title: System-level multi-target drug discovery from natural products with applications to cardiovascular diseases.
abstract: The term systems pharmacology describes a field of study that uses computational and experimental approaches to broaden the view of drug actions rooted in molecular interactions and advance the process of drug discovery. The aim of this work is to stick out the role that the systems pharmacology plays across the multi-target drug discovery from natural products for cardiovascular diseases (CVDs). Firstly, based on network pharmacology methods, we reconstructed the drug-target and target-target networks to determine the putative protein target set of multi-target drugs for CVDs treatment. Secondly, we reintegrated a compound dataset of natural products and then obtained a multi-target compounds subset by virtual-screening process. Thirdly, a drug-likeness evaluation was applied to find the ADME-favorable compounds in this subset. Finally, we conducted in vitro experiments to evaluate the reliability of the selected chemicals and targets. We found that four of the five randomly selected natural molecules can effectively act on the target set for CVDs, indicating the reasonability of our systems-based method. This strategy may serve as a new model for multi-target drug discovery of complex diseases.
authors.affiliation: Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China.
authors.forename: Chunli
authors.initials: C
authors.lastname: Zheng
authors.forename: Jinan
authors.initials: J
authors.lastname: Wang
authors.forename: Jianling
authors.initials: J
authors.lastname: Liu
authors.forename: Mengjie
authors.initials: M
authors.lastname: Pei
authors.forename: Chao
authors.initials: C
authors.lastname: Huang
authors.forename: Yonghua
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000818:Animals; D001688:Biological Products / Q000494:pharmacology* / Q000627:therapeutic use; D002318:Cardiovascular Diseases / Q000188:drug therapy* / Q000201:enzymology; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D062313:Databases, Pharmaceutical; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D020128:Inhibitory Concentration 50; D008958:Models, Molecular
chemical_list: D001688:Biological Products