A control theoretic three timescale model for analyzing energy management in mammalian cancer cells
Interaction among different pathways, such as metabolic, signaling and gene regulatory networks, of cellular system is responsible to maintain homeostasis in a mammalian cell. Malfunctioning of this cooperation may lead to many complex diseases, such as cancer and type 2 diabetes. Timescale differen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037020305444 |
| _version_ | 1819320356508270592 |
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| author | Abhijit Dasgupta Abhisek Bakshi Nirmalya Chowdhury Rajat K. De |
| author_facet | Abhijit Dasgupta Abhisek Bakshi Nirmalya Chowdhury Rajat K. De |
| author_sort | Abhijit Dasgupta |
| collection | DOAJ |
| description | Interaction among different pathways, such as metabolic, signaling and gene regulatory networks, of cellular system is responsible to maintain homeostasis in a mammalian cell. Malfunctioning of this cooperation may lead to many complex diseases, such as cancer and type 2 diabetes. Timescale differences among these pathways make their integration a daunting task. Metabolic, signaling and gene regulatory networks have three different timescales, such as, ultrafast, fast and slow respectively.The article deals with this problem by developing a support vector regression (SVR) based three timescale model with the application of genetic algorithm based nonlinear controller. The proposed model can successfully capture the nonlinear transient dynamics and regulations of such integrated biochemical pathway under consideration. Besides, the model is quite capable of predicting the effects of certain drug targets for many types of complex diseases. Here, energy and cell proliferation management of mammalian cancer cells have been explored and analyzed with the help of the proposed novel approach. Previous investigations including in silico/in vivo/in vitro experiments have validated the results (the regulations of glucose transporter 1 (glut1), hexokinase (HK), and hypoxia-inducible factor-1α (HIF-1α) among others, and the switching of pyruvate kinase (M2 isoform) between dimer and tetramer) generated by this model proving its effectiveness. Subsequently, the model predicts the effects of six selected drug targets, such as, the deactivation of transketolase and glucose-6-phosphate isomerase among others, in the case of mammalian malignant cells in terms of growth, proliferation, fermentation, and energy supply in the form of adenosine triphosphate (ATP). |
| first_indexed | 2024-12-24T11:18:17Z |
| format | Article |
| id | doaj.art-07504dee3c974a0a923bddeec68ef350 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-12-24T11:18:17Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-07504dee3c974a0a923bddeec68ef3502022-12-21T16:58:18ZengElsevierComputational and Structural Biotechnology Journal2001-03702021-01-0119477508A control theoretic three timescale model for analyzing energy management in mammalian cancer cellsAbhijit Dasgupta0Abhisek Bakshi1Nirmalya Chowdhury2Rajat K. De3Department of Data Science, School of Interdisciplinary Studies, University of Kalyani, Kalyani, Nadia 741235, West Bengal, IndiaDepartment of Information Technology, Bengal Institute of Technology, Basanti Highway, Kolkata 700150, IndiaDepartment of Computer Science & Engineering, Jadavpur University, Kolkata 700032, IndiaMachine Intelligence Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata 700108, India; Corresponding author at: Machine Intelligence Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, West Bengal 700108, India.Interaction among different pathways, such as metabolic, signaling and gene regulatory networks, of cellular system is responsible to maintain homeostasis in a mammalian cell. Malfunctioning of this cooperation may lead to many complex diseases, such as cancer and type 2 diabetes. Timescale differences among these pathways make their integration a daunting task. Metabolic, signaling and gene regulatory networks have three different timescales, such as, ultrafast, fast and slow respectively.The article deals with this problem by developing a support vector regression (SVR) based three timescale model with the application of genetic algorithm based nonlinear controller. The proposed model can successfully capture the nonlinear transient dynamics and regulations of such integrated biochemical pathway under consideration. Besides, the model is quite capable of predicting the effects of certain drug targets for many types of complex diseases. Here, energy and cell proliferation management of mammalian cancer cells have been explored and analyzed with the help of the proposed novel approach. Previous investigations including in silico/in vivo/in vitro experiments have validated the results (the regulations of glucose transporter 1 (glut1), hexokinase (HK), and hypoxia-inducible factor-1α (HIF-1α) among others, and the switching of pyruvate kinase (M2 isoform) between dimer and tetramer) generated by this model proving its effectiveness. Subsequently, the model predicts the effects of six selected drug targets, such as, the deactivation of transketolase and glucose-6-phosphate isomerase among others, in the case of mammalian malignant cells in terms of growth, proliferation, fermentation, and energy supply in the form of adenosine triphosphate (ATP).http://www.sciencedirect.com/science/article/pii/S2001037020305444Pathway integrationTimescaleMIMOSupport vector regressionGenetic algorithmWarburg effect |
| spellingShingle | Abhijit Dasgupta Abhisek Bakshi Nirmalya Chowdhury Rajat K. De A control theoretic three timescale model for analyzing energy management in mammalian cancer cells Computational and Structural Biotechnology Journal Pathway integration Timescale MIMO Support vector regression Genetic algorithm Warburg effect |
| title | A control theoretic three timescale model for analyzing energy management in mammalian cancer cells |
| title_full | A control theoretic three timescale model for analyzing energy management in mammalian cancer cells |
| title_fullStr | A control theoretic three timescale model for analyzing energy management in mammalian cancer cells |
| title_full_unstemmed | A control theoretic three timescale model for analyzing energy management in mammalian cancer cells |
| title_short | A control theoretic three timescale model for analyzing energy management in mammalian cancer cells |
| title_sort | control theoretic three timescale model for analyzing energy management in mammalian cancer cells |
| topic | Pathway integration Timescale MIMO Support vector regression Genetic algorithm Warburg effect |
| url | http://www.sciencedirect.com/science/article/pii/S2001037020305444 |
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