A recent article in C&EN reports that scientists at the University of North Carolina at Chapel Hill School of Medicine and the University of California, San Francisco have developed and experimentally tested a technique to predict new target diseases for existing drugs. The team, led by Bryan L. Roth and Brian K. Shoichet, developed a computational method that compares how similar the structures of all known drugs are to the naturally occurring ligands of disease targets within cells. In their study, the scientists showed that the method predicts potential new uses as well as unexpected side effects of approved drugs.
Many of the most successful drugs on the market today are being prescribed for ailments that are quite different from the ones they were originally designed to treat since many drugs have been found to bind to multiple targets. Sometimes these interactions lead to new uses for well established drugs. At other times, they may cause harmful side effects. Either way, knowing about these interactions allows for better use of drugs.
In the new method, drug receptors are not defined by structure or sequence but by the ligands that bind to them. This approach differs from structure-based approaches which usually use a receptor’s crystal structure as a starting point.
“This approach uncovered interactions between drugs and targets that we never could have predicted simply by looking at the chemical structures,” said senior study author Bryan Roth, M.D., Ph.D., professor of pharmacology and director of the National Institute of Mental Health Psychoactive Drug Screening Program at UNC. “We may now have a way to predict what side effects are likely to occur from treatment before we even put a drug into clinical testing.” internetchemistry.com
By using a modified version of an already established algorithm used to search gene-sequence databases, compounds were screened against a database of targets, asking how much the compounds looked like the ligands. The team compared 3,665 approved or investigational drugs with hundreds of targets which were defined by their ligands. The researchers predicted thousands of unanticipated interactions and experimentally tested 30 of them. Of these 30, they confirmed 23 of the interactions.
In one case, the team found that Rescriptor, which inhibits the enzyme HIV reverse transcriptase, also inhibited the histamine H4 receptor. The scientists have linked Rescriptor binding to histamine H4 at physiologically relevant concentrations to some of the painful side effects that the drug has. In another example, the antidepressant Prozac, whose primary target is the serotonin transporter, bound the beta-1 adrenerfic receptor, a G-protein-coupled receptor (GPCR) that usually binds such compounds as epinephrine and norepinephrine.
Roth states that the power of their approach is that it can be used to uncover the real targets of pharmaceutical compounds quickly and efficiently, and will probably lead to a greater understanding of the many molecular targets of each drug. Consequently, this new method will be an important step forward for chemists to design drugs that act on multiple targets.