Format

Send to

Choose Destination
J Biomed Inform. 2015 Apr;54:132-40. doi: 10.1016/j.jbi.2015.02.007. Epub 2015 Feb 24.

Characterizing and optimizing human anticancer drug targets based on topological properties in the context of biological pathways.

Author information

1
School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, PR China.
2
Majorbio Bio-Pharm Technology Co., Ltd., Shanghai 201203, PR China.
3
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
4
Department of Mathematics, Heilongjiang Institute of Technology, Harbin 150050, PR China.
5
School of Nursing, Daqing Campus, Harbin Medical University, Daqing 163319, PR China.
6
School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, PR China. Electronic address: lcqbio@163.com.

Abstract

One of the challenging problems in drug discovery is to identify the novel targets for drugs. Most of the traditional methods for drug targets optimization focused on identifying the particular families of "druggable targets", but ignored their topological properties based on the biological pathways. In this study, we characterized the topological properties of human anticancer drug targets (ADTs) in the context of biological pathways. We found that the ADTs tended to present the following seven topological properties: influence the number of the pathways related to cancer, be localized at the start or end of the pathways, interact with cancer related genes, exhibit higher connectivity, vulnerability, betweenness, and closeness than other genes. We first ranked ADTs based on their topological property values respectively, then fused them into one global-rank using the joint cumulative distribution of an N-dimensional order statistic to optimize human ADTs. We applied the optimization method to 13 anticancer drugs, respectively. Results demonstrated that over 70% of known ADTs were ranked in the top 20%. Furthermore, the performance for mercaptopurine was significant: 6 known targets (ADSL, GMPR2, GMPR, HPRT1, AMPD3, AMPD2) were ranked in the top 15 and other four out of the top 15 (MAT2A, CDKN1A, AREG, JUN) have the potentialities to become new targets for cancer therapy.

KEYWORDS:

Drug targets; Optimization; Pathways; Topology

PMID:
25724580
DOI:
10.1016/j.jbi.2015.02.007
[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center