Mathematical modelling of GPCR-mediated calcium signalling

Majin, Wodu (2012) Mathematical modelling of GPCR-mediated calcium signalling. PhD thesis, University of Nottingham.

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Abstract

Ca2+ is an important messenger which mediates several physiological functions, including muscle contraction, fertilisation, heart regulation and gene transcription. One major way its cytosolic level is raised is via a G-protein coupled receptor (GPCR)- mediated release from intracellular stores. GPCR’s are the target of approximately 50% of all drugs in clinical use. Hence, understanding the underlying mechanisms of signalling in this pathway could lead to improved therapy in disease conditions associated with abnornmal Ca2+ signalling, and to the identification of new drug targets. To gain such insight, this thesis builds and analyses a detailed mathematical model of key processes leading to Ca2+ mobilisation.

Ca2+ signalling is considered in the particular context of the M3 muscarinic receptor system. Guided by available data, the Ca2+ mobilisation model is assembled, first by analysing a base G-protein activation model, and subsequently extending it with downstream details. Computationally efficient designs of a global parameter sensitivity analysis method are used to identify the key controlling parameters with respect to the main features of the Ca2+ data. The underlying mechanism behind the experimentally observed, rapid, amplified Ca2+ response is shown to be a rapid rate of inositol trisphosphate (IP3) formation from Phosphatidylinositol 4,5-bisphosphate (PIP2) hydrolysis. Using the same results, potential drug targets (apart fromthe GPCR) are identified, including the sarco/endoplasmic reticulum Ca2+-ATPase (SERCA) and PIP2. Moreover, possible explanations for therapeutic failures were found when some parameters exerted a biphasic effect on the relative Ca2+ increase.

The sensitivity analysis results are used to simplify the process of parameter estimation by a significant reduction of the parameter space of interest. An evolutionary algorithm is used to successfully fit the model to a significant portion of the Ca2+ data. Subsequent sensitivity analyses of the best-fitting parameter sets suggest that mechanistic modelling of kinase-mediated GPCR desensitisation, and SERCA dynamics may be required for a comprehensive representation of the data.

Item Type:Thesis (PhD)
Supervisors:Owen, M.
Hill, S.J.
King, J.R.
Faculties/Schools:UK Campuses > Faculty of Science > School of Mathematical Sciences
ID Code:2451
Deposited By:Wodu Majin
Deposited On:28 Sep 2012 11:10
Last Modified:28 Sep 2012 11:10

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