Abstract
As a terpenoids natural product isolated from the plant Thunder God Vine, Celastrol is widely studied for its pharmacological activities, including anti-tumor activities. The clinical application of Celastrol is strictly limited due to its severe side effects, whereas previously revealed targets and mechanism of Celastrol seldom reduce its in vivo toxicity via structural optimization. Target identification has a far-reaching influence on the development of innovative drugs, and omics data has been widely used for unbiased target prediction. However, it is difficult to enrich target of specific phenotype from thousands of genes or proteins, especially for natural products with broad promising activities. Here, we developed a text-mining-based web-server tool to enrich targets from omics data of inquired compounds. Then peroxiredoxin 1 (PRDX1) was identified as the ROS-manipulating target protein of Celastrol in colorectal cancer. Our solved high-resolution crystal structure revealed the unique covalent binding mode of Celastrol with PRDX1. New derivative compound 19-048 with improved potency against PRDX1 and selectivity towards PRDX2~PRDX6 were synthesized based on crystal structure analysis. Both Celastrol and 19-048 effectively suppressed the proliferation of colorectal cancer cells. The anti-tumor efficacy of Celastrol and 19-048 was significantly diminished on xenograft nude mice bearing PRDX1 knock-down colorectal cancer cells. Several downstream genes of p53 signaling pathway were dramatically up-regulated with Celastrol or 19-048 treatment. Our findings reveal that the side effects of Celastrol could be reduced via structural modification, and PRDX1 inhibition is promising for the treatment of colorectal cancer.