The new way involves automated drug design by computer that takes advantage of large databases of drug-target interactions. The latter have been made public through Roth's lab at UNC and through other resources.
Basically, the researchers, also co-led by Andrew L. Hopkins, PhD in the Division of Biological Chemistry and Drug Discovery, College of Life Sciences, at the University of Dundee, in Scotland, used the power of computational chemistry to design drug compounds that were then synthesized by chemists, tested in experimental assays and validated in mouse models of human disease.
The study team experimentally tested 800 drug-target predictions of the computationally designed compounds; of these, 75 percent were confirmed in test-tube (in vitro) experiments.
Drug to target engagement also was confirmed in animal models of human disease. In a mouse model of attention deficit hyperactivity disorder (ADHD), mice missing a particular dopamine receptor engage in recurrent aberrant behaviors similar to what is seen in ADHD: distractibility and novelty seeking. "We created a compound that was predicted to prevent those recurrent behaviors and it worked quite well," Roth said.
The researchers then tested the compound in another mouse model where a particular enzyme for a brain neuropeptide is missing. Distractibility and novelty seeking also are behavioral features in these animals. And the drug had the same effect in those mice.
The new drug design process includes ensuring that compounds enter the brain by crossing the blood-brain barrier. These, too, were tested successfully in live animals.
According to Roth, pharmaceutical company chemists had suggested that the objective of a drug hitting multiple targets simultaneously is impossible and unlikely to succeed. "Here we show how to efficiently and effectively make designer drugs
|Contact: Les Lang|
University of North Carolina Health Care