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New mathematical model may hasten drug development for Parkinson's Disease

Published on November 19, 2009 at 1:52 AM · No Comments

Australian scientists have significantly advanced our understanding of dopamine release from nerve cells, findings that should speed the development of more effective drugs for treating Parkinson's Disease.

People with Parkinson's Disease suffer from muscle rigidity, tremor, a slowing of physical movement and, in extreme cases, a loss of physical movement. These primary symptoms are caused by the loss of dopamine producing nerve cells in the brain.

Medicines used for treating Parkinson's either provide extra dopamine or attach to the remaining nerve cells that release dopamine and regulate its release. In the latter case, no-one understands the mechanisms involved, or how to control them.

When an electrical impulse reaches the end of a dopamine nerve cell, called a synapse, it sometimes stimulates the release of dopamine. Yet more often it doesn't. Only about 1 in 5 impulses cause dopamine release, and the release rhythm is irregular. So the cell might release dopamine 5 times in a row, then not release twice, then release once, and so on.

Neuroscientists at Sydney's Garvan Institute of Medical Research have developed a mathematical model and microscopy method that reveal the mechanisms behind synaptic dopamine release - and the factors that govern the probability of release.

These important findings, made by Drs James Daniel and Bryce Vissel, are now published online in the Journal of Neuroscience.

"While there has been an enormous amount of effort put into the development of drugs for Parkinson's Disease, very little has been known about how the dopamine releasing drugs achieve their effects, other than the fact they attach to a receptor on a dopamine nerve cell, and then something happens," said Dr Vissel.

"We know that there's an intrinsic probability of the release of a neurotransmitter, but what's really interesting is that this release probability is regulated. A neuron can make it more likely or less likely that a neurotransmitter will be released, but it can't guarantee release. For example, it becomes more likely that a neurotransmitter will be released in a nerve pathway that is used a lot."

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