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DREAM: an R package for druggability evaluation of human complex diseases

MOTIVATION: De novo drug development is a long and expensive process that poses significant challenges from the design to the preclinical testing, making the introduction into the market slow and difficult. This limitation paved the way to the development of drug repurposing, which consists in the r...

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Autores principales: Federico, Antonio, Fratello, Michele, Pavel, Alisa, Möbus, Lena, del Giudice, Giusy, Serra, Angela, Greco, Dario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374489/
https://www.ncbi.nlm.nih.gov/pubmed/37471593
http://dx.doi.org/10.1093/bioinformatics/btad442
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author Federico, Antonio
Fratello, Michele
Pavel, Alisa
Möbus, Lena
del Giudice, Giusy
Serra, Angela
Greco, Dario
author_facet Federico, Antonio
Fratello, Michele
Pavel, Alisa
Möbus, Lena
del Giudice, Giusy
Serra, Angela
Greco, Dario
author_sort Federico, Antonio
collection PubMed
description MOTIVATION: De novo drug development is a long and expensive process that poses significant challenges from the design to the preclinical testing, making the introduction into the market slow and difficult. This limitation paved the way to the development of drug repurposing, which consists in the re-usage of already approved drugs, developed for other therapeutic indications. Although several efforts have been carried out in the last decade in order to achieve clinically relevant drug repurposing predictions, the amount of repurposed drugs that have been employed in actual pharmacological therapies is still limited. On one hand, mechanistic approaches, including profile-based and network-based methods, exploit the wealth of data about drug sensitivity and perturbational profiles as well as disease transcriptomics profiles. On the other hand, chemocentric approaches, including structure-based methods, take into consideration the intrinsic structural properties of the drugs and their molecular targets. The poor integration between mechanistic and chemocentric approaches is one of the main limiting factors behind the poor translatability of drug repurposing predictions into the clinics. RESULTS: In this work, we introduce DREAM, an R package aimed to integrate mechanistic and chemocentric approaches in a unified computational workflow. DREAM is devoted to the druggability evaluation of pathological conditions of interest, leveraging robust drug repurposing predictions. In addition, the user can derive optimized sets of drugs putatively suitable for combination therapy. In order to show the functionalities of the DREAM package, we report a case study on atopic dermatitis. AVAILABILITY AND IMPLEMENTATION: DREAM is freely available at https://github.com/fhaive/dream. The docker image of DREAM is available at: https://hub.docker.com/r/fhaive/dream.
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spelling pubmed-103744892023-07-29 DREAM: an R package for druggability evaluation of human complex diseases Federico, Antonio Fratello, Michele Pavel, Alisa Möbus, Lena del Giudice, Giusy Serra, Angela Greco, Dario Bioinformatics Applications Note MOTIVATION: De novo drug development is a long and expensive process that poses significant challenges from the design to the preclinical testing, making the introduction into the market slow and difficult. This limitation paved the way to the development of drug repurposing, which consists in the re-usage of already approved drugs, developed for other therapeutic indications. Although several efforts have been carried out in the last decade in order to achieve clinically relevant drug repurposing predictions, the amount of repurposed drugs that have been employed in actual pharmacological therapies is still limited. On one hand, mechanistic approaches, including profile-based and network-based methods, exploit the wealth of data about drug sensitivity and perturbational profiles as well as disease transcriptomics profiles. On the other hand, chemocentric approaches, including structure-based methods, take into consideration the intrinsic structural properties of the drugs and their molecular targets. The poor integration between mechanistic and chemocentric approaches is one of the main limiting factors behind the poor translatability of drug repurposing predictions into the clinics. RESULTS: In this work, we introduce DREAM, an R package aimed to integrate mechanistic and chemocentric approaches in a unified computational workflow. DREAM is devoted to the druggability evaluation of pathological conditions of interest, leveraging robust drug repurposing predictions. In addition, the user can derive optimized sets of drugs putatively suitable for combination therapy. In order to show the functionalities of the DREAM package, we report a case study on atopic dermatitis. AVAILABILITY AND IMPLEMENTATION: DREAM is freely available at https://github.com/fhaive/dream. The docker image of DREAM is available at: https://hub.docker.com/r/fhaive/dream. Oxford University Press 2023-07-20 /pmc/articles/PMC10374489/ /pubmed/37471593 http://dx.doi.org/10.1093/bioinformatics/btad442 Text en © The Author(s) 2023. 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 Applications Note
Federico, Antonio
Fratello, Michele
Pavel, Alisa
Möbus, Lena
del Giudice, Giusy
Serra, Angela
Greco, Dario
DREAM: an R package for druggability evaluation of human complex diseases
title DREAM: an R package for druggability evaluation of human complex diseases
title_full DREAM: an R package for druggability evaluation of human complex diseases
title_fullStr DREAM: an R package for druggability evaluation of human complex diseases
title_full_unstemmed DREAM: an R package for druggability evaluation of human complex diseases
title_short DREAM: an R package for druggability evaluation of human complex diseases
title_sort dream: an r package for druggability evaluation of human complex diseases
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374489/
https://www.ncbi.nlm.nih.gov/pubmed/37471593
http://dx.doi.org/10.1093/bioinformatics/btad442
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