A Review of Computational Drug Repositioning Approaches

Title:A Review of Computational Drug Repositioning Approaches

Volume: 20 Issue: 10

Author(s): Guohua Huang*, Jincheng Li, Peng Wang and Weibiao Li

Affiliation:

• Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shaoyang, Hunan 422000,China

Keywords: Drug repositioning, heterogeneous network, machine learning, gene expression profile, phenotype, drug target.

Abstract: Aims & Scope: Computational drug repositioning emerges as a new idea of drug discovery and development. Contrary to conventional routines, computational drug repositioning encompasses low risk and high safety. Some successful cases demonstrated its advantage. Therefore, a large number of computational drug repositioning approaches have been developed over the past decades. We summarized briefly these methods and classified them into target-based, geneexpression- based, phenome-based and multi-omics-based categories according to strategies of drug repositioning.

Conclusion: We reviewed some representatives of computational drug repositioning methods in each category, with emphasis on detail of techniques and finally discussed developing trends of computational drug repositioning.

Cite this article as:

Huang Guohua*, Li Jincheng, Wang Peng and Li Weibiao , A Review of Computational Drug Repositioning Approaches, Combinatorial Chemistry & High Throughput Screening 2017; 20 (10) . https://dx.doi.org/10.2174/1386207321666171221112835