All the 10 drug combinations are used to treat breast cancer except the one used for treating gastric cancer. Additionally, 8 drug combinations target related pathways, while the other two target different unrelated pathways or cross talking pathways. Finally, these kinase inhibitor Ceritinib results, together with the consistent findings shown in Figure 3, strongly indicate that star drugs tend to have similar therapeutic characteristics as their neighbors. In addition, we investigated the proteins targeted by the 13 hub drugs in the drug cocktail network that have target information. By mapping all proteins targeted by the drugs in the drug cocktail network to the human protein protein interaction network retrieved from STRING database, we found that, in terms of the shortest distance between target proteins, hub drugs tend to have a closer relationship with their combina tion partners than the drugs having similar ATC codes.

Furthermore, we analyzed the cellular localizations of these target proteins of the 13 hub drugs. More than 70% of the target proteins of the hub drugs are membrane proteins, which is reason able considering that membrane proteins are widely involved in various biological processes and represent the largest class of drug targets. Implication of drug cocktail network for possible drug combinations As shown in Figure 3, 82% of the combinations between star drugs and their neighbors have therapeutic similar ity, and most of the star drugs have therapeutic similar ity to the majority of their neighbors in the drug cocktail network.

Additionally, most of the effective combinations are observed to be located in the vicinity of drug pairs with similar ATC codes. Hence, it is possi ble to predict drug combinations from the set of drug pairs with similar ATC codes. Nonetheless, we found that there are only 74 known effective combinations in all of the 1181 possible combinations with similar ATC codes. Since the number of effective drug combinations is considerably smaller GSK-3 than that of random combina tions between drugs having similar ATC codes, it is a challenging but crucial task to discover the effective combinations from the pool with a vast number of ran dom combinations. In Figure 4B and 4C, we can see that if two drugs with similar ATC codes have a common neighbor in the drug cocktail network, they are more likely to be com bined together. Therefore, we assume that the two drugs having similar ATC codes and sharing a Tivantinib signifi cantly larger number of common partners in the drug cocktail network are more likely to be combined effec tively. Based on this assumption, we further developed a new statistical approach called DCPred to test this hypothesis and applied it to predict and rank all the possible drug combinations.