The AutoDock suite at 30

The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third‐party developers.     

Impacts of remotely sensed environmental drivers on coral outplant survival

Globally, coral reefs are degrading due to a variety of stressors including climate change and pollution. Active restoration is an important effort for sustaining coral reefs where, typically, coral fragments are outplanted onto degraded reefs. Coral outplants, however, can experience mortality in response to a range of stressors. We pair results of outplant monitoring observations with satellite‐based measurements of multiple oceanographic variables to estimate the relative importance of each driver to coral outplant survival. We find that when considering mean environmental conditions experienced by outplants during the monitoring period, particulate organic carbon (POC) levels are most important in determining outplant survival, with certain levels of POC beneficial for outplants. Sea surface temperature anomalies (SSTA) are also important determinants of outplant survival, where survival is greatest in regions with minimal or slightly negative anomalies. Survival also increases with increasing distance to land, likely due to a reduction in negative ridge‐to‐reef effects on coral outplants. When considering the range (min–max) of environmental conditions experienced during the monitoring period, large fluctuations in photosynthetically active radiation (PAR) and POC are most important in determining outplant survival. Increasing outplant depth can help to counter the negative impacts of large fluctuations in environmental variables. We find that a variety of remotely sensed oceanographic variables have significant impacts on survival and should be considered in coral restoration planning to help evaluate potential restoration sites and ultimately maximize coral outplant survival.     

Production and characterization of a cold-active and n-hexane activated lipase from a newly isolated Serratia grimesii RB06-22

Abstract

A lipase-producing bacterium isolated from raw milk was identified as Serratia grimesii based on 16S rRNA sequence analysis. The extracellular lipase was partially purified by ammonium sulfate precipitation and ultrafiltration. Maximal activity was observed at 10°C, the optimum pH was 8.0 and the enzyme was stable at 5–30°C for 1 h. The K_m and V_max values were 1.7 mM and 0.3 mM/min respectively. It was found that the lipase had the highest hydrolytic activity towards sunflower oil and soybean oil. CaCl₂ had a stimulatory effect on lipase activity, while EDTA and iodoacetic acid slightly inhibited the lipase activity and the enzyme was strongly inhibited by PMSF. The enzyme was compatible with various non-ionic surfactants as well as sodium cholate and saponin. In addition, the enzyme was relatively stable towards oxidizing agents. This lipase exhibited maximum activity in 35% n-hexane retaining about 2191% activity for 1 h.     

Influence of environmental factors on content and composition of essential oil from common juniper ripe berry cones (Juniperus communis L.)

Abstract

The present study evaluated the influence of some environmental factors on the quantity and composition of essential oil (EO) in ripe berry cones of Juniperus communis L. The berry cones were collected from juniper shrubs growing wild at five localities of north-east Slovakia during the years 2012–2014. The EO yield ranged from 0.4 to 1.9%, depending on the locality and year. In the EO, eight monoterpenes (α-pinene, β-pinene, β-myrcene, sabinene, limonene, terpinene-4-ol, borneol, bornylacetate) and one sesquiterpene (β-caryophyllene) were identified. The dominant component was the monoterpene α-pinene, ranging from 31.0 to 49.0%. The amount and composition of the EO was affected by soil composition (content of humus and pH) and topographic environmental factors, including air temperature and precipitation. According to the composition of the EO, the studied juniper shrubs belong to the α-pinene chemotype.     

The Active and the Inactive Form of the hAT1 Receptor Have an Identical Ligand-Binding Environment: An MPA Study on a Constitutively Active Angiotensin II Receptor Mutant

Several models of activation mechanisms were proposed for G protein-coupled receptors (GPCRs), yet no direct methods exist for their elucidation. The availability of constitutively active mutants has given an opportunity to study active receptor conformations within acceptable limits using models such as the angiotensin II type 1 (AT₁)¹ receptor mutant N111G-hAT₁ which displays an important constitutive activity. Recently, by using methionine proximity assay, we showed for the hAT₁ receptor that TMD III, VI, and VII form the ligand-binding pocket of the C-terminal amino acid of an antagonistic AngII analogue. In the present contribution, we investigated whether the same residues would also constitute the ligand-binding contacts in constitutively activated mutant (CAM) receptors. For this purpose, the same Met mutagenesis strategy was carried out on the N111G double mutants. Analysis of 43 receptors mutants in the N111G-hAT₁ series, photolabeled and CNBr digested, showed that there were only subtle structural changes between the wt-receptor and its constitutively active form.     

Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data

This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C₃ and C₄) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPAR_ps) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R² > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry‐grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R² > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPAR_ps) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPAR_ps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution.     

5-Hydroxymethylcytosine is an essential intermediate of active DNA demethylation processes in primary human monocytes

Background

Cytosine methylation is a frequent epigenetic modification restricting the activity of gene regulatory elements. Whereas DNA methylation patterns are generally inherited during replication, both embryonic and somatic differentiation processes require the removal of cytosine methylation at specific gene loci to activate lineage-restricted elements. However, the exact mechanisms facilitating the erasure of DNA methylation remain unclear in many cases.

Results

We previously established human post-proliferative monocytes as a model to study active DNA demethylation. We now show, for several previously identified genomic sites, that the loss of DNA methylation during the differentiation of primary, post-proliferative human monocytes into dendritic cells is preceded by the local appearance of 5-hydroxymethylcytosine. Monocytes were found to express the methylcytosine dioxygenase Ten-Eleven Translocation (TET) 2, which is frequently mutated in myeloid malignancies. The siRNA-mediated knockdown of this enzyme in primary monocytes prevented active DNA demethylation, suggesting that TET2 is essential for the proper execution of this process in human monocytes.

Conclusions

The work described here provides definite evidence that TET2-mediated conversion of 5-methylcytosine to 5-hydroxymethylcytosine initiates targeted, active DNA demethylation in a mature postmitotic myeloid cell type.     

Behavioral responses of satellite tracked Blainville's beaked whales (Mesoplodon densirostris) to mid-frequency active sonar

The vulnerability of beaked whales (Family: Ziphiidae) to intense sound exposure has led to interest in their behavioral responses to mid-frequency active sonar (MFAS, 3–8 kHz). Here we present satellite-transmitting tag movement and dive behavior records from Blainville's beaked whales (Mesoplodon densirostris) tagged in advance of naval sonar exercises at the Atlantic Undersea Test and Evaluation Center (AUTEC) in the Bahamas. This represents one of the largest samples of beaked whales individually tracked during sonar operations (n = 7). The majority of individuals (five of seven) were displaced 28–68 km after the onset of sonar exposure and returned to the AUTEC range 2–4 days after exercises ended. Modeled sound pressure received levels were available during the tracking of four individuals and three of those individuals showed declines from initial maxima of 145–172 dB re 1 μPa to maxima of 70–150 dB re 1 μPa following displacements. Dive behavior data from tags showed a continuation of deep diving activity consistent with foraging during MFAS exposure periods, but also suggested reductions in time spent on deep dives during initial exposure periods. These data provide new insights into behavioral responses to MFAS and have important implications for modeling the population consequences of disturbance.     

Sequential adaptive variables and subject selection for GEE methods

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process—such as the active-learning methods found in the machine-learning literature—will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method.