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Updated: Jun 19, 2026
07:57
Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
Published on: August 21, 2019
Drug effects viewed from a signal transduction network perspective
Anton F Fliri1, William T Loging, Robert A Volkmann
1Pfizer Global Research and Development, CT, USA.
Journal of Medicinal Chemistry
|November 7, 2009
Summary
This study reveals that drugs with similar effects target similar protein networks. Analyzing drug-protein interactions helps predict drug pharmacology and build network models for medicine discovery.
Area of Science:
- Pharmacology
- Systems Biology
- Network Science
Background:
- Understanding drug mechanisms requires linking cellular network changes to observed effects.
- Investigating the relationship between drug pharmacology and protein network interactions is crucial for drug discovery.
Purpose of the Study:
- To determine protein network structures associated with specific in vivo drug effects.
- To explore the cause-effect relationship between drug actions and cellular network alterations.
- To identify medicines with similar pharmacology by comparing drug-effect profiles and protein network interactions.
Main Methods:
- Compared drug-effect profiles of 1320 medicines.
- Analyzed coinvestigation frequency of medicines and 1179 protein network constituents across millions of scientific investigations.
- Constructed drug-mediated protein network topology models using protein associations and curated interaction data.
Main Results:
- Medicine associations derived from drug-effect profiles mirrored those from drug-protein coinvestigation frequency profiles.
- Demonstrated the relevance of drug-protein reachability profiles to in vivo pharmacology.
- Revealed that drugs with similar pharmacology profiles occupy similar positions within cellular protein networks.
Conclusions:
- Drug-protein reachability profiles are valuable for understanding in vivo pharmacology.
- Protein network topology models offer a systems-level view of drug cause-effect relationships.
- This approach facilitates the discovery of medicines by mapping drug actions onto cellular networks.
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