Although drugs are usually targeted to be selective for a single protein, it is recognized that other proteins may also be affected, a phenomenon called polypharmacology.  While off-target interactions can cause potentially harmful side-effects, in some cases, an effect on an unintended target might suggest new disease indications for established drugs. 

Chemoinformatics, statistical programs, and experimental techniques are being utilized by Brian Shoichet of the University of California San Francisco to predict off-target interactions.  Similarities between 3665 (existing and experimental) drugs and a set of over 65,000 known ligands to protein receptors in the body were examined.  In addition, the ligands were arranged into around 250 classes depending on the type of receptor to which they bind.  This exhaustive survey yielded hundreds of previously unrecognised potential interactions between drugs and protein receptors in the body.   A number of these potential interactions were confirmed by laboratory experiments, including identification of the key receptor that binds the hallucinatory drug dimethyltryptamine.

These new computational techniques should not only prove valuable to pharmaceutical companies to both expand existing pipelines and to reap additional benefits from current compounds, they should also aid researchers to anticipate and avoid unanticipated adverse events.

Source: Chemistry World

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One Response to “Computational techniques suggest new ways to find drugs’ unintended targets”

  1. Martin Griffies Says:

    Ariadne also provides a superb program to examine off-target effects mechanisms of toxicity. ChemEffect and Pathway Studio include over one million interactions between proteins, targets, indications and cellular processes.

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