Abstract
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.
Original language | English (US) |
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Pages (from-to) | 3-20 |
Number of pages | 18 |
Journal | Oncotarget |
Volume | 9 |
Issue number | 1 |
DOIs | |
State | Published - 2018 |
Keywords
- Cancer
- Drug discovery
- High throughput drug screening
- Lipid metabolism
- Stearoyl CoA desaturase
ASJC Scopus subject areas
- Oncology