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Machine intelligence decrypts β-lapachone as an allosteric 5-lipoxygenase inhibitor

Using machine learning, targets were identified for β-lapachone. Resorting to biochemical assays, β-lapachone was validated as a potent, ligand efficient, allosteric and reversible modulator of 5-lipoxygenase (5-LO). Moreover, we provide a rationale for 5-LO modulation and show that inhibition of 5-...

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Detalles Bibliográficos
Autores principales: Rodrigues, Tiago, Werner, Markus, Roth, Jakob, da Cruz, Eduardo H. G., Marques, Marta C., Akkapeddi, Padma, Lobo, Susana A., Koeberle, Andreas, Corzana, Francisco, da Silva Júnior, Eufrânio N., Werz, Oliver, Bernardes, Gonçalo J. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal Society of Chemistry 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138237/
https://www.ncbi.nlm.nih.gov/pubmed/30310622
http://dx.doi.org/10.1039/c8sc02634c
Descripción
Sumario:Using machine learning, targets were identified for β-lapachone. Resorting to biochemical assays, β-lapachone was validated as a potent, ligand efficient, allosteric and reversible modulator of 5-lipoxygenase (5-LO). Moreover, we provide a rationale for 5-LO modulation and show that inhibition of 5-LO is relevant for the anticancer activity of β-lapachone. This work demonstrates the power of machine intelligence to deconvolute complex phenotypes, as an alternative and/or complement to chemoproteomics and as a viable general approach for systems pharmacology studies.