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Computational Studies of the Biogenic Amines of the Brain for Targeting Neurological Diseases

Principal investigator

Project type
Znanstveno-istraživački projekti
Financier
European Union
Start date
Apr 1st 2013
End date
Mar 31st 2017
Status
Done
Total cost
100000 EUR
More information

The main purpose of this computational research is to improve the understanding of a relation between features, metabolic pathways and signal transduction of amine neurotransmitters and the treatment of neurological diseases. Brain monoaminergic systems have been extensively implicated in the etiology and course of various neurodegenerative disorders, and their binding proteins such as receptors, transporters and common metabolic enzymes are the starting points for development of tools to diagnose and drugs to treat specific clusters of symptoms. Therefore, the research described here will be focused on two particular biological systems: monoamine oxidase enzymes (MAOs) responsible for regulating amine levels in the synaptic region, and histamine H1 and H2 receptors that regulate the activity of allergic and inflammatory mediator histamine. The work on MAO should aid in revealing molecular mechanisms of MAO-catalyzed amine degradation to their corresponding aldehydes, as well as of irreversible MAO inhibition related to the pharmacotherapy of depression, Parkinson disease and age-related cognitive disorders. This should help improve efficiency and reduce adverse effects of commercially available drugs, and should suggest novel classes of active compounds as transition state analogues. In joint computational/experimental efforts, studies on histamine receptors should unlock the secrets of receptors distinction between agonist and antagonist binding using receptor deuteration, being of major relevance for molecular pharmacology. Overall, it is intended to identify ubiquitous trends and features that are applicable well beyond the scopes of these individual investigations. The proposed research is in general highly interdisciplinary with the promise of industrial applications, since it bridges the gap between fundamental understanding of biological systems and preclinical medicine combining modern methods of computational biochemistry with pharmacological approaches.

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