Despite the approval and commercialization of a large number of treatment options in recent years, cancer remains the leading cause of death in America. To remain competitive in this market and move toward broadly efficacious treatments, emphasis must be put on personalized, targeted therapies that exploit the unique metabolic changes that occur in cancer cells. Recent bioinformatic analyses have identified one of driving forces for the metabolic rewiring that is the underlying cause of many aggressive cancers, aberrant overexpression of the serine hydroxymethyltransferase, SHMT2. After validating this finding experimentally, we developed a high throughput screen to identify small molecule inhibitors of SHMT2 which can be developed into powerful tools for slowing the growth of tumors. Our lead compounds are first-in-class, potent, and orally active SHMT2 inhibitors for the treatment of a variety of aggressive cancers.
Targeting Aberrant Glycine Metabolism to Slow Tumor Growth
SHMTs simultaneously catalyze the conversion of L-serine to glycine and tetrahydrofolate to 5,10-methylenetetrahydrofolate. Elevated expression of SHMT2 is associated with fast proliferation in cancer cells and with poor prognosis and survival probability in cancer patients, whereas silencing SHMT2 significantly impairs cancer cell growth and proliferation. Although modulating SHMT2 at the genetic level is not clinically feasible, small molecule inhibition of SHMT2 activity can regulate the genes aberrant activity. To this end we identified 47 lead compounds that inhibit SHMT2 by 50-93% at pharmaceutically relevant concentrations. These compounds show attractive absorption, distribution, metabolism, excretion and toxicity characteristics making them promising drug candidates.
- Selective, high throughput assay for identification and design of SHMT2 inhibitors
- Lead compounds to be used for clinical studies or scaffolds for rational design
- First-in-class drug candidates for SHMT2 inhibition
- Targets an underlying metabolic rewiring mechanism
- Attractive Ki and ADMET properties