ArticleBMC bioinformatics2015
A comparative study of disease genes and drug targets in the human protein interactome.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 39 citations in OpenAlex.
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- Integrated Pharmacogenetics Analysis of the Three Fangjis Decoctions for Treating Arrhythmias Based on Molecular Network Patterns.Frontiers in cardiovascular medicine · 2021Article
- Identification of the key target profiles underlying the drugs of narrow therapeutic index for treating cancer and cardiovascular disease.Computational and structural biotechnology journal · 2021Article
- Integrating molecular networks with genetic variant interpretation for precision medicine.Wiley interdisciplinary reviews. Systems biology and medicine · 2019Review
- An optimized prediction framework to assess the functional impact of pharmacogenetic variants.The pharmacogenomics journal · 2019Article
- Predicting clinically promising therapeutic hypotheses using tensor factorization.BMC bioinformatics · 2019Article
- Construction and Analysis of Molecular Association Network by Combining Behavior Representation and Node Attributes.Frontiers in genetics · 2019Article
- Systematic interrogation of diverse Omic data reveals interpretable, robust, and generalizable transcriptomic features of clinically successful therapeutic targets.PLoS computational biology · 2018Article
- Classical Galactosaemia and CDG, the N-Glycosylation Interface. A Review.JIMD reports · 2017Article
- Systematic Analysis of Drug Targets Confirms Expression in Disease-Relevant Tissues.Scientific reports · 2016Article
- Integrative analysis of cancer genes in a functional interactome.Scientific reports · 2016Article
- Illuminating drug action by network integration of disease genes: a case study of myocardial infarction.Molecular bioSystems · 2016Article
- Colorectal cancer drug target prediction using ontology-based inference and network analysis.Database : the journal of biological databases and curation · 2015Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
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.
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