Scientists create artificial genes to determine cellular responses to drugs

The technology of scientists consists of a set of “biosensors”. They are artificial genes that

can be introduced into cells to report inreal time when an important group of signaling molecules is turned on. These signaling molecules, G proteins, are molecular switches in cells. They include a large family of receptor proteins that recognize a very wide range of stimuli, including light, smells, neurotransmitters, and hormones.

This signaling mechanism has been studied for several decades. However, the “new biosensors” are designed to study G-proteins with accuracy that was not possible before.

Scientists call them "spies" - they cantell researchers everything that G-proteins do in real time, but without interfering with the observed signaling process. Moreover, biosensors have an advantage in ease of implementation, which allows scientists to study G-proteins directly in experimental systems that were previously unavailable.

Researchers Used Molecular Engineeringto create biosensors. They borrowed parts from existing genes, including those that encode fluorescent proteins in jellyfish; also proteins that cause muscles to contract, light-emitting proteins from deep-sea shrimp, and proteins that specifically recognize active G-proteins. Scientists then presented engineered genes that convert biosensors into several different types of cells, and studied how they respond to stimulation with natural stimuli — neurotransmitters or clinically used drugs.

According to researchers, more than a third of approvedThe FDA (U.S. Food and Drug Administration) uses drugs to activate or inhibit G-protein signaling, including conventional allergy medications, nasal medications, and often prescribed blood pressure medications. In addition, these drugs include those that are used to treat Parkinson's disease, as well as analgesics, antipsychotics and opioids.

Scientists believe that these "biosensors" may beuseful for the discovery and development of new drugs, as well as for a more complete understanding of the principles of action of many existing drugs. Researchers will be able to more easily and accurately identify drugs that are more likely to be successful in clinical trials. Now, many drugs that initially show promise in experimental systems do not ultimately produce clinical results.

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