title: Systems pharmacology strategies for anticancer drug discovery based on natural products.
abstract: 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.
authors.affiliation: Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, P. R. China. lirongc@pku.edu.cn xiaojxu@pku.edu.cn.
authors.forename: Fang
authors.initials: F
authors.lastname: Luo
authors.forename: Jiangyong
authors.initials: J
authors.lastname: Gu
authors.forename: Lirong
authors.initials: L
authors.lastname: Chen
authors.forename: Xiaojie
authors.initials: X
authors.lastname: Xu
mesh_terms: D000972:Antineoplastic Agents, Phytogenic / Q000737:chemistry / Q000494:pharmacology* / Q000627:therapeutic use; D001688:Biological Products / Q000737:chemistry / Q000494:pharmacology* / Q000627:therapeutic use; D019295:Computational Biology / Q000379:methods*; D062313:Databases, Pharmaceutical; D030562:Databases, Protein; D055808:Drug Discovery; D062105:Molecular Docking Simulation; D009363:Neoplasm Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry
chemical_list: D000972:Antineoplastic Agents, Phytogenic; D001688:Biological Products; D009363:Neoplasm Proteins