Quantitative profiling of protease specificity.

Proteases are an important class of enzymes, whose activity is central to many physiologic and pathologic processes. Detailed knowledge of protease specificity is key to understanding their function. Although many methods have been developed to profile specificities of proteases, few have the diversity and quantitative grasp necessary to fully define specificity of a protease, both in terms of substrate numbers and their catalytic efficiencies.

Predictive models of protease specificity based on quantitative protease-activity profiling data.

Bioinformatics-based prediction of protease substrates can help to elucidate regulatory proteolytic pathways that control a broad range of biological processes such as apoptosis and blood coagulation. The majority of published predictive models are position weight matrices (PWM) reflecting specificity of proteases toward target sequence. These models are typically derived from experimental data on positions of hydrolyzed peptide bonds and show a reasonable predictive power.

Metabolic rewiring in melanoma.

Oncogene-driven metabolic rewiring is an adaptation to low nutrient and oxygen conditions in the tumor microenvironment that enables cancer cells of diverse origin to hyperproliferate. Aerobic glycolysis and enhanced reliance on glutamine utilization are prime examples of such rewiring. However, tissue of origin as well as specific genetic and epigenetic changes determines gene expression profiles underlying these metabolic alterations in specific cancers.

Right on TARGET: glutamine metabolism in cancer.

Recent studies highlight the importance of glutamine metabolism in metabolic reprogramming, which underlies cancer cell addiction to glutamine. Examples for the dependence on glutamine metabolism are seen across different tumor types as during different phases of cancer development, progression and response to therapy. In this perspective, we assess the possibility of targeting glutamine metabolism as a therapeutic modality for cancer.