title: In silico prediction of chemical mechanism of action via an improved network-based inference method.
abstract: Deciphering chemical mechanism of action (MoA) enables the development of novel therapeutics (e.g. drug repositioning) and evaluation of drug side effects. Development of novel computational methods for chemical MoA assessment under a systems pharmacology framework would accelerate drug discovery and development with greater efficiency and low cost.
  
  
  
  In this study, we proposed an improved network-based inference method, balanced substructure-drug-target network-based inference (bSDTNBI), to predict MoA for old drugs, clinically failed drugs and new chemical entities. Specifically, three parameters were introduced into network-based resource diffusion processes to adjust the initial resource allocation of different node types, the weighted values of different edge types and the influence of hub nodes. The performance of the method was systematically validated by benchmark datasets and bioassays.
  
  
  
  High performance was yielded for bSDTNBI in both 10-fold and leave-one-out cross validations. A global drug-target network was built to explore MoA of anticancer drugs and repurpose old drugs for 15 cancer types/subtypes. In a case study, 27 predicted candidates among 56 commercially available compounds were experimentally validated to have binding affinities on oestrogen receptor α with IC50or EC50values ≤10 μM. Furthermore, two dual ligands with both agonistic and antagonistic activities ≤1 μM would provide potential lead compounds for the development of novel targeted therapy in breast cancer or osteoporosis.
  
  
  
  In summary, bSDTNBI would provide a powerful tool for the MoA assessment on both old drugs and novel compounds in drug discovery and development.
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Zengrui
authors.initials: Z
authors.lastname: Wu
authors.affiliation: Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
authors.forename: Weiqiang
authors.initials: W
authors.lastname: Lu
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Dang
authors.initials: D
authors.lastname: Wu
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Anqi
authors.initials: A
authors.lastname: Luo
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Hanping
authors.initials: H
authors.lastname: Bian
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Li
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Weihua
authors.initials: W
authors.lastname: Li
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Guixia
authors.initials: G
authors.lastname: Liu
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Huang
authors.affiliation: State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.|Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.|Center for Complex Networks Research, Northeastern University, Boston, Massachusetts, USA.
authors.forename: Feixiong
authors.initials: F
authors.lastname: Cheng
authors.affiliation: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Tang
mesh_terms: D000970:Antineoplastic Agents / Q000008:administration & dosage / Q000494:pharmacology*; D003198:Computer Simulation; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods; D058492:Drug Repositioning / Q000379:methods; D006801:Humans; D020128:Inhibitory Concentration 50; D008024:Ligands; D058990:Molecular Targeted Therapy; D009369:Neoplasms / Q000188:drug therapy*
chemical_list: D000970:Antineoplastic Agents; D008024:Ligands