Breast cancer is the second most common types of cancer worldwide. Molecular strategies have developed rapidly; however, novel treatments strategies with high efficacy and lower toxicity are still urgently demanded. Notably, biological networks estimated from microarray data and functional activity network analysis could be utilized to identify and validate potential targets. In this study, two microarray data (GSE13477, GSE31192) were firstly selected, and analyzed by multi-functional activity network analysis to generate the core protein-protein-interaction (PPI) network. Several potential targets were subsequently identified and c-Met and poly (ADP-ribose) polymerase-1 (PARP-1) were manually chosen as the key targets in breast cancer. Furthermore, virtual screening and molecular dynamics (MD) simulations were utilized to recognize novel c-Met/PARP-1 inhibitors in Specs products database. Three small molecules, namely, ZINC19909930, ZINC20032678 and ZINC13562414 were selected. Additionally, these compounds were synthesized, and two breast cancer cell lines, MDA-MB-231 and MCF-7 cells were used to validate our bioinformatic findings in vitro. MTT assay and Hoechst staining showed that ZINC20032678 significantly induced breast cancer cell death, which was mediated through apoptosis by flow cytometry. Furthermore, ZINC20032678 was shown to target the active sites of the both targets and recruitment of downstream apoptotic signaling pathways, eventually inducing breast cancer cell apoptosis. Collectively, our findings not only offer systems biology approaches based drug target identification, but also provide the new clues for developing novel inhibitors for future breast cancer research.
Keywords: PARP-1; apoptosis; breast cancer; c-Met; drug discovery; systems biology.
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