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From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures

MOTIVATION: A critical element of drug development is the identification of therapeutic targets for diseases. However, the depletion of therapeutic targets is a serious problem. RESULTS: In this study, we propose the novel concept of target repositioning, an extension of the concept of drug repositi...

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Autores principales: Namba, Satoko, Iwata, Michio, Yamanishi, Yoshihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235496/
https://www.ncbi.nlm.nih.gov/pubmed/35758779
http://dx.doi.org/10.1093/bioinformatics/btac240
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author Namba, Satoko
Iwata, Michio
Yamanishi, Yoshihiro
author_facet Namba, Satoko
Iwata, Michio
Yamanishi, Yoshihiro
author_sort Namba, Satoko
collection PubMed
description MOTIVATION: A critical element of drug development is the identification of therapeutic targets for diseases. However, the depletion of therapeutic targets is a serious problem. RESULTS: In this study, we propose the novel concept of target repositioning, an extension of the concept of drug repositioning, to predict new therapeutic targets for various diseases. Predictions were performed by a trans-disease analysis which integrated genetically perturbed transcriptomic signatures (knockdown of 4345 genes and overexpression of 3114 genes) and disease-specific gene transcriptomic signatures of 79 diseases. The trans-disease method, which takes into account similarities among diseases, enabled us to distinguish the inhibitory from activatory targets and to predict the therapeutic targetability of not only proteins with known target–disease associations but also orphan proteins without known associations. Our proposed method is expected to be useful for understanding the commonality of mechanisms among diseases and for therapeutic target identification in drug discovery. AVAILABILITY AND IMPLEMENTATION: Supplemental information and software are available at the following website [http://labo.bio.kyutech.ac.jp/~yamani/target_repositioning/]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-92354962022-06-29 From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures Namba, Satoko Iwata, Michio Yamanishi, Yoshihiro Bioinformatics ISCB/Ismb 2022 MOTIVATION: A critical element of drug development is the identification of therapeutic targets for diseases. However, the depletion of therapeutic targets is a serious problem. RESULTS: In this study, we propose the novel concept of target repositioning, an extension of the concept of drug repositioning, to predict new therapeutic targets for various diseases. Predictions were performed by a trans-disease analysis which integrated genetically perturbed transcriptomic signatures (knockdown of 4345 genes and overexpression of 3114 genes) and disease-specific gene transcriptomic signatures of 79 diseases. The trans-disease method, which takes into account similarities among diseases, enabled us to distinguish the inhibitory from activatory targets and to predict the therapeutic targetability of not only proteins with known target–disease associations but also orphan proteins without known associations. Our proposed method is expected to be useful for understanding the commonality of mechanisms among diseases and for therapeutic target identification in drug discovery. AVAILABILITY AND IMPLEMENTATION: Supplemental information and software are available at the following website [http://labo.bio.kyutech.ac.jp/~yamani/target_repositioning/]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-06-27 /pmc/articles/PMC9235496/ /pubmed/35758779 http://dx.doi.org/10.1093/bioinformatics/btac240 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle ISCB/Ismb 2022
Namba, Satoko
Iwata, Michio
Yamanishi, Yoshihiro
From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
title From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
title_full From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
title_fullStr From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
title_full_unstemmed From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
title_short From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
title_sort from drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures
topic ISCB/Ismb 2022
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235496/
https://www.ncbi.nlm.nih.gov/pubmed/35758779
http://dx.doi.org/10.1093/bioinformatics/btac240
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