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Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network.
- Source :
- PLoS Computational Biology; 4/26/2019, Vol. 15 Issue 4, p1-19, 19p, 2 Color Photographs, 4 Diagrams, 3 Charts
- Publication Year :
- 2019
-
Abstract
- Drosophila provides an inexpensive and quantitative platform for measuring whole animal drug response. A complementary approach is virtual screening, where chemical libraries can be efficiently screened against protein target(s). Here, we present a unique discovery platform integrating structure-based modeling with Drosophila biology and organic synthesis. We demonstrate this platform by developing chemicals targeting a Drosophila model of Medullary Thyroid Cancer (MTC) characterized by a transformation network activated by oncogenic dRet<superscript>M955T</superscript>. Structural models for kinases relevant to MTC were generated for virtual screening to identify unique preliminary hits that suppressed dRet<superscript>M955T</superscript>-induced transformation. We then combined features from our hits with those of known inhibitors to create a ‘hybrid’ molecule with improved suppression of dRet<superscript>M955T</superscript> transformation. Our platform provides a framework to efficiently explore novel kinase inhibitors outside of explored inhibitor chemical space that are effective in inhibiting cancer networks while minimizing whole body toxicity. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 15
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 136121016
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1006878