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Drug-target kinetics enable time-dependent changes in target engagement to be quantified as a function of drug concentration. When coupled to drug pharmacokinetics (PK), drug-target kinetics can thus be used to predict in vivo pharmacodynamics (PD). Previously we described a mechanistic PK/PD model that successfully predicted the antibacterial activity of an LpxC inhibitor in a model of Pseudomonas aeruginosa infection. In the present work we demonstrate that the same approach can be used to predict the in vivo activity of an enoyl-ACP reductase (FabI) inhibitor in a model of methicillin-resistant Staphylococcus aureus (MRSA) infection. This is significant because the LpxC inhibitors are cidal, whereas the FabI inhibitors are static. In addition P. aeruginosa is a Gram-negative organism whereas MRSA is Gram-positive. Thus this study supports the general applicability of our modeling approach across antibacterial space.
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
(2016)
Background
A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.
Results
We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.
Conclusions
The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
Multichromophoric macrocycles and cyclophanes are important supramolecular architectures for the elucidation of interchromophoric interactions originating from precise spatial organization. Herein, by combining an axially chiral binaphthol bisimide (BBI) and a bay-substituted conformationally labile twisted perylene bisimide (PBI) within a cyclophane of well-defined geometry, we report a chiral PBI hetero-cyclophane (BBI-PBI) that shows intramolecular energy and solvent-regulated chirality transfer from the BBI to the PBI subunit. Excellent spectral overlap and spatial arrangement of BBI and PBI lead to efficient excitation energy transfer and subsequent PBI emission with high quantum yield (80–98 %) in various solvents. In contrast, chirality transfer is strongly dependent on the respective solvent as revealed by circular dichroism (CD) spectroscopy. The combination of energy and chirality transfer affords a bright red circularly polarized luminescence (CPL) from the PBI chromophore by excitation of BBI.
Coal mining, an important human activity, disturbs soil organic carbon (SOC) accumulation and decomposition, eventually affecting terrestrial carbon cycling and the sustainability of human society. However, changes of SOC content and their relation with influential factors in coal mining areas remained unclear. In the study, predictive models of SOC content were developed based on field sampling and Landsat images for different land-use types (grassland, forest, farmland, and bare land) of the largest coal mining area in China (i.e., Shendong). The established models were employed to estimate SOC content across the Shendong mining area during 1990–2020, followed by an investigation into the impacts of climate change and human disturbance on SOC content by a Geo-detector. Results showed that the models produced satisfactory results (R\(^2\) > 0.69, p < 0.05), demonstrating that SOC content over a large coal mining area can be effectively assessed using remote sensing techniques. Results revealed that average SOC content in the study area rose from 5.67 gC·kg\(^{−1}\) in 1990 to 9.23 gC·kg\(^{−1}\) in 2010 and then declined to 5.31 gC·Kg\(^{−1}\) in 2020. This could be attributed to the interaction between the disturbance of soil caused by coal mining and the improvement of eco-environment by land reclamation. Spatially, the SOC content of farmland was the highest, followed by grassland, and that of bare land was the lowest. SOC accumulation was inhibited by coal mining activities, with the effect of high-intensity mining being lower than that of moderate- and low-intensity mining activities. Land use was found to be the strongest individual influencing factor for SOC content changes, while the interaction between vegetation coverage and precipitation exerted the most significant influence on the variability of SOC content. Furthermore, the influence of mining intensity combined with precipitation was 10 times higher than that of mining intensity alone.
The blunt snout bream Megalobrama amblycephala is the economically most important cyprinid fish species. As an herbivore, it can be grown by eco-friendly and resource-conserving aquaculture. However, the large number of intermuscular bones in the trunk musculature is adverse to fish meat processing and consumption. As a first towards optimizing this aquatic livestock, we present a 1.116-Gb draft genome of M. amblycephala, with 779.54 Mb anchored on 24 linkage groups. Integrating spatiotemporal transcriptome analyses, we show that intermuscular bone is formed in the more basal teleosts by intramembranous ossification and may be involved in muscle contractibility and coordinating cellular events. Comparative analysis revealed that olfactory receptor genes, especially of the beta type, underwent an extensive expansion in herbivorous cyprinids, whereas the gene for the umami receptor T1R1 was specifically lost in M. amblycephala. The composition of gut microflora, which contributes to the herbivorous adaptation of M. amblycephala, was found to be similar to that of other herbivores. As a valuable resource for the improvement of M. amblycephala livestock, the draft genome sequence offers new insights into the development of intermuscular bone and herbivorous adaptation.
Unexpected edge conduction in mercury telluride quantum wells under broken time-reversal symmetry
(2015)
The realization of quantum spin Hall effect in HgTe quantum wells is considered a milestone in the discovery of topological insulators. Quantum spin Hall states are predicted to allow current flow at the edges of an insulating bulk, as demonstrated in various experiments. A key prediction yet to be experimentally verified is the breakdown of the edge conduction under broken time-reversal symmetry. Here we first establish a systematic framework for the magnetic field dependence of electrostatically gated quantum spin Hall devices. We then study edge conduction of an inverted quantum well device under broken time-reversal symmetry using microwave impedance microscopy, and compare our findings to a noninverted device. At zero magnetic field, only the inverted device shows clear edge conduction in its local conductivity profile, consistent with theory. Surprisingly, the edge conduction persists up to 9 T with little change. This indicates physics beyond simple quantum spin Hall model, including material-specific properties and possibly many-body effects.