Since in chemical proteomics Evodiamine Isoevodiamine the drug is always present at a large excess of constant concentration, it is only possible to distinguish the affinities of completely competed proteins by taking the protein amount into account. To down weigh this parameter influence, the logarithm is applied to pt. Thus, the affinity score can be expressed by the following equation: at 1{ pt,comp pt |lneptT e2T Due to the reduced complexity of the competed pull down, it can sporadically happen that pt,comp.pt. This case is seen as no competition and thus the affinity is set to 0. Randomization An empirical p value is calculated via randomization of the interactome. First, the interaction partners of each node are randomly selected. It is ensured that the degree of each node remains constant.
Second, the annotation is randomly assigned to the nodes, while the total number of each term is preserved. The presented algorithm is applied to 500 random instances of the interactome. The empirical p value is calculated from the fraction of randomized interactomes containing a sub network with a score GSK1904529A equal or better to the tested score divided by the total number of randominstances. The highest score of all the random instances smax, rand is 0.124. R Package The presented approach is programmed in the statistical environment R/Bioconductor and available at The provided R package depends on graph, RBGL, snow and GO.db. Parallelization is done with snow to generate and score random instances. Additionally, the above described data and the results are stored as R data objects.
Visualization and comparison Networks are visualized with Cytoscape. For comparison, classical GO/KEGG/Biocarta enrichment analysis of sets are performed with DAVID. Results and Discussion We present a novel strategy to analyze the mechanisms of action of bafetinib. The target profile is weighted with respect to its drug affinity and its impact on protein interaction networks is scored. Ten perturbed functional sub networks are scored higher than any sub network of the 500 randomized interactomes, see Table 1 and Figure 3, 4 and supplementary Figure S1, S2. The sub networks do not necessarily contain all the components of a specific function since several disjoint functional sub networks can be constructed. Bafetinib is designed to treat BCR ABL dependent chronic myeloid leukemia.
Constitutively active BCR ABL interferes strongly with apoptosis in malignant cells. We catch this process in our significantly perturbed sub networks at rank 6. Furthermore, MAP kinase signaling can also be brought together with pathogenesis and treatment of CML. The top ranked perturbation of,Epidermal growth factor receptor signaling pathways, and,Insulin receptor signaling pathway, suggest potential novel domains of treatment for bafetinib and,heart development, indicates a putative side effect. The hit signaling pathways further play important roles in the general perturbed processes of aging, extracelluar structure organization and cell cycle. Finally, phosphorylation is an obvious process to be perturbed by a kinase inhibitor. We discuss pathogenesis, potential new domains of drug treatment and putative side effects of bafetinib in more details. Inactivated apoptosis sig