4.6 Review Book Chapter

Novel Computational Approaches to Polypharmacology as a Means to Define Responses to Individual Drugs

Journal

Publisher

ANNUAL REVIEWS
DOI: 10.1146/annurev-pharmtox-010611-134630

Keywords

protein-ligand interaction; drug-target network; in vivo efficacy; dynamic simulation; metabolic modeling

Funding

  1. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM078596] Funding Source: NIH RePORTER
  2. NIGMS NIH HHS [GM078596] Funding Source: Medline

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Polypharmacology, which focuses on designing therapeutics to target multiple receptors, has emerged as a new paradigm in drug discovery. Polypharmacological effects are an attribute of most, if not all, drug molecules. The efficacy and toxicity of drugs, whether designed as single-ormultitarget therapeutics, result from complex interactions between pharmacodynamic, pharmacokinetic, genetic, epigenetic, and environmental factors. Ultimately, to predict a drug response phenotype, it is necessary to understand the change in information flow through cellular networks resulting from dynamic drug-target interactions and the impact that this has on the complete biological system. Although such is a future objective, we review recent progress and challenges in computational techniques that enable the prediction and analysis of in vitro and in vivo drug-response phenotypes.

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