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A control theoretic three timescale model for analyzing energy management in mammalian cancer cells.

Authors :
Dasgupta A
Bakshi A
Chowdhury N
De RK
Source :
Computational and structural biotechnology journal [Comput Struct Biotechnol J] 2020 Dec 29; Vol. 19, pp. 477-508. Date of Electronic Publication: 2020 Dec 29 (Print Publication: 2021).
Publication Year :
2020

Abstract

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-1 α (HIF-1 α ) 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).<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2020 The Authors.)

Details

Language :
English
ISSN :
2001-0370
Volume :
19
Database :
MEDLINE
Journal :
Computational and structural biotechnology journal
Publication Type :
Academic Journal
Accession number :
33510857
Full Text :
https://doi.org/10.1016/j.csbj.2020.12.019