An international research collaboration led by scientists at the University of North Carolina at Chapel Hill and the University of Dundee in Scotland has developed a way to efficiently and effectively make designer drugs that hit multiple protein targets at once.
This accomplishment, described in the December 13, 2012, issue of the journal Nature, may prove invaluable for developing drugs to treat many common diseases such as diabetes, high blood pressure, obesity, cancer, schizophrenia, and bipolar disorder. Such disorders are called complex diseases because each has a number of genetic and non-genetic influences that determine whether someone will develop the disease.
“In terms of the genetics of schizophrenia, we know there are likely hundreds of different genes that can influence the risk for disease and, because of that, there’s likely no single gene and no one drug target that will be useful for treating it, like other common complex diseases,” says study co-leader Bryan Roth, MD, PhD, the Michael J. Hooker Distinguished Professor of Pharmacology in the UNC School of Medicine, a professor in the Division of Chemical Biology and Medicinal Chemistry in the UNC Eshelman School of Pharmacy, and the director of the National Institute of Mental Health Psychoactive Drug Screening Program.
Roth says that drug design for complex neuropsychiatric conditions, infectious diseases, and cancer has been selectively aimed at a single molecular target in the past twenty years, but because these are complex diseases, the drugs are often ineffective and thus many never reach market.
Moreover, a drug that acts on a single targeted protein may interact with many other proteins, frequently causing toxicity and adverse effects.
“And so the realization has been that perhaps one way forward is to make drugs that hit collections of drug targets simultaneously. This paper provides a way to do that,” Roth says.
According to Roth, pharmaceutical company chemists had suggested that it was impossible to create a drug that hits multiple targets simultaneously, but “here we show how to efficiently and effectively make designer drugs that can do that.”
The new approach involves automated drug design by computer that takes advantage of large databases of drug-target interactions. The databases 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, at the University of Dundee, 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 diseases.
The team experimentally tested eight hundred drug-target predictions of the computationally designed compounds. Of those, 75 percent were confirmed in in-vitro experiments.
Drug-to-target engagement also was confirmed in animal models of human diseases. In a mouse model of attention deficit hyperactivity disorder, mice missing a particular dopamine receptor display distractibility and novelty seeking—recurrent aberrant behaviors similar to what is seen in ADHD. “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, also resulting in distractibility and novelty seeking. 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, which was also successfully tested in live animals.
Along with Roth, other UNC researchers among the study’s twenty-one co-authors include Vincent Setola, Xi-Ping Huang, and Maria F. Sassano. Other co-authors are from the University of Dundee, the Duke University Medical School, the Clinical Research Institute of Montreal, and the Swiss Federal Institute of Technology.
Part of the funding for the research comes from the National Institutes of Health grants supporting drug discovery receptor pharmacology.