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Molybdenum and tungsten enzymes require specific chaperones for folding and cofactor insertion. PaoD is the chaperone of the periplasmic aldehyde oxidoreductase PaoABC. It is the last gene in the paoABCD operon in Escherichia coli and its presence is crucial for obtaining mature enzyme. PaoD is an unstable, 35 kDa, protein. Our biochemical studies showed that it is a dimer in solution with a tendency to form large aggregates, especially after freezing/thawing cycles. In order to improve stability, PaoD was thawed in the presence of two ionic liquids [C(4)mim]Cl and [C(2)OHmim]PF6 and no protein precipitation was observed. This allowed protein concentration and crystallization using polyethylene glycol or ammonium sulfate as precipitating agents. Saturation transfer difference - nuclear magnetic resonance (STD-NMR) experiments have also been performed in order to investigate the effect of the ionic liquids in the stabilization process, showing a clear interaction between the acidic ring protons of the cation and, most likely, negatively charged residues at the protein surface. DLS assays also show a reduction of the overall size of the protein aggregates in presence of ionic liquids. Furthermore, cofactor binding studies on PaoD showed that the protein is able to discriminate between molybdenum and tungsten bound to the molybdenum cofactor, since only a Mo-MPT form of the cofactor remained bound to PaoD.
Aldehyde oxidase (AOX) is characterized by a broad substrate specificity, oxidizing aromatic azaheterocycles, such as N(1)-methylnicotinamide and N-methylphthalazinium, or aldehydes, such as benzaldehyde, retinal, and vanillin. In the past decade, AOX has been recognized increasingly to play an important role in the metabolism of drugs through its complex cofactor content, tissue distribution, and substrate recognition. In humans, only one AOX gene (AOX1) is present, but in mouse and other mammals different AOX homologs were identified. The multiple AOX isoforms are expressed tissue-specifically in different organisms, and it is believed that they recognize distinct substrates and carry out different physiological tasks. AOX is a dimer with a molecular mass of approximately 300 kDa, and each subunit of the homodimeric enzyme contains four different cofactors: the molybdenum cofactor, two distinct [2Fe-2S] clusters, and one FAD. We purified the AOX homolog from mouse liver (mAOX3) and established a system for the heterologous expression of mAOX3 in Escherichia coli. The purified enzymes were compared. Both proteins show the same characteristics and catalytic properties, with the difference that the recombinant protein was expressed and purified in a 30% active form, whereas the native protein is 100% active. Spectroscopic characterization showed that FeSII is not assembled completely in mAOX3. In addition, both proteins were crystallized. The best crystals were from native mAOX3 and diffracted beyond 2.9 angstrom. The crystals belong to space group P1, and two dimers are present in the unit cell.
This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.