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Acta Cryst. (2014). A70, C829
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Inflammation is steadily gaining recognition as contributing to different disease states, e.g. cancer, immune dysfunction and cardiovascular disease. Vanin-1, a GPI-anchored, developmentally regulated member of the nitrilase family, sits at the intersection of many known pathways of inflammation. Three members of the vanin family of enzymes in humans have been described, with vanin-1 and vanin-2 having confirmed enzymatic activity. A known substrate is pantetheine which is hydrolyzed to give vitamin B5 and cysteamine. One function of these enzymes is in pantothenate recycling, and therefore they are involved in the Coenzyme A cycle and metabolism. Mouse knockout studies have shown that Vnn1(-/-) mice are resistant to oxidative stress, intestinal inflammation and colitis. Epidemiological studies have shown that mutations in vanin-1 in humans are associated with child obesity1; other studies show an association with cholesterol homeostasis and cardiovascular disease. Importantly, the metabolic pathways of lipid metabolism and inflammation are interconnected2 whereby impairment of lipid metabolism leads to inflammation and inflammation leads to impairment of lipid metabolism. We recently solved the structure of a soluble form of human vanin-1 using a single heavy atom derivative and anomalous scattering to 2.3 Å resolution. It has two domains: a predicted nitrilase domain and a cap domain which has no known sequence homology to any other structural domain. We also have structures with inhibitors bound and have performed mutational studies to determine the function of the cap domain and affirm the catalytic residues in the catalytic site. Structural studies have been complemented by enzymatic assays showing various levels of activity for the mutant and wild type enzymes. These data will be fundamental in characterizing vanin-1 in different disease states.

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Acta Cryst. (2014). A70, C1512
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The PDB is currently growing at a rate of about 9000 structures annually, and 90% of these have been determined by X-ray diffraction methods. Each structure is the result of one or more crystals. Not every protein crystallises nor do all crystals diffract well enough; it has been estimated that of every 10 proteins that are purified, four will show some sign of crystallisation and one will crystallise robustly enough to obtain a structure1. Using these numbers, and making some educated guesses (for example, that most proteins are tested in 1000 crystallisation trials1) these 8000 structures represent 80,000 purified proteins, and 80,000,000 crystallisation trials which are set up each year. The cost of consumables, chemicals and direct labour to set up those trials varies, but can be estimated to be $0.1- $1, excluding the cost of the protein sample and any automation, suggesting that the structural biology community spends between 10 and 100 million each year on crystallisation. Any tools or insight that we can get from data mining or taking a computational approach to rationalize this process may not only profoundly change structural biology, but will make it much less expensive as well. We will discuss approaches to data mining, data standards, and software tools to enable a more rational approach to the process of crystallogenesis.
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