Network-based prediction of drug combinations
Northeastern University · Cleveland Clinic Lerner College of Medicine · +4 more institutions
Abstract
Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an important role in treating multiple complex diseases. Yet, our ability to identify and validate effective combinations is limited by a combinatorial explosion, driven by both the large number of drug pairs as well as dosage combinations. Here we propose a network-based methodology to identify clinically efficacious drug combinations for specific diseases. By quantifying the network-based relationship between drug targets and disease proteins in the human protein-protein interactome, we show the existence of six distinct classes of drug-drug-disease combinations. Relying on approved drug combinations for hypertension and…
Citation impact
- FWCI
- 91.78
- Percentile
- 100%
- References
- 56
Authors
3- FCFeixiong ChengCorresponding
Northeastern University, Cleveland Clinic Lerner College of Medicine, Dana-Farber Cancer Institute, Case Western Reserve University
- IKI. Kovács
Northeastern University, Dana-Farber Cancer Institute
- ABAlbert-Ĺaszló Barabási
Brigham and Women's Hospital, Northeastern University, Central European University, Dana-Farber Cancer Institute
Topics & keywords
- Drug
- Interactome
- Drug repositioning
- Disease
- Computational biology
- Drug development
- Drug response
- Drug discovery
- Good health and well-being