A comparative study of disease genes and drug targets in the human protein interactome

BMC Bioinformatics

Proceedings

Kevin Zhu¹  Hua Xu²  Jingchun Sun²  W Jim Zheng² 

[1] Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, 77030, Houston, TX, USA;School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 77030, Houston, TX, USA;

关键词: Drug Target;    Disease Gene;    Cluster Coefficient;    Disease Category;    Anatomical Therapeutic Chemical;   

DOI  :  10.1186/1471-2105-16-S5-S1

来源: Springer

【 摘 要 】

BackgroundDisease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear.ResultsIn this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes.ConclusionsThe study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing.

【 授权许可】

Unknown   
© Sun et al.; licensee BioMed Central Ltd. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.