Systems pharmacology strategies for anticancer drug discovery based on natural products.

Cancer is a complex disease, known medically as malignant neoplasm. Natural products (NPs) play a very important role in anticancer drug discovery and a large number of NPs have been proven to have potential anticancer effects. Compared with newly synthesized chemical compounds, NPs show a favorable profile in terms of their absorption and metabolism in the body with low toxicity. Searching for multi-target natural drugs can be regarded as a solution to improve therapeutic efficacy and safety. In this work, we collected 104 cancer-associated target proteins from the Protein Data Bank. Based on the Universal Natural Products Database, all of the NPs were docked to 104 cancer-associated target proteins. Then we explored the potential of NPs and several herbs in anticancer drug discovery by using a network-based multi-target computational approach. The NPs with the most potential for anticancer drug discovery and their indications were predicted based on a docking score-weighted prediction model. We also explored the interactions between NPs and cancer target proteins to find the pathological networks, potential drug candidates and new indications.