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Accelerated bottom-up drug design platform enables the discovery of novel stearoyl-CoA desaturase 1 inhibitors for cancer therapy

Here we present an innovative computational-based drug discovery strategy, coupled with machine-based learning and functional assessment, for the rational design of novel small molecule inhibitors of the lipogenic enzyme stearoyl-CoA desaturase 1 (SCD1). Our methods resulted in the discovery of seve...

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Detalles Bibliográficos
Autores principales: von Roemeling, Christina A., Caulfield, Thomas R., Marlow, Laura, Bok, Ilah, Wen, Jiang, Miller, James L., Hughes, Robert, Hazlehurst, Lori, Pinkerton, Anthony B., Radisky, Derek C., Tun, Han W., Kim, Yon Son Betty, Lane, Amy L., Copland, John A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5787466/
https://www.ncbi.nlm.nih.gov/pubmed/29416592
http://dx.doi.org/10.18632/oncotarget.21545
Descripción
Sumario:Here we present an innovative computational-based drug discovery strategy, coupled with machine-based learning and functional assessment, for the rational design of novel small molecule inhibitors of the lipogenic enzyme stearoyl-CoA desaturase 1 (SCD1). Our methods resulted in the discovery of several unique molecules, of which our lead compound SSI-4 demonstrates potent anti-tumor activity, with an excellent pharmacokinetic and toxicology profile. We improve upon key characteristics, including chemoinformatics and absorption/distribution/metabolism/excretion (ADME) toxicity, while driving the IC50 to 0.6 nM in some instances. This approach to drug design can be executed in smaller research settings, applied to a wealth of other targets, and paves a path forward for bringing small-batch based drug programs into the Clinic.