Journal
MOLECULAR SYSTEMS BIOLOGY
Volume 4, Issue -, Pages -Publisher
WILEY
DOI: 10.1038/msb.2008.53
Keywords
combination therapy; network dynamics; network pharmacology; synthetic biology
Categories
Funding
- EMBO
- PE Lindahl foundation (SN)
- Goteborg University
- Swedish Strategic Research Foundation
- Matt's Promise Foundation (CS)
Ask authors/readers for more resources
We present a novel method for deriving network models from molecular profiles of perturbed cellular systems. The network models aim to predict quantitative outcomes of combinatorial perturbations, such as drug pair treatments or multiple genetic alterations. Mathematically, we represent the system by a set of nodes, representing molecular concentrations or cellular processes, a perturbation vector and an interaction matrix. After perturbation, the system evolves in time according to differential equations with built-in nonlinearity, similar to Hopfield networks, capable of representing epistasis and saturation effects. For a particular set of experiments, we derive the interaction matrix by minimizing a composite error function, aiming at accuracy of prediction and simplicity of network structure. To evaluate the predictive potential of the method, we performed 21 drug pair treatment experiments in a human breast cancer cell line (MCF7) with observation of phospho-proteins and cell cycle markers. The best derived network model rediscovered known interactions and contained interesting predictions. Possible applications include the discovery of regulatory interactions, the design of targeted combination therapies and the engineering of molecular biological networks.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available