In silico prediction of chemical mechanism of action via an improved network-based inference method.

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

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.

Related collections

Author and article information

Journal

Journal ID (iso-abbrev): Br J Pharmacol

Title: British journal of pharmacology

Publisher: Wiley

ISSN (Electronic): 1476-5381

ISSN (Print): 0007-1188

Publication date (Electronic): Dec 2016

Volume: 173

Issue: 23

Affiliations

[1 ] Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.

[2 ] Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.

[3 ] State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.

[4 ] Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.

[5 ] Center for Complex Networks Research, Northeastern University, Boston, Massachusetts, USA.

Article

DOI: 10.1111/bph.13629

PMC ID: 5738663

PubMed ID: 27646592

SO-VID: 3b95e4da-91b3-458d-82d3-3d33e52e1ff5

History

Data availability:

Comments

Comment on this article

scite_

Cited by 27

See all cited by

- Version 1