Pool, F., Currie, R., Sweby, P. K.
ORCID: https://orcid.org/0009-0003-8488-0251, Salazar, J. D. and Tindall, M. J.
(2018)
A mathematical model of the mevalonate cholesterol biosynthesis pathway.
Journal of Theoretical Biology, 443.
pp. 157-176.
ISSN 0022-5193
doi: 10.1016/j.jtbi.2017.12.023
Abstract/Summary
We formulate, parameterise and analyse a mathematical model of the mevalonate pathway, a key pathway in the synthesis of cholesterol. Of high clinical importance, the pathway incorporates rate limiting enzymatic reactions with multiple negative feedbacks. In this work we investigate the pathway dynamics and demonstrate that rate limiting steps and negative feedbacks within it act in concert to tightly regulate intracellular cholesterol levels. Formulated using the theory of nonlinear ordinary differential equations and parameterised in the context of a hepatocyte, the governing equations are analysed numerically and analytically. Sensitivity and mathematical analysis demonstrate the importance of the two rate limiting enzymes 3-hydroxy-3-methylglutaryl-CoA reductase and squalene synthase in controlling the concentration of substrates within the pathway as well as that of cholesterol. The role of individual feedbacks, both global (between that of cholesterol and sterol regulatory element-binding protein 2; SREBP-2) and local internal (between substrates in the pathway) are investigated. We find that whilst the cholesterol SREBP-2 feedback regulates the overall system dynamics, local feedbacks activate within the pathway to tightly regulate the overall cellular cholesterol concentration. The network stability is analysed by constructing a reduced model of the fall pathway and is shown to exhibit one real, stable steady-state. We close by addressing the biological question as to how farnesyl-PP levels are affected by CYP51 inhibition, and demonstrate that the regulatory mechanisms within the network work in unison to ensure they remain bounded.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/74972 |
| Identification Number/DOI | 10.1016/j.jtbi.2017.12.023 |
| Refereed | Yes |
| Divisions | Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR) Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics |
| Publisher | Elsevier |
| Download/View statistics | View download statistics for this item |
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