Characterizing the network of drugs and their affected metabolic subpathways

PLoS One. 2012;7(10):e47326. doi: 10.1371/journal.pone.0047326. Epub 2012 Oct 24.


A fundamental issue in biology and medicine is illustration of the overall drug impact which is always the consequence of changes in local regions of metabolic pathways (subpathways). To gain insights into the global relationship between drugs and their affected metabolic subpathways, we constructed a drug-metabolic subpathway network (DRSN). This network included 3925 significant drug-metabolic subpathway associations representing drug dual effects. Through analyses based on network biology, we found that if drugs were linked to the same subpathways in the DRSN, they tended to share the same indications and side effects. Furthermore, if drugs shared more subpathways, they tended to share more side effects. We then calculated the association score by integrating drug-affected subpathways and disease-related subpathways to quantify the extent of the associations between each drug class and disease class. The results showed some close drug-disease associations such as sex hormone drugs and cancer suggesting drug dual effects. Surprisingly, most drugs displayed close associations with their side effects rather than their indications. To further investigate the mechanism of drug dual effects, we classified all the subpathways in the DRSN into therapeutic and non-therapeutic subpathways representing drug therapeutic effects and side effects. Compared to drug side effects, the therapeutic effects tended to work through tissue-specific genes and these genes tend to be expressed in the adrenal gland, liver and kidney; while drug side effects always occurred in the liver, bone marrow and trachea. Taken together, the DRSN could provide great insights into understanding the global relationship between drugs and metabolic subpathways.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adrenal Glands / drug effects
  • Bone Marrow / drug effects
  • Drug-Related Side Effects and Adverse Reactions*
  • Gene Expression Regulation / drug effects
  • Humans
  • Kidney / drug effects
  • Liver / drug effects
  • Metabolic Networks and Pathways / drug effects*
  • Models, Biological
  • Pharmacology
  • Trachea / drug effects

Grant support

This work was supported in part by the National Natural Science Foundation of China grant nos. 61170154 and 61073136) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (grant nos. 20102307120027 and 20102307110022). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.