Introduction

Cancer cells exhibit altered metabolic pathways to support their rapid growth and survival. One of the key metabolic adaptations in many cancers is glutamine addiction, where cells rely on glutamine as a major carbon and nitrogen source for energy production and biosynthesis. Glutaminase 1 (GLS1) plays a crucial role in this process by catalyzing the conversion of glutamine to glutamate, which subsequently fuels the TCA cycle, nucleotide synthesis, and lipid metabolism. Given its critical function in cancer metabolism, GLS1 has emerged as a promising therapeutic target. So far, CB-839 (Telaglenastat) is a potent and selective GLS1 small molecule inhibitor that blocks glutamine metabolism, thereby disrupting the metabolic flexibility of cancer cells. By inhibiting GLS1 activity, CB-839 effectively reduces glutamate availability, leading to downstream metabolic alterations that can impair cancer cell proliferation and survival.

Protein-ligand structure prediction has become a cornerstone of structure-based drug design, enabling the rational development of therapeutic compounds by modeling how small molecules interact with target proteins. Despite recent advances in protein structure prediction tools, identifying key ligand interactions within protein binding pockets remains challenging. As in silico screening offers a powerful approach to guide lead compound optimization by providing structural insights, this strategy holds great potential to accelerate drug discovery and contribute meaningfully to the design of more effective and selective therapeutics.

In this project, we investigated how cancer cell metabolism is reprogrammed in response to CB-839 treatment by examining key metabolic pathways. Additionally, we aimed to utilized bioinformatics prediction tools for the protein-ligand interaction between GLS1 and known inhibitors in (pre)clinical trials including CB-839, and compared its structure with existing X-ray crystallography structures. With these efforts, we tried to provide insights in how GLS1 inhibition can impact in cancer metabolism, and the structural mechanism of GLS1 inhibition potentially guiding the development of structure-based drug design strategies for more effective therapeutic interventions.

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