Construction of Cancer-Perturbed Protein–Protein Interaction Network of Apoptosis for Drug Target Discovery

Abstract

Inspecting interactive behaviors of proteins in cancer cells and comparing them with those in normal cells to obtain cancer-perturbed protein network can shed light on how a normal cell transforms into a cancer cell. Rough protein-protein interaction networks of apoptosis in cancer and normal cells are constructed according to human yeast-two-hybrid data sets and websites. The nonlinear stochastic model, maximum likelihood parameter estimation, and Akaike Information Criteria (AIC) are employed to reduce high false-positive rates in these large-scale interactome. By comparing protein-protein interaction networks of apoptosis between He La cancer cells and normal cells, we obtain cancer-perturbed networks and gain insight into the mechanism of apoptotic network in human cancer, which helps discovery of cancer drug targets. This proposed method could be extended to construct other perturbed protein interaction networks of cancer cells such as perturbated protein interaction network of cell cycle.