Latest evaluation and validation of cancer drugs and their targets has demonstrated the lack and inadequate development of new and better drugs, based on available protocols. Even though the specificity of drug targets is a great challenge in the pharmaco-proteomics field of cancer biology, for eradicating such hurdles and paving the way for the drugs of future, a novel step has been envisaged here to study the relation between drug target network and the corresponding drug network using the advanced concepts of proteomics and network biology. The literature mining was done for the collection of receptors and the ligands. About 1000 natural compounds were collected and out of those 300 molecules showed anti-cancer activity against colon cancer. Ligand Vs multiple receptor docking was done using the software Quantum 3.3.0; the results were further used for the designing of a well connected Protein Ligand Interaction (PLI) network of colon cancer. The obtained network is then extrapolated to sort out the receptors expressed in the specific cancer type. The network is then statistically analyzed and represented by the graphical interpretation, in order to ascertain the hub nodes and their locally parsed neighbours. Based on the best docking scores, the graphs obtained from the docking analysis are statistically validated with the help of VisANT. In the network three hub nodes Neutrophil cytosol factor 2, UV excision repair protein RAD23 homolog A, & Receptor-type tyrosine-protein phosphatase eta were identified, which showed the highest interaction with the ligands. Butyrate and Farnesol showed highest interaction as ligands. Multiple Sequence Alignment was done of the binding site sequence of the drug targets to find out the evolutionary closeness of the binding sites. The phylogenetic tree was also constructed to further validate the observation. Further in-vitro and in-vivo studies needs to be done to analyse the receptor specificity and anti tumor activity of these compounds in Colon cancer
