By analyzing drug-induced changes in disease-specific patterns of gene expression, a new algorithm called DeMAND identifies the genes involved in implementing a drug's effects. The method could help predict undesirable off-target interactions, suggest ways of regulating a drug's activity, and identify novel therapeutic uses for FDA-approved drugs, three critical challenges in drug development.
Researchers in the Columbia University Department of Systems Biology have developed an efficient and accurate method for determining a drug’s mechanism of action — the cellular machinery through which it produces its pharmacological effect. Considering that most drugs, including widely used ones, act in ways that are not completely understood at the molecular level, this accomplishment addresses a key challenge to drug development. The new approach also holds great potential for improving drugs’ effectiveness, identifying better combination therapies, and avoiding dangerous drug-induced side effects.
According to Andrea Califano, the Clyde and Helen Wu Professor of Chemical Systems Biology and co-senior author on the study, “This new methodology makes it possible for the first time to generate a genome-wide footprint of the proteins that are responsible for implementing or modulating the activity of a drug. The accuracy of the method has been the most surprising result, with up to 80% of the identified proteins confirmed by experimental assays.”