Estimation of Drug Treatment Effects on the Signaling Pathways

Abstract

Developing a computational method to observe cell behaviors can help to understand the expected outcome of a drug treatment even before doing the wet-lab experiments. The main goal of this research is computing the effects of a drug treatment in the signaling level for a better understanding of cellular responses after a drug treatment. The proposed algorithm can work on various biological networks to quantitatively evaluate the effects of a drug treatment in the cell by using gene expression data. The method was applied on the integrated KEGG signaling pathway and the most effected proteins were identified after the application of 14 different drugs on lymphoma cells. The results showed that the most affected proteins are not the direct target proteins of the given drugs. Indeed, the protein activities in the distant parts of signaling pathways are highly changed upon drug treatments. The literature validation showed that some of the proteins, which are commonly effected by the treatment of several drugs, have cancer related cellular activities as well.