Design and Potency Optimization of Kinase Inhibitors for Cancer Treatment

Cancer has been a leading cause of death in Taiwan for many years. Protein kinases are often overexpressed in cancer cells, making them an important target for cancer therapy. However, most of the current kinase drugs target the TK family. As a result, many cancer-related kinases are without an effective drug treatment, such as CDK7 and PKR. The former belongs to the CMGC family, while the latter belongs to the other kinase family. In this study, we focused on designing CDK7 and PKR inhibitors. CDK7 is a therapeutic target for colorectal and small-cell lung cancer, while PKR is associated with colorectal, breast and liver cancer. In addition, most of current kinase drugs suffer from side effects due to low selectivity. For example, our study will also focus on a cancer and inflammatory marker, JAK2. The JAK2 inhibitor, Ruxolitinib, can also inhibit 107 kinases (~24%) when tested in 439 kinases assays. Thus, the development and optimization of specific kinase inhibitors has great potential for cancer treatment. The main objectives of this project are: (1) to establish a computational platform to design compounds with increased potency against targeted kinases; (2) to optimize potency and improve the selectivity of JAK2, PKR, CDK7 and other kinase inhibitors discovered by our team; (3) to evaluate the pharmacology, pharmacodynamics, mechanics, pharmacokinetics, and toxicology of designed compounds. For our preliminary results, our team has discovered 62 novel inhibitors targeting 36 kinases using our computational platform. We focused on cancer-associated kinases, including JAK2, CDK7 and PKR. For JAK2, we have discovered 15 inhibitors. Of these, 13626 was highly specific for JAK2 inhibitors. When tested against a panel of 97 kinases, 13626 inhibited JAK2 and JAK3. Cell assay results showed 13626 can inhibit STAT3 phosphorylation and drive cell arrest in the S phase. This in turn inhibited colorectal cancer cell growth (GI50 ＝ 6~8 μM). We further designed inhibitor 12488, which has an IC50 value of 726.1 nM against JAK2. For CDK7, we identified inhibitor 755437 (IC50 ＝<10 μM), which inhibited the growth of colorectal cancer cells (GI50 ＝ 3~7 μM) and small-cell lung cancer cells (GI50 ＝19.2 μM). Furthermore, cancer cells were arrested in the G0 phase and treatment with 755437 leads to cancer cell apoptosis. Finally, we identified compound 211799 with an IC50 value of 1.16 μM against PKR activity. We applied the computational platform to design approximately 270,000 derivatives for 12488, 755437 and 211799. Based on the computational platform, the derivatives with high-activity potential were selected for further study. These compounds will be synthesized and their activities will be verified by enzymatic and cellular assays. Our future work will include enhancement of our computational platform to further optimize potency and increase selectivity of the inhibitors. We have full confidence that our team will develop highly specific and efficient kinase inhibitors for use as cancer therapeutics to not only improve the survival rate, but quality of life of cancer patients.