Disease Pathway Cut for Multi-Target drugs
Abstract Background Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity. But still, the set of target genes should effectively block all possib...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-02-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-019-2638-3 |
| _version_ | 1811286088898052096 |
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| author | Sunjoo Bang Sangjoon Son Sooyoung Kim Hyunjung Shin |
| author_facet | Sunjoo Bang Sangjoon Son Sooyoung Kim Hyunjung Shin |
| author_sort | Sunjoo Bang |
| collection | DOAJ |
| description | Abstract Background Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity. But still, the set of target genes should effectively block all possible paths of disease progression. Methods In this article, we propose a network based computational analysis for target gene identification for multi-target drugs. The min-cut algorithm is employed to cut all the paths from onset genes to apoptotic genes on a disease pathway. If the pathway network is completely disconnected, development of disease will not further go on. The genes corresponding to the end points of the cutting edges are identified as candidate target genes for a multi-target drug. Results and conclusions The proposed method was applied to 10 disease pathways. In total, thirty candidate genes were suggested. The result was validated with gene set enrichment analysis software, PubMed literature review and de facto drug targets. |
| first_indexed | 2024-04-13T02:53:36Z |
| format | Article |
| id | doaj.art-e6a39e64def84243895b2610a9c7c644 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-13T02:53:36Z |
| publishDate | 2019-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-e6a39e64def84243895b2610a9c7c6442022-12-22T03:05:45ZengBMCBMC Bioinformatics1471-21052019-02-0120111210.1186/s12859-019-2638-3Disease Pathway Cut for Multi-Target drugsSunjoo Bang0Sangjoon Son1Sooyoung Kim2Hyunjung Shin3Department of Industrial Engineering, Ajou UniversityDepartment of Psychiatry, Ajou University School of MedicineDepartment of Surgery, Thyroid Cancer Center, Gangnam Severance Hospital, Institute of Refractory Thyroid Cancer, Yonsei University College of MedicineDepartment of Industrial Engineering, Ajou UniversityAbstract Background Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity. But still, the set of target genes should effectively block all possible paths of disease progression. Methods In this article, we propose a network based computational analysis for target gene identification for multi-target drugs. The min-cut algorithm is employed to cut all the paths from onset genes to apoptotic genes on a disease pathway. If the pathway network is completely disconnected, development of disease will not further go on. The genes corresponding to the end points of the cutting edges are identified as candidate target genes for a multi-target drug. Results and conclusions The proposed method was applied to 10 disease pathways. In total, thirty candidate genes were suggested. The result was validated with gene set enrichment analysis software, PubMed literature review and de facto drug targets.http://link.springer.com/article/10.1186/s12859-019-2638-3Target gene identificationDisease pathwayDirected PPIPathway networkMin-cut algorithm |
| spellingShingle | Sunjoo Bang Sangjoon Son Sooyoung Kim Hyunjung Shin Disease Pathway Cut for Multi-Target drugs BMC Bioinformatics Target gene identification Disease pathway Directed PPI Pathway network Min-cut algorithm |
| title | Disease Pathway Cut for Multi-Target drugs |
| title_full | Disease Pathway Cut for Multi-Target drugs |
| title_fullStr | Disease Pathway Cut for Multi-Target drugs |
| title_full_unstemmed | Disease Pathway Cut for Multi-Target drugs |
| title_short | Disease Pathway Cut for Multi-Target drugs |
| title_sort | disease pathway cut for multi target drugs |
| topic | Target gene identification Disease pathway Directed PPI Pathway network Min-cut algorithm |
| url | http://link.springer.com/article/10.1186/s12859-019-2638-3 |
| work_keys_str_mv | AT sunjoobang diseasepathwaycutformultitargetdrugs AT sangjoonson diseasepathwaycutformultitargetdrugs AT sooyoungkim diseasepathwaycutformultitargetdrugs AT hyunjungshin diseasepathwaycutformultitargetdrugs |