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.