Protein homology reveals new targets for bioactive small molecules.

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Version: Final published version
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ID Serval
serval:BIB_318526DD8C13
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Protein homology reveals new targets for bioactive small molecules.
Périodique
Bioinformatics
Auteur⸱e⸱s
Gfeller D., Zoete V.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Statut éditorial
Publié
Date de publication
2015
Peer-reviewed
Oui
Volume
31
Numéro
16
Pages
2721-2727
Langue
anglais
Notes
Publication types: Journal ArticlePublication Status: ppublish
Résumé
MOTIVATION: The functional impact of small molecules is increasingly being assessed in different eukaryotic species through large-scale phenotypic screening initiatives. Identifying the targets of these molecules is crucial to mechanistically understand their function and uncover new therapeutically relevant modes of action. However, despite extensive work carried out in model organisms and human, it is still unclear to what extent one can use information obtained in one species to make predictions in other species.
RESULTS: Here, for the first time, we explore and validate at a large scale the use of protein homology relationships to predict the targets of small molecules across different species. Our results show that exploiting target homology can significantly improve the predictions, especially for molecules experimentally tested in other species. Interestingly, when considering separately orthology and paralogy relationships, we observe that mapping small molecule interactions among orthologs improves prediction accuracy, while including paralogs does not improve and even sometimes worsens the prediction accuracy. Overall, our results provide a novel approach to integrate chemical screening results across multiple species and highlight the promises and remaining challenges of using protein homology for small molecule target identification.
AVAILABILITY AND IMPLEMENTATION: Homology-based predictions can be tested on our website http://www.swisstargetprediction.ch.
CONTACT: david.gfeller@unil.ch or vincent.zoete@isb-sib.ch.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Pubmed
Web of science
Open Access
Oui
Création de la notice
07/09/2015 14:35
Dernière modification de la notice
14/02/2022 7:54
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