| Literature DB >> 27667560 |
Xueping Liu1, Hoeke Abele Baarsma2, Chung Hwee Thiam3, Corinna Montrone4, Barbara Brauner4, Gisela Fobo4, Julia-Sophie Heier5, Sven Duscha4, Melanie Königshoff2, Veronique Angeli3, Andreas Ruepp4, Monica Campillos6.
Abstract
Phenotypic drug discovery offers some advantages over target-based methods, mainly because it allows drug leads to be tested in systems that more closely model distinct disease states. However, a potential disadvantage is the difficulty of linking the observed phenotype to a specific cellular target. To address this problem, we developed DePick, a computational target de-convolution tool to determine targets specifically linked to small-molecule phenotypic screens. We applied DePick to eight publicly available screens and predicted 59 drug target-phenotype associations. In addition to literature-based evidence for our predictions, we provide experimental support for seven predicted associations. Interestingly, our analysis led to the discovery of a previously unrecognized connection between the Wnt signaling pathway and an aromatase, CYP19A1. These results demonstrate that the DePick approach can not only accelerate target de-convolution but also aid in discovery of new functionally relevant biological relationships.Entities:
Keywords: drug target-phenotype relations; high-throughput chemical screens; target de-convolution; target prediction
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Year: 2016 PMID: 27667560 DOI: 10.1016/j.chembiol.2016.08.011
Source DB: PubMed Journal: Cell Chem Biol ISSN: 2451-9448 Impact factor: 8.116