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A computational method originally designed to identify new drug targets on the basis of similarity between small-molecule structures can also predict targets responsible for side effects and adverse drug reactions (Nature, DOI: 10.1038/nature11159). Brian K. Shoichet of the University of California, San Francisco; Laszlo Urban of the Novartis Institutes for Biomedical Research, in Cambridge, Mass.; and coworkers used the similarity ensemble approach algorithm to predict binding between 656 drugs and 73 known side-effect targets. The algorithm identified 1,644 potential interactions, some of which were already known. The researchers tested 694 of the unknown interactions and found that many drugs affected multiple off-targets, often ones that are unrelated to the therapeutic target by either sequence or structure. For example, chlorhexidine, the most promiscuous drug tested, hit 34 of 54 targets against which it was tested. Chlorotrianisene, whose therapeutic target is the estrogen receptor, also hits the cyclooxygenase-1 enzyme, an interaction that is consistent with the drug’s upper abdominal pain side effect. The method could be used to identify potential liabilities of drugs early in the development process, the researchers note.
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