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

Mac Gabhann, F., Ung, P. M. U., Sonoshita, M., Scopton, A. P., Dar, A. C., Cagan, R. L. and Schlessinger, A. (2019) Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network. PLoS Computational Biology, 15(4), e1006878. (doi: 10.1371/journal.pcbi.1006878) (PMID:31026276) (PMCID:PMC6506148)

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 dRetM955T. Structural models for kinases relevant to MTC were generated for virtual screening to identify unique preliminary hits that suppressed dRetM955T-induced transformation. We then combined features from our hits with those of known inhibitors to create a ‘hybrid’ molecule with improved suppression of dRetM955T 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.

• Item Type: Articles
• Additional Information: Funding: AS and PMUU were supported in part by the National Institutes of Health (NIH) grant R01-GM108911. MS and RLC were supported by the NIH grants U54OD020353, R01-CA170495, and R01-CA109730 and Department of Defense grant W81XWH-15-1-0111. APS and ACD were supported by Innovation awards from the NIH (DP2 CA186570-01) and Damon Runyon-Rachleff Foundation. ACD is a Pew-Stewart Scholar in Cancer Research and Young Investigator of the Pershing-Square Sohn Cancer Research Alliance.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cagan, Professor Ross

Creator Roles

Cagan, R.: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review and editing

• Authors: Mac Gabhann, F., Ung, P. M. U., Sonoshita, M., Scopton, A. P., Dar, A. C., Cagan, R. L., and Schlessinger, A.
• College/School: College of Medical Veterinary and Life Sciences > School of Cancer Sciences
• Journal Name: PLoS Computational Biology
• Publisher: Public Library of Science
• ISSN: 1553-7358
• ISSN (Online): 1553-7358
• Copyright Holders: Copyright © 2019 Ung et al.
• First Published: First published in PLoS Computational Biology 15(4):e1006878
• Publisher Policy: Reproduced under a Creative Commons Licence