13.01.20
University research could help people quit smoking
A new study led by scientists from the University of Bristol has revealed how neuroreceptors responsible for addiction, respond to nicotine.
Nicotine is extremely addictive, making it hard to quit smoking and as a result, adding pressure on the NHS. The habit claims the lives of more than seven million people each year, with many more receiving treatments for smoke-related illnesses.
The tobacco in a cigarette delivers nicotine to the neuroreceptors, and thanks to this new study into the molecular interactions, how the neuroreceptors respond to nicotine has been revealed.
By using new computational simulation methods, scientists have been able to discover how receptors respond, and more importantly, at unprecedented speeds.
The use of Oracle Cloud Infrastructure in the study meant that a large number of simulations could be run, in a very short amount of time.
Calculations that might otherwise have taken months to complete were finished in a matter of days, bringing new hope for researchers looking for cessation aids.
Co-author of the study, Professor Adrian Mulholland, from Bristol’s Centre for Computational Chemistry, part of Bristol’s School of Chemistry, said:
“Nicotine is highly addictive: it’s very hard to give up smoking. To understand why it is so addictive, and to make molecules to help people quit, we need to understand how it affects the nervous system.
“We have used simulations to model and understand how nicotine affects receptors in the brain. Using the power of cloud computing, we were able to show how nicotine exerts its effects, at the molecular level, the first stage of signalling in the brain. This information, and the methods we have developing, will help in developing new smoking cessation aids.”
The study saw researchers perform 450 individual molecular dynamics simulations of the biochemistry associated with the binding of nicotine to a subtype of nicotinic acetylcholine receptors in the brain. They were able to compare with other types nicotine receptor and identify common features of receptor activation.
The quick timescale of producing this data means that future design and development of effectively drugs can be accelerated dramatically.