In silico identification and biological evaluation of a selective MAP4K4 inhibitor against pancreatic cancer

Abstract

Inhibiting a specific target in cancer cells and reducing unwanted side effects has become a promising strategy in pancreatic cancer treatment. MAP4K4 is associated with pancreatic cancer development and correlates with poor clinical outcomes. By phosphorylating MKK4, proteins associated with cell apoptosis and survival are translated. Therefore, inhibiting MAP4K4 activity in pancreatic tumours is a new therapeutic strategy. Herein, we performed a structure-based virtual screening to identify MAP4K4 inhibitors and discovered the compound F389-0746 with a potent inhibition (IC₅₀ 120.7 nM). The results of kinase profiling revealed that F389-0746 was highly selective to MAP4K4 and less likely to cause side effects. Results of in vitro experiments showed that F389-0746 significantly suppressed cancer cell growth and viability. Results of in vivo experiments showed that F389-0746 displayed comparable tumour growth inhibition with the group treated with gemcitabine. These findings suggest that F389-0746 has promising potential to be further developed as a novel pancreatic cancer treatment.

Graphical abstract

Highlights

• We identified a novel MAP4K4 inhibitor using a structure-based virtual screening strategy.

• Kinase profiling showed high selectivity towards MAP4K4.

• The identified inhibitor suppressed pancreatic cancer cell growth and viability in vitro.

• The inhibitor downregulated the MKK4-JNK signalling pathway.

• The inhibitor suppressed tumour growth in vivo.

Keywords:

• MAP4K4
• JNK signalling pathway
• pancreatic cancer
• structure-based virtual screening
• kinase inhibitor

Acknowledgements

We gratefully acknowledge the support from the Ministry of Science and Technology (MOST 111-2320-B-038-042-MY3 and MOST 111-2622-B-038-009). This research was also partially supported by the Biomedical Translation Research Center, Academia Sinica (Grant No. AS-BRPT-112-11) and "TMU Research Center of Cancer Translational Medicine" from the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan. We also acknowledge Graphen Inc. for the RNA-seq data analysis of pancreatic cancer.

Disclosure statement

The authors report no conflicts of interest.

Additional information

Funding

This research was supported by the Ministry of Science and Technology (MOST 111-2320-B-038-042-MY3 and MOST 111-2622-B-038-009). This research was also partially supported by the Biomedical Translation Research Center, Academia Sinica (Grant No. AS-BRPT-112-11) and “TMU Research Center of Cancer Translational Medicine” from the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.