| Summary: | Understanding the mechanisms of cell function and drug action is a major endeavor in
the pharmaceutical industry. Drug effects are governed by the intrinsic properties of the
drug (i.e., selectivity and potency) and the specific signaling transduction network of the
host (i.e., normal vs. diseased cells). Here, we describe an unbiased, phosphoproteomicbased
approach to identify drug effects by monitoring drug-induced topology alterations.
With the proposed method, drug effects are investigated under several conditions on a
cell-type specific signaling network. First, starting with a generic pathway made of
logical gates, we build a cell-type specific map by constraining it to fit 13 key
phopshoprotein signals under 55 experimental cases. Fitting is performed via a
formulation as an Integer Linear Program (ILP) and solution by standard ILP solvers; a
procedure that drastically outperforms previous fitting schemes. Then, knowing the cell
topology, we monitor the same key phopshoprotein signals under the presence of drug
and cytokines and we re-optimize the specific map to reveal the drug-induced topology
alterations. To prove our case, we make a pathway map for the hepatocytic cell line
HepG2 and we evaluate the effects of 4 drugs: 3 selective inhibitors for the Epidermal
Growth Factor Receptor (EGFR) and a non selective drug. We confirm effects easily
predictable from the drugs’ main target (i.e. EGFR inhibitors blocks the EGFR pathway)
but we also uncover unanticipated effects due to either drug promiscuity or the cell’s
specific topology. An interesting finding is that the selective EGFR inhibitor Gefitinib is
able to inhibit signaling downstream the Interleukin-1alpha (IL-1α) pathway; an effect
that cannot be extracted from binding affinity based approaches. Our method represents
an unbiased approach to identify drug effects on a small to medium size pathways and
is scalable to larger topologies with any type of signaling perturbations (small molecules,
3
RNAi etc). The method is a step towards a better picture of drug effects in pathways,
the cornerstone in identifying the mechanisms of drug efficacy and toxicity.
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