PHILADELPHIA - Biophysicists at the University of Pennsylvania have used 3,200 computer processors and long-established data on cholesterol's role in the function of proteins to clarify the mysterious interaction between cholesterol and neurotransmitter receptors. The results provide a new model of behavior for the nicotinic acetylcholine receptor, a well studied protein involved in inflammation, Alzheimer's disease, Parkinson's disease, schizophrenia, epilepsy, the effect of general anesthetics and addiction to alcohol, nicotine and cocaine.
Moreover, the results apply to closely related receptors that bind serotonin and GABA, which are neurotransmitters directly involved in regulation of mood and sleep.
The findings have broad implications for, among other fields, pharmacology. Drug development in this arena has to take into account the structure and chemical makeup of this receptor, both of which researchers now say were incomplete. Drugs acting on the receptor have been thought to interact with the protein as though it were isolated.
Now, researchers believe that drugs binding to the receptor not only interact with amino acids the building blocks of the protein receptor but also cholesterol tucked away within the protein. The shift in thinking transforms the understanding of this receptor in many ways, from shape and structure to its interaction with its environment and its response to neurotransmitters. The new model should spark a reexamination of several decades of research on the receptor's structure and function.
Researchers demonstrated that the receptor, also know as nAChR, contains internal sites capable of containing cholesterol which serve to stabilize the protein's structure. Furthermore, molecular simulations revealed that both surface sites and deeply buried sites within the protein require cholesterol, which directly supports contacts between the agonist-binding domain and the pores that are thought to
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| Contact: Jordan Reese jreese@upenn.edu 215-573-6604 University of Pennsylvania Source:Eurekalert |