Researchers have developed a screening tool for discovering unexpected effects that drugs may have on living cells. It could provide a better way of identifying both potential side effects of and applications for new drugs – and take the serendipity out of the drug discovery process.
Published in the current issue of the journal Nature Chemical Biology, the new tool combines modern chemical screening techniques with computer analysis. Using it, pharmaceutical companies could get an early snapshot of the potential uses and possible side effects of particular drugs, says Stephen Michnick, who heads a laboratory at the Department of Biochemistry at the University of Montreal. One of the primary researchers on the project, Michnick developed the technique with John Westwick, president and chief scientific officer at Odyssey Thera in San Ramon CA, which specializes in using mass-screening techniques in drug discovery.
Most drugs work by interacting with target proteins to influence their effect on biochemical pathways within cells. But because these pathways and their interactions are complex, a drug can often have side effects – beneficial or toxic. To ferret out these effects, drugs nowadays are usually screened one target protein at a time, says Graeme Milligan, a molecular pharmacologist at the Institute of Biomedical and Life Sciences, University of Glasgow. Although it works, this approach can be costly for the pharmaceutical industry. “Potentially toxic and off-target effects are generally not discovered until a later stage,” he says, after a lot of time, money, and effort have been spent.
Instead, by profiling and comparing more than 100 known drugs, this latest research showed that many drugs could be grouped based on the way they influenced cells – rather than on their structure or the proteins they were targeting. Using this methodology, the researchers profiled the antidepressant sertraline, for example, showing that its profile for certain biochemical pathways was similar to many anti-cancer drugs, says Michnick.
The research analysed the way individual pairs of proteins interact in healthy cultured cells, by introducing engineering proteins that would bind to each pair and glow whenever they interact. The scientists were then able to use automated screening techniques to measure these interactions and where in the cell they occurred.
By comparing the normal responses of these pairs of proteins with those exposed to a particular drug, they built a picture of how that drug influenced the stages of each biochemical pathway. The researchers then used a simple computer model to categorize the drugs according to how they influenced these pathways. This allowed them to compare and ultimately predict the overall effect each of these existing drugs would have on cells. For example, four existing drugs currently not used for treating cancer were found to be grouped together with cancer-inhibiting drugs, suggesting that they had similar effects on inhibiting cancer growth, which was later verified.