4.6 Article

Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network

Journal

PLOS COMPUTATIONAL BIOLOGY
Volume 15, Issue 4, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1006878

Keywords

-

Funding

  1. National Institutes of Health (NIH) [R01-GM108911]
  2. NIH [U54OD020353, R01-CA170495, R01-CA109730, DP2 CA186570-01]
  3. Department of Defense [W81XWH-15-1-0111]
  4. Damon Runyon-Rachleff Foundation

Ask authors/readers for more resources

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(M955T). Structural models for kinases relevant to MTC were generated for virtual screening to identify unique preliminary hits that suppressed dRet(M955T)-induced transformation. We then combined features from our hits with those of known inhibitors to create a hybrid' molecule with improved suppression of dRet(M955T) 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. Author summary Effective and safe treatment of multigenic diseases often involves drugs that address multiple points along disease networks, i.e., polypharmacology. Polypharmacology is increasingly appreciated as a potentially desirable property of kinase drugs. However, most known drugs that interact with multiple targets have been identified as such by chance and most polypharmacological compounds are not chemically unique, resembling structures of known kinase inhibitors. The fruit fly Drosophila provides an inexpensive, rapid, quantitative, whole animal screening platform that has the potential to complement computational approaches. We present a chemical genetics approach that efficiently combines Drosophila with structural prediction and virtual screening, creating a unique discovery platform. We demonstrate the utility of our approach by developing useful small molecules targeting a kinase network in a Drosophila model of Medullary Thyroid Cancer (MTC) driven by oncogenic dRet(M955T).

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available