Shaping the interaction landscape of bioactive molecules.

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ID Serval
serval:BIB_8684DDDEADE4
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Shaping the interaction landscape of bioactive molecules.
Périodique
Bioinformatics
Auteur⸱e⸱s
Gfeller D., Michielin O., Zoete V.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Statut éditorial
Publié
Date de publication
2013
Volume
29
Numéro
23
Pages
3073-3079
Langue
anglais
Résumé
MOTIVATION: Most bioactive molecules perform their action by interacting with proteins or other macromolecules. However, for a significant fraction of them, the primary target remains unknown. In addition, the majority of bioactive molecules have more than one target, many of which are poorly characterized. Computational predictions of bioactive molecule targets based on similarity with known ligands are powerful to narrow down the number of potential targets and to rationalize side effects of known molecules.
RESULTS: Using a reference set of 224 412 molecules active on 1700 human proteins, we show that accurate target prediction can be achieved by combining different measures of chemical similarity based on both chemical structure and molecular shape. Our results indicate that the combined approach is especially efficient when no ligand with the same scaffold or from the same chemical series has yet been discovered. We also observe that different combinations of similarity measures are optimal for different molecular properties, such as the number of heavy atoms. This further highlights the importance of considering different classes of similarity measures between new molecules and known ligands to accurately predict their targets.
CONTACT: olivier.michielin@unil.ch or vincent.zoete@unil.ch
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Pubmed
Web of science
Open Access
Oui
Création de la notice
22/12/2013 17:48
Dernière modification de la notice
14/02/2022 8:55
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