Dominant negative inhibition data should be analyzed using mathematical modeling – re‐interpreting data from insulin signaling

• DOI: 10.1111/febs.13182
• Publication Date: 2014-12-24T14:10:30Z
• Authors: David Jullesson; Rikard Johansson; Meenu R. Rajan; Peter Strålfors; Gunnar Cedersund
• Keywords: Publication; Experimental data

As our ability to measure the complexity of intracellular networks has evolved, it become increasingly clear that we need new methods for data analysis: involving mathematical modeling. Nevertheless, is still uncontroversial publish and interpret experimental results without a model-based proof reasoning correct. In present study, argue this attitude probably needs change in future. We illustrate modeling by considering common technique using dominant-negative constructs. More specifically, consider published time-series dose-response which previously have been used protein S6 kinase does not phosphorylate insulin receptor substrate-1 at specific serine residue. Using presented general approach such data, now demonstrate given are conclusive (i.e. absence other proofs, may be kinase). simulations with uncertainty analysis analytical solutions, show an alternative explanation centered around depletion substrate, can tested experimentally. This thus illustrates both necessity benefits fully understand implications biological even small system relatively simple data.