Reference : Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selec...
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/50730
Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selection Pipeline and Cell Viability Assay.
English
Cipriani, Claudia [> >]
Pires Pacheco, Maria Irene mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM) >]
Kishk, Ali mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
Wachich, Maryem [> >]
Abankwa, Daniel mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
Schaffner-Reckinger, Elisabeth mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
2022
Pharmaceuticals (Basel, Switzerland)
15
2
Yes (verified by ORBilu)
1424-8247
1424-8247
[en] bruceine D ; drug prediction workflow ; emodin ; metabolic modelling ; natural products ; scutellarein
[en] The multi-target effects of natural products allow us to fight complex diseases like cancer on multiple fronts. Unlike docking techniques, network-based approaches such as genome-scale metabolic modelling can capture multi-target effects. However, the incompleteness of natural product target information reduces the prediction accuracy of in silico gene knockout strategies. Here, we present a drug selection workflow based on context-specific genome-scale metabolic models, built from the expression data of cancer cells treated with natural products, to predict cell viability. The workflow comprises four steps: first, in silico single-drug and drug combination predictions; second, the assessment of the effects of natural products on cancer metabolism via the computation of a dissimilarity score between the treated and control models; third, the identification of natural products with similar effects to the approved drugs; and fourth, the identification of drugs with the predicted effects in pathways of interest, such as the androgen and estrogen pathway. Out of the initial 101 natural products, nine candidates were tested in a 2D cell viability assay. Bruceine D, emodin, and scutellarein showed a dose-dependent inhibition of MCF-7 and Hs 578T cell proliferation with IC(50) values between 0.7 to 65 μM, depending on the drug and cell line. Bruceine D, extracted from Brucea javanica seeds, showed the highest potency.
http://hdl.handle.net/10993/50730

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