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Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape

Drugs produce pharmaceutical and adverse effects that arise from the complex relationship between drug targets and signatures; by considering such relationships, we can begin to understand the cellular mechanisms of drugs. In this study, we selected 463 genes from the DSigDB database corresponding t...

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Autores principales: Lee, Chae Won, Kim, Sung Min, Sa, Soonok, Hong, Myunghee, Nam, Sang-Min, Han, Hyun Wook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885570/
https://www.ncbi.nlm.nih.gov/pubmed/36717817
http://dx.doi.org/10.1186/s12920-023-01444-8
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author Lee, Chae Won
Kim, Sung Min
Sa, Soonok
Hong, Myunghee
Nam, Sang-Min
Han, Hyun Wook
author_facet Lee, Chae Won
Kim, Sung Min
Sa, Soonok
Hong, Myunghee
Nam, Sang-Min
Han, Hyun Wook
author_sort Lee, Chae Won
collection PubMed
description Drugs produce pharmaceutical and adverse effects that arise from the complex relationship between drug targets and signatures; by considering such relationships, we can begin to understand the cellular mechanisms of drugs. In this study, we selected 463 genes from the DSigDB database corresponding to targets and signatures for 382 FDA-approved drugs with both protein binding information for a drug-target score (KDTN, i.e., the degree to which the protein encoded by the gene binds to a number of drugs) and microarray signature information for a drug-sensitive score (KDSN, i.e., the degree to which gene expression is stimulated by the drug). Accordingly, we constructed two drug–gene bipartite network models, a drug-target network and drug-signature network, which were merged into a multidimensional model. Analysis revealed that the KDTN and KDSN were in mutually exclusive and reciprocal relationships in terms of their biological network structure and gene function. A symmetric balance between the KDTN and KDSN of genes facilitates the possibility of therapeutic drug effects in whole genome. These results provide new insights into the relationship between drugs and genes, specifically drug targets and drug signatures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01444-8.
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spelling pubmed-98855702023-01-31 Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape Lee, Chae Won Kim, Sung Min Sa, Soonok Hong, Myunghee Nam, Sang-Min Han, Hyun Wook BMC Med Genomics Research Drugs produce pharmaceutical and adverse effects that arise from the complex relationship between drug targets and signatures; by considering such relationships, we can begin to understand the cellular mechanisms of drugs. In this study, we selected 463 genes from the DSigDB database corresponding to targets and signatures for 382 FDA-approved drugs with both protein binding information for a drug-target score (KDTN, i.e., the degree to which the protein encoded by the gene binds to a number of drugs) and microarray signature information for a drug-sensitive score (KDSN, i.e., the degree to which gene expression is stimulated by the drug). Accordingly, we constructed two drug–gene bipartite network models, a drug-target network and drug-signature network, which were merged into a multidimensional model. Analysis revealed that the KDTN and KDSN were in mutually exclusive and reciprocal relationships in terms of their biological network structure and gene function. A symmetric balance between the KDTN and KDSN of genes facilitates the possibility of therapeutic drug effects in whole genome. These results provide new insights into the relationship between drugs and genes, specifically drug targets and drug signatures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01444-8. BioMed Central 2023-01-30 /pmc/articles/PMC9885570/ /pubmed/36717817 http://dx.doi.org/10.1186/s12920-023-01444-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lee, Chae Won
Kim, Sung Min
Sa, Soonok
Hong, Myunghee
Nam, Sang-Min
Han, Hyun Wook
Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
title Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
title_full Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
title_fullStr Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
title_full_unstemmed Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
title_short Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
title_sort relationship between drug targets and drug-signature networks: a network-based genome-wide landscape
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885570/
https://www.ncbi.nlm.nih.gov/pubmed/36717817
http://dx.doi.org/10.1186/s12920-023-01444-8
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