High-throughput glycolytic inhibitor discovery targeting glioblastoma by graphite dots-assisted LDI mass spectrometry.

in Science advances by Rui Shi, Peichen Pan, Rui Lv, Chongqing Ma, Enhui Wu, Ruochen Guo, Zhihao Zhao, Hexing Song, Joe Zhou, Yang Liu, Guoqiang Xu, Tingjun Hou, Zhenhui Kang, Jian Liu

TLDR

  • The study is looking for a way to treat a type of brain tumor called glioblastoma. They found a way to stop the tumor from making energy by cutting off its ability to do something called metabolic reprogramming. They did this by finding a special kind of drug called a glycolytic inhibitor. They found five new types of drugs that might work, and the best one (Compd 27) worked really well. They also found that when they used this drug with another drug called temozolomide, it worked even better. This could help doctors find new ways to treat glioblastoma.

Abstract

Malignant tumors will become vulnerable if their uncontrolled biosynthesis and energy consumption engaged in metabolic reprogramming can be cut off. Here, we report finding a glycolytic inhibitor targeting glioblastoma with graphite dots-assisted laser desorption/ionization mass spectrometry as an integrated drug screening and pharmacokinetic platform (GLMSD). We have performed high-throughput virtual screening to narrow an initial library of 240,000 compounds down to the docking of 40 compounds and identified five previously unknown chemical scaffolds as promising hexokinase-2 inhibitors. The best inhibitor (Compd 27) can regulate the reprogrammed metabolic pathway in U87 glioma cells (median inhibitory concentration ~ 11.3 μM) for tumor suppression. Highly effective therapy against glioblastoma has been demonstrated in both subcutaneous and orthotopic brain tumors by synergizing Compd 27 and temozolomide. Our glycolytic inhibitor discovery can inspire personalized medicine targeting reprogrammed metabolisms of malignant tumors. GLMSD enables large, high-quality data for next-generation artificial intelligence-aided drug development.

Overview

  • The study aims to discover a glycolytic inhibitor targeting glioblastoma using graphite dots-assisted laser desorption/ionization mass spectrometry as an integrated drug screening and pharmacokinetic platform (GLMSD).
  • The study uses high-throughput virtual screening to narrow an initial library of 240,000 compounds down to the docking of 40 compounds and identifies five previously unknown chemical scaffolds as promising hexokinase-2 inhibitors. The best inhibitor (Compd 27) can regulate the reprogrammed metabolic pathway in U87 glioma cells for tumor suppression. The study demonstrates highly effective therapy against glioblastoma by synergizing Compd 27 and temozolomide. The glycolytic inhibitor discovery can inspire personalized medicine targeting reprogrammed metabolisms of malignant tumors. GLMSD enables large, high-quality data for next-generation artificial intelligence-aided drug development.

Comparative Analysis & Findings

  • The study compares the outcomes observed under different experimental conditions or interventions, including the virtual screening of a large library of compounds and the identification of five previously unknown chemical scaffolds as promising hexokinase-2 inhibitors. The study also compares the effectiveness of the best inhibitor (Compd 27) in regulating the reprogrammed metabolic pathway in U87 glioma cells and in suppressing tumors in subcutaneous and orthotopic brain tumors when synergized with temozolomide. The study finds that Compd 27 is highly effective in suppressing tumors and that the GLMSD platform enables large, high-quality data for next-generation artificial intelligence-aided drug development.

Implications and Future Directions

  • The study's findings have significant implications for the field of research and clinical practice, as they demonstrate the potential of glycolytic inhibitors targeting reprogrammed metabolisms of malignant tumors for personalized medicine. The study also identifies limitations, such as the need for further preclinical and clinical studies to validate the efficacy and safety of the identified inhibitors. Future research directions could include the development of more potent and selective inhibitors, the exploration of other reprogrammed metabolic pathways in malignant tumors, and the integration of GLMSD with other advanced technologies for drug discovery and development.
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