ArticlePLoS computational biology2019
Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Genotype-Informed Whole-Animal Kinome Screening Reveals Shared Kinase Vulnerabilities Across Driver Contexts in PDAC.Cancer science · 2026Article
- Inhibition of NAD-GPx4 axis and MEK triggers ferroptosis to suppress pancreatic ductal adenocarcinoma.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
- Modelling Cancer in Drosophila: Exploration to Personalised Medicine.Advances in experimental medicine and biology · 2025Review
- Concurrent targeting of GSK3 and MEK as a therapeutic strategy to treat pancreatic ductal adenocarcinoma.Cancer science · 2024Article
- Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge.PLoS computational biology · 2021Article
- Article
- Tiny Drosophila makes giant strides in cancer research.Cancer science · 2021Review
- Two-Faced: Roles of JNK Signalling During Tumourigenesis in theFrontiers in cell and developmental biology · 2020Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.