| 1. |
- Bergmann, Justin, et al.
(författare)
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Can the results of quantum refinement be improved with a continuum-solvation model?
- 2021
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Ingår i: Acta Crystallographica. Section B: Structural Science. - 0108-7681. ; 77:6, s. 906-918
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Tidskriftsartikel (refereegranskat)abstract
- Quantum refinement has repeatedly been shown to be a powerful approach to interpret and improve macromolecular crystal structures, allowing for the discrimination between different interpretations of the structure, regarding the protonation states or the nature of bound ligands, for example. In this method, the empirical restraints, used to supplement the crystallographic raw data in standard crystallographic refinement, are replaced by more accurate quantum mechanical (QM) calculations for a small, but interesting, part of the structure. Previous studies have shown that the results of quantum refinement can be improved if the charge of the QM system is reduced by adding neutralizing groups. However, this significantly increases the computation time for the refinement. In this study, we show that a similar improvement can be obtained if the original highly charged QM system is instead immersed in a continuum solvent in the QM calculations. The best results are typically obtained with a high dielectric constant (ε). The continuum solvent improves real-space it Z values, electron-density difference maps and strain energies, and it normally does not affect the discriminatory power of the calculations between different chemical interpretations of the structure. However, for structures with a low charge in the QM system or with a low crystallographic resolution (>2Å), no improvement of the structures is seen.
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| 2. |
- Bergmann, Justin, et al.
(författare)
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Critical evaluation of a crystal structure of nitrogenase with bound N2 ligands
- 2021
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Ingår i: Journal of Biological Inorganic Chemistry. - : Springer Science and Business Media LLC. - 0949-8257 .- 1432-1327. ; 26:2-3, s. 341-353
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Tidskriftsartikel (refereegranskat)abstract
- Recently, a 1.83 Å crystallographic structure of nitrogenase was suggested to show N2-derived ligands at three sites in the catalytic FeMo cluster, replacing the three μ2 bridging sulfide ligands (two in one subunit and the third in the other subunit) (Kang et al. in Science 368: 1381–1385, 2020). Naturally, such a structure is sensational, having strong bearings on the reaction mechanism of the enzyme. Therefore, it is highly important to ensure that the interpretation of the structure is correct. Here, we use standard crystallographic refinement and quantum refinement to evaluate the structure. We show that the original crystallographic raw data are strongly anisotropic, with a much lower resolution in certain directions than others. This, together with the questionable use of anisotropic B factors, give atoms an elongated shape, which may look like diatomic atoms. In terms of standard electron-density maps and real-space Z scores, a resting-state structure with no dissociated sulfide ligands fits the raw data better than the interpretation suggested by the crystallographers. The anomalous electron density at 7100 eV is weaker for the putative N2 ligands, but not lower than for several of the μ3 bridging sulfide ions and not lower than what can be expected from a statistical analysis of the densities. Therefore, we find no convincing evidence for any N2 binding to the FeMo cluster. Instead, a standard resting state without any dissociated ligands seems to be the most likely interpretation of the structure. Likewise, we find no support that the homocitrate ligand should show monodentate binding. Graphic abstract: [Figure not available: see fulltext.].
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| 3. |
- Bergmann, Justin, et al.
(författare)
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Quantum-refinement studies of the bidentate ligand of V‑nitrogenase and the protonation state of CO-inhibited Mo‑nitrogenase
- 2021
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Ingår i: Journal of Inorganic Biochemistry. - : Elsevier BV. - 0162-0134. ; 219
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Tidskriftsartikel (refereegranskat)abstract
- Nitrogenase is the only enzyme that can cleave the triple bond in N2, making nitrogen available to plants (although the enzyme itself is strictly microbial). It has been studied extensively with both experimental and computational methods, but many details of the reaction mechanism are still unclear. X-ray crystallography is the main source of structural information for biomacromolecules, but it has problems to discern hydrogen atoms or to distinguish between elements with the same number of electrons. These problems can sometimes be alleviated by introducing quantum chemical calculations in the refinement, providing information about the ideal structure (in the same way as the empirical restraints used in standard crystallographic refinement) and comparing different interpretations of the structure with normal crystallographic and quantum mechanical quality measures. We have performed such quantum-refinement calculations to address two important issues for nitrogenase. First, we show that the bidentate ligand of the active-site FeV cluster in V‑nitrogenase is carbonate, rather than bicarbonate or nitrate. Second, we study the CO-inhibited structure of Mo‑nitrogenase. CO binds to a reduced and protonated state of the enzyme by replacing one of the sulfide ions (S2B) in the active-site FeMo cluster. We examined if it is possible to deduce from the crystal structure the location of the protons. Our results indicates that the crystal structure is best modelled as fully deprotonated.
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| 4. |
- Singleton, Rosie K., et al.
(författare)
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Risk prediction for renal cell Carcinoma : Results from the European Prospective Investigation into Cancer and nutrition (EPIC) prospective cohort study
- 2021
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Ingår i: Cancer Epidemiology Biomarkers and Prevention. - : AACR. - 1055-9965 .- 1538-7755. ; 30:3, s. 507-512
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Tidskriftsartikel (refereegranskat)abstract
- Background: Early detection of renal cell carcinoma (RCC) has the potential to improve disease outcomes. No screening program for sporadic RCC is in place. Given relatively low incidence, screening would need to focus on people at high risk of clinically meaningful disease so as to limit overdiagnosis and screen-detected false positives. Methods: Among 192,172 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (including 588 incident RCC cases), we evaluated a published RCC risk prediction model (including age, sex, BMI, and smoking status) in terms of discrimination (C-statistic) and calibration (observed probability as a function of predicted probability). We used a flexible parametric survival model to develop an expanded model including age, sex, BMI, and smoking status, with the addition of self-reported history of hypertension and measured blood pressure. Results: The previously published model yielded well-calibrated probabilities and good discrimination (C-statistic [95% CI]: 0.699 [0.679–0.721]). Our model had slightly improved discrimination (0.714 [0.694–0.735], bootstrap optimism-corrected C-statistic: 0.709). Despite this good performance, predicted risk was low for the vast majority of participants, with 70% of participants having 10-year risk less than 0.0025. Conclusions: Although the models performed well for the prediction of incident RCC, they are currently insufficiently powerful to identify individuals at substantial risk of RCC in a general population. Impact: Despite the promising performance of the EPIC RCC risk prediction model, further development of the model, possibly including biomarkers of risk, is required to enable risk stratification of RCC.
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