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WIREs Syst Biol Med
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Role of systems pharmacology in understanding drug adverse events

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Abstract Systems pharmacology involves the application of systems biology approaches, combining large‐scale experimental studies with computational analyses, to the study of drugs, drug targets, and drug effects. Many of these initial studies have focused on identifying new drug targets, new uses of known drugs, and systems‐level properties of existing drugs. This review focuses on systems pharmacology studies that aim to better understand drug side effects and adverse events. By studying the drugs in the context of cellular networks, these studies provide insights into adverse events caused by off‐targets of drugs as well as adverse events‐mediated complex network responses. This allows rapid identification of biomarkers for side effect susceptibility. In this way, systems pharmacology will lead to not only newer and more effective therapies, but safer medications with fewer side effects. WIREs Syst Biol Med 2011 3 129–135 DOI: 10.1002/wsbm.114 This article is categorized under: Analytical and Computational Methods > Computational Methods Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Topological Methods

Drug effects are mediated by a drug or metabolite binding a protein target and affecting the function of the target in the context of a cellular network. The response of the cellular network can cause changes in gene expression, enzymatic activation, and ultimately tissue or organ physiology. These give rise to the observed effects of drugs. Measurements or information about any step in the information flow from drug to effects can be informative about any of the preceding steps. Systems pharmacology studies can integrate various forms of data about drug responses to identify off‐targets of drugs and predict potential adverse drug effects.

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Systems pharmacology approaches will allow clinical observations coupled with high dimensional data obtained from a patient's genomic, proteomic, and metabolomic profiles to be integrated with a systems pharmacology knowledgebase to assist clinical decision making in choosing the correct medication and appropriate dosing.

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Different strategies can be used to predict drug–target relationships. (a) Drug chemical structure can be compared to known ligands of a potential target. (b) Drug chemical structure and known target protein structure can be combined through computational docking to predict a binding site. This predicted binding site can be compared to protein structures of potential off‐targets. (c) Drugs can be computationally docked to the protein structures of potential off‐targets to generate predicted affinities and drug–target relationships.

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Analytical and Computational Methods > Computational Methods
Translational, Genomic, and Systems Medicine > Therapeutic Methods
Analytical and Computational Methods > Topological Methods

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