DOAJ |
| description | Abstract Background In cell signaling pathways, proteins interact with each other to determine cell fate in response to either cell-extrinsic (micro-environmental) or intrinsic cues. One of the well-studied pathways, the mitogen-activated protein kinase (MAPK) signaling pathway, regulates cell processes such as differentiation, proliferation, apoptosis, and survival in response to various micro-environmental stimuli in eukaryotes. Upon micro-environmental stimulus, receptors on the cell membrane become activated. Activated receptors initiate a cascade of protein activation in the MAPK pathway. This activation involves protein binding, creating scaffold proteins, which are known to facilitate effective MAPK signaling transduction. Results This paper presents a novel mathematical model of a cell signaling pathway coordinated by protein scaffolding. The model is based on the extended Boolean network approach with stochastic processes. Protein production or decay in a cell was modeled considering the stochastic process, whereas the protein–protein interactions were modeled based on the extended Boolean network approach. Our model fills a gap in the binary set applied to previous models. The model simultaneously considers the stochastic process directly. Using the model, we simulated a simplified mitogen-activated protein kinase (MAPK) signaling pathway upon stimulation of both a single receptor at the initial time and multiple receptors at several time points. Our simulations showed that the signal is amplified as it travels down to the pathway from the receptor, generating substantially amplified downstream ERK activity. The noise generated by the stochastic process of protein self-activity in the model was also amplified as the signaling propagated through the pathway. Conclusions The signaling transduction in a simplified MAPK signaling pathway could be explained by a mathematical model based on the extended Boolean network model with a stochastic process. The model simulations demonstrated signaling amplifications when it travels downstream, which was already observed in experimental settings. We also highlight the importance of stochastic activity in regulating protein inactivation. |
| first_indexed | 2024-04-12T04:06:39Z |
| format | Article |
| id | doaj.art-bfe9f8c95a5a4da095ba62bdef3792cd |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-12T04:06:39Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-bfe9f8c95a5a4da095ba62bdef3792cd2022-12-22T03:48:36ZengBMCBMC Bioinformatics1471-21052022-11-0123111510.1186/s12859-022-05077-zMathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic processMinsoo Kim0Eunjung Kim1Natural Product Informatics Research Center, Korea Institute of Science and TechnologyNatural Product Informatics Research Center, Korea Institute of Science and TechnologyAbstract Background In cell signaling pathways, proteins interact with each other to determine cell fate in response to either cell-extrinsic (micro-environmental) or intrinsic cues. One of the well-studied pathways, the mitogen-activated protein kinase (MAPK) signaling pathway, regulates cell processes such as differentiation, proliferation, apoptosis, and survival in response to various micro-environmental stimuli in eukaryotes. Upon micro-environmental stimulus, receptors on the cell membrane become activated. Activated receptors initiate a cascade of protein activation in the MAPK pathway. This activation involves protein binding, creating scaffold proteins, which are known to facilitate effective MAPK signaling transduction. Results This paper presents a novel mathematical model of a cell signaling pathway coordinated by protein scaffolding. The model is based on the extended Boolean network approach with stochastic processes. Protein production or decay in a cell was modeled considering the stochastic process, whereas the protein–protein interactions were modeled based on the extended Boolean network approach. Our model fills a gap in the binary set applied to previous models. The model simultaneously considers the stochastic process directly. Using the model, we simulated a simplified mitogen-activated protein kinase (MAPK) signaling pathway upon stimulation of both a single receptor at the initial time and multiple receptors at several time points. Our simulations showed that the signal is amplified as it travels down to the pathway from the receptor, generating substantially amplified downstream ERK activity. The noise generated by the stochastic process of protein self-activity in the model was also amplified as the signaling propagated through the pathway. Conclusions The signaling transduction in a simplified MAPK signaling pathway could be explained by a mathematical model based on the extended Boolean network model with a stochastic process. The model simulations demonstrated signaling amplifications when it travels downstream, which was already observed in experimental settings. We also highlight the importance of stochastic activity in regulating protein inactivation.https://doi.org/10.1186/s12859-022-05077-zExtended Boolean network modelStochastic processMAPK signaling pathway |
| spellingShingle | Minsoo Kim Eunjung Kim Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process BMC Bioinformatics Extended Boolean network model Stochastic process MAPK signaling pathway |
| title | Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process |
| title_full | Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process |
| title_fullStr | Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process |
| title_full_unstemmed | Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process |
| title_short | Mathematical model of the cell signaling pathway based on the extended Boolean network model with a stochastic process |
| title_sort | mathematical model of the cell signaling pathway based on the extended boolean network model with a stochastic process |
| topic | Extended Boolean network model Stochastic process MAPK signaling pathway |
| url | https://doi.org/10.1186/s12859-022-05077-z |
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