Cancer is the only disease that is a severe threat and a dark fear to mankind for many centuries. Cancer being a highly complex combination of diseases, it can be studied and understood better by the complex networks in Systems Biology & Network pharmacology approach. Here is a novel step to study the relation between drug target network and the corresponding drug network using the advanced concept of proteomics and systems biology and to develop an effective strategy for cancer prevention. We constructed gene co-expression networks and identified the globally cancer-related genes by network structure analysis. To study the properties of networks, modules were identified and their functions and roles were investigated. Our results showed that the inferred networks were structurally conservative and the identified modules were highly overlapped between various data sets. From this network the different interactions of the ligands and the proteins were observed. From the data obtained and the various analysis done the antimutagen Beta-Sitosterol obtained from the Black cumin Seeds (Nigella Sativa) shows least RMSD value with the protein 2I1J corresponding to the gene UTP14A.