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Deciphering the Role of Gamma-amino butyric Acid in Epilepsy; A Multiscale Approach Using Formal Modeling and Verification

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dc.contributor.author Fazeel, Ahtisham
dc.date.accessioned 2023-08-09T07:03:52Z
dc.date.available 2023-08-09T07:03:52Z
dc.date.issued 2019-08-01
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/35930
dc.description.abstract Background: Epileptic seizures are known since 2000 B.C., having a high prevalence rate, are portrayed by anomalous function of brain and neurons. High throughput sequencing has made data available for the analysis of complex systems. Most of the studies have been done to explore neurological disorders, which show dysregulation of gamma amino-butyric acid. GABA is an inhibitory neurotransmitter involved in the deactivation of neurons via tripartite synapse. Anomalies in the GABAergic processes can lead to the synchronous firing of the neurons which marshals towards the abnormal behaviors like Epileptic seizures and Huntington’s Disease etc. In addition to the crucial importance of GABA in neurological disorders it has been reported that it plays an important role in regulating glucagon in IELTS of Langerhans, sometimes leading to weakened muscles and diabetes etc. However, the role of GABA in such anomalistic systems have been poorly understood. To undermine the roles of GABA in a tripartite synapse and some other cells, a systems biology approach employing Qualitative Modeling method is used. Behavior of the system is dependent on certain parameters which are required to study the dynamics of the system, These are computed first in qualitative modeling based on the logics of René Thomas. Moreover, in addition to this, stability of the system is analyzed with the important parameters involved in the fixing of system; which can even act as potential therapeutic target as well. Methodology: Our works is based on the construction and analyses of GABAergic systems by the assistance of Knowledge driven objectives; where an overall GABAergic synapse is constructed using Literature mining techniques as well. Four different natural administrative systems are formulated based on the functionality of GABA i.e. i) Inhibitory role of GABA (Compartment level), ii) Inhibitory role of GABA (Macro level), iii) GABAergic role in elucidating glucagon, iv) GABAergic roles in chronic seizures. After the formulation of Biological regulatory network specifically for each of the abovexviii List of Figures mentioned, static analysis is done to find out stable states of each system using Pypint process hitting (Python). SMBioNet is used to calculate list of all logical parameters taking the system towards deadlocks or stable states by specifying system’s property in CTL. GenotechE, codes written in Java and Cytoscape are used to get state graph and path leading to deadlock state on the basis of betweenness centrality. Hybrid modeling is done by HyTECH in the form of Bio-Linear Hybrid automaton to get production and degradation delays relevant to each state. These delays are manipulated in the form of relation matrix by using Pyconstraint library (Python). Hybrid Modeling results are confirmed by stochastic petri net simulations and potential mixed therapies are proposed. Results: Our results indicate that the low levels of positive ions Ca2+ or K+ in presynaptic neuron, lead towards low hyperpolarization, whereas in spite of effecting presynaptic neuron these ions are involved in creating positive ionic gradient in post synaptic neuron. Inhibition of FOXO gene and over activation of MTORs by GABA causes diabetic issues and weakened muscles whereas in the case of chronic seizures OCTNs complex causes the over-activation of Rest transcription causing problems in regulation of KCCb2 leading to chronic seizures. Our results confirm previous experimental findings and some new observations as mentioned earlier. Moreover these findings can be validated using computer aided drug designing. Conclusion: Based on various modelling approaches and analyzing the biological regulatory mechanisms of various pathways. We are able to identify different targets for the treatment of epileptic seizures and diseases associated with glucagon disturbance i-e. Diabetes. For the treatment of generalized epileptic seizure we have identified a mixed therapy in which agonist can be designed for VGCC presynaptic neuron and antagonists for KCCb2 and GABAB on postsynaptic neuron. To treat diseases associated with glucagon disturbance agonists for FOXO and antagonists for Akt can be delineated. At last for chronic seizures OctNs complex can be targeted to minimize the chances of disturbance in Chloride ions in pre mature brain. en_US
dc.description.sponsorship Dr.Muhammad Tariq Saeed en_US
dc.language.iso en_US en_US
dc.publisher RCMS NUST en_US
dc.subject Gamma aminobutyric acid, Hybrid Modeling, Model Checking, Computational Tree Logic en_US
dc.title Deciphering the Role of Gamma-amino butyric Acid in Epilepsy; A Multiscale Approach Using Formal Modeling and Verification en_US
dc.type Thesis en_US


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