Differential Binding of Co(II) and Zn(II) to Metallo-β-Lactamase Bla2 from \u3cem\u3eBacillus anthracis\u3c/em\u3e

In an effort to probe the structure, mechanism, and biochemical properties of metallo-β-lactamase Bla2 from Bacillus anthracis, the enzyme was overexpressed, purified, and characterized. Metal analyses demonstrated that recombinant Bla2 tightly binds 1 equiv of Zn(II). Steady-state kinetic studies showed that mono-Zn(II) Bla2 (1Zn-Bla2) is active, while di-Zn(II) Bla2 (ZnZn-Bla2) was unstable. Catalytically, 1Zn-Bla2 behaves like the related enzymes CcrA and L1. In contrast, di-Co(II) Bla2 (CoCo-Bla2) is substantially more active than the mono-Co(II) analogue. Rapid kinetics and UV−vis, 1H NMR, EPR, and EXAFS spectroscopic studies show that Co(II) binding to Bla2 is distributed, while EXAFS shows that Zn(II) binding is sequential. To our knowledge, this is the first documented example of a Zn enzyme that binds Co(II) and Zn(II) via distinct mechanisms, underscoring the need to demonstrate transferability when extrapolating results on Co(II)-substituted proteins to the native Zn(II)-containing forms

Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots

A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified

Principles for Understanding the Accuracy of SHAPE-Directed RNA Structure Modeling

Accurate RNA structure modeling is an important, incompletely solved, challenge. Single-nucleotide resolution SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) yields an experimental measurement of local nucleotide flexibility that can be incorporated as pseudo-free energy change constraints to direct secondary structure predictions. Prior work from our laboratory has emphasized both the overall accuracy of this approach and the need for nuanced interpretation of some apparent discrepancies between modeled and accepted structures. Recent studies by Das and colleagues [Kladwang et al., Biochemistry 50:8049 (2011) and Nat. Chem. 3:954 (2011)], focused on analyzing six small RNAs, yielded poorer RNA secondary structure predictions than expected based on prior benchmarking efforts. To understand the features that led to these divergent results, we re-examined four RNAs yielding the poorest results in this recent work – tRNAPhe, the adenine and cyclic-di-GMP riboswitches, and 5S rRNA. Most of the errors reported by Das and colleagues reflected non-standard experiment and data processing choices, and selective scoring rules. For two RNAs, tRNAPhe and the adenine riboswitch, secondary structure predictions are nearly perfect if no experimental information is included but were rendered inaccurate by the Das and colleagues SHAPE data. When best practices were used, single-sequence SHAPE-directed secondary structure modeling recovered ~93% of individual base pairs and greater than 90% of helices in the four RNAs, essentially indistinguishable from the mutate-and-map approach with the exception of a single helix in the 5S rRNA. The field of experimentally-directed RNA secondary structure prediction is entering a phase focused on the most difficult prediction challenges. We outline five constructive principles for guiding this field forward

The impact of the enlargement of the nuclear power plant 'Paks' (Hungary) on groundwater resources in Vojvodina

The current decision of the neighbouring Republic of Hungary to enlarge the capacities of the existing nuclear power plant 'Paks', located on the Danube river, by two new reactors, poses a significant issue which requires extensive assessment of all aspects of the impact of such a decision on the environment in the given region due to the proximity to the territory of the Republic of Serbia. The paper is concerned with the impact of the future nuclear complex's functioning on groundwater resources in Vojvodina, based on experience in the area of groundwater reserve formation in the region of the Pannonian Basin, its utilization and protection. Furthermore, an impact assessment has been given, relative to the strategic solution for future water supply system of the northern and north-western Bačka region, according to which the construction of a groundwater regional source in the Danube alluvion near the city of Apatin is planned, an area which was subjected to detailed hydrogeological explorations and hydrodynamic investigation in recent years

A novel Quality Control Framework for the management of existing bridges

The paper presents a framework to evaluate key performance indicators (KPIs) in qualitative manner. This framework is the basis for establishment of Quality Control plans for existing bridges. It addresses the dynamics of the damage processes that allows predicting the point in time, from which the performance goals are not met anymore. The KPIs are defined to address not only road users' but also owner's or operator's perspective as well as environmental and societal concerns. To this end the RAMSSHE€P approach gas been modified. The proposed framework is also illustrated on a simple example

On the significance of an RNA tertiary structure prediction

Tertiary structure prediction is important for understanding structure–function relationships for RNAs whose structures are unknown and for characterizing RNA states recalcitrant to direct analysis. However, it is unknown what root-mean-square deviation (RMSD) corresponds to a statistically significant RNA tertiary structure prediction. We use discrete molecular dynamics to generate RNA-like folds for structures up to 161 nucleotides (nt) that have complex tertiary interactions and then determine the RMSD distribution between these decoys. These distributions are Gaussian-like. The mean RMSD increases with RNA length and is smaller if secondary structure constraints are imposed while generating decoys. The compactness of RNA molecules with true tertiary folds is intermediate between closely packed spheres and a freely jointed chain. We use this scaling relationship to define an expression relating RMSD with the confidence that a structure prediction is better than that expected by chance. This is the prediction significance, and corresponds to a P-value. For a 100-nt RNA, the RMSD of predicted structures should be within 25 Å of the accepted structure to reach the P ≤ 0.01 level if the secondary structure is predicted de novo and within 14 Å if secondary structure information is used as a constraint. This significance approach should be useful for evaluating diverse RNA structure prediction and molecular modeling algorithms