Modeling of metal interaction geometries for protein-ligand docking

The accurate modeling of metal coordination geometries plays an important role for structure-based drug design applied to metalloenzymes. For the development of a new metal interaction model, we perform a statistical analysis of metal interaction geometries that are relevant to protein-ligand complexes. A total of 43,061 metal sites of the Protein Data Bank (PDB), containing amongst others magnesium, calcium, zinc, iron, manganese, copper, cadmium, cobalt, and nickel, were evaluated according to their metal coordination geometry. Based on statistical analysis, we derived a model for the automatic calculation and definition of metal interaction geometries for the purpose of molecular docking analyses. It includes the identification of the metal-coordinating ligands, the calculation of the coordination geometry and the superposition of ideal polyhedra to identify the optimal positions for free coordination sites. The new interaction model was integrated in the docking software FlexX and evaluated on a data set of 103 metalloprotein-ligand complexes, which were extracted from the PDB. In a first step, the quality of the automatic calculation of the metal coordination geometry was analyzed. In 74% of the cases, the correct prediction of the coordination geometry could be determined on the basis of the protein structure alone. Secondly, the new metal interaction model was tested in terms of predicting protein-ligand complexes. In the majority of test cases, the new interaction model resulted in an improved docking accuracy of the top ranking placements.     

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

Background

Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images.

Methodology/Principal Findings

Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R² ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001).

Conclusion/Significance

In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.     

Efficient Evaluation of Ranking Procedures when the Number of Units is Large,with Application to SNP Identification

Simulation‐based assessment is a popular and frequently necessary approach for evaluating statistical procedures. Sometimes overlooked is the ability to take advantage of underlying mathematical relations and we focus on this aspect. We show how to take advantage of large‐sample theory when conducting a simulation using the analysis of genomic data as a motivating example. The approach uses convergence results to provide an approximation to smaller‐sample results, results that are available only by simulation. We consider evaluating and comparing various ranking‐based methods for identifying the most highly associated SNPs in a genome‐wide association study, derive integral equation representations of the pre‐posterior distribution of percentiles produced by three ranking methods, and provide examples comparing performance. These results are of interest in their own right and set the framework for a more extensive set of comparisons.     

Gaseous NO2 as a regulator for ammonia oxidation of Nitrosomonas eutropha

Cells of Nitrosomonas eutropha strain N904 that were denitrifying under anoxic conditions with hydrogen as electron donor and nitrite as electron acceptor were unable to utilize ammonium (ammonia) as an energy source. The recovery of ammonia oxidation activity was dependent on the presence of NO₂. Anaerobic ammonia oxidation activity was observed in a helium atmosphere supplemented with 25 ppm NO₂ after 20 h. Ammonia oxidation activity was detected after 2–3 days using an oxic atmosphere with 25 ppm NO₂. In contrast, ammonia consumption started after 8–9 days under oxic conditions without the addition of NO₂; in this case, small amounts of NO and NO₂ were detected and their concentrations increased with increasing ammonia oxidation activities. Hardly any ammonia oxidation was detected when nitrogen oxides were removed by intensive aeration. It would seem, therefore, that NO₂ is the master regulatory signal for ammonia oxidation in Nitrosomonas eutropha. Anaerobic ammonia oxidation activity was inhibited by the addition of NO. This inhibition was partly compensated by either increasing the NO₂ concentration or by using 2,3-dimercapto-1-propane-sulfonic acid as a NO binding substrate. DMPS was inhibitory to nitrification under oxic conditions, while increased amounts of NO or NO₂ led to increased oxidation activities.     

Functional domains of the ubiquitous chromatin protein DEK

DEK was originally described as a proto-oncogene protein and is now known to be a major component of metazoan chromatin. DEK is able to modify the structure of DNA by introducing supercoils. In order to find interaction partners and functional domains of DEK, we performed yeast two-hybrid screens and mutational analyses. Two-hybrid screening yielded C-terminal fragments of DEK, suggesting that DEK is able to multimerize. We could localize the domain to amino acids 270 to 350 and show that multimerization is dependent on phosphorylation by CK2 kinase in vitro. We also found two DNA binding domains of DEK, one on a fragment including amino acids 87 to 187 and containing the SAF-box DNA binding motif, which is located between amino acids 149 and 187. This region is sufficient to introduce supercoils into DNA. The second DNA binding domain is located between amino acids 270 and 350 and thus overlaps the multimerization domain. We show that the two DNA-interacting domains differ in their binding properties and in their abilities to respond to CK2 phosphorylation.     

Adaptive Growth of Gymnosperm Branches-Ultrastructural and Micromechanical Examinations

The top, the lateral and the underside of basal branch segments of two gymnosperm species, spruce (Picea abies [L.] Karst.) and yew (Taxus baccata L.), were studied with respect to possible adaptation in structural and mechanical properties. Microtensile tests were performed on thin wet foils, which were removed from the periphery of the branches. Structural parameters such as density and the microfibril angle in the S2-layer were examined to investigate the structure-function relationships of the branch wood. The top, the lateral and the underside of both branches showed significant differences in their structural and mechanical properties. However, no significant variations were observed as a function of age and size development. The findings were discussed in view of adaptive growth strategies of trees, including biomechanical constraints of a horizontally growing branch.     

A molecular docking study of estrogenically active compounds with 1,2-diarylethane and 1,2-diarylethene pharmacophores

Numerous selective estrogen receptor modulators (SERMs) have been synthesized and assayed in recent years. The focus of this study is to apply coarse-grain molecular docking procedures coupled with fine-grain all-atom force field optimization strategies to shed light on the binding mechanisms of currently available estrogen receptor-active compounds. Although the mechanics of ligand binding in estrogen receptors is generally well understood, there is room for surprises. In this paper computational evidence corroborating the experimentally observed type I agonistic binding mode for estradiol (E2) and diethylstilbesterol (DES) and the type II antagonistic binding mode for 4-hydroxytamoxifen and raloxifen is presented. Included in this type I agonistic mode are the DES derivatives, transstilbene and 1,2-diaryldiaminoethane. In addition, a novel ‘type II agonistic’ binding mode for 2,3-diarylimidazolines, 4,5-diarylimidazoles, 2,3-diarylpiperazines is introduced. This mode is stabilized by suggesting alternative hydrogen bond anchor points in the ligand binding domain as potential leads for future drug design.