9 research outputs found
On converse bounds for classical communication over quantum channels
We explore several new converse bounds for classical communication over
quantum channels in both the one-shot and asymptotic regimes. First, we show
that the Matthews-Wehner meta-converse bound for entanglement-assisted
classical communication can be achieved by activated, no-signalling assisted
codes, suitably generalizing a result for classical channels. Second, we derive
a new efficiently computable meta-converse on the amount of classical
information unassisted codes can transmit over a single use of a quantum
channel. As applications, we provide a finite resource analysis of classical
communication over quantum erasure channels, including the second-order and
moderate deviation asymptotics. Third, we explore the asymptotic analogue of
our new meta-converse, the -information of the channel. We show that
its regularization is an upper bound on the classical capacity, which is
generally tighter than the entanglement-assisted capacity and other known
efficiently computable strong converse bounds. For covariant channels we show
that the -information is a strong converse bound.Comment: v3: published version; v2: 18 pages, presentation and results
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X‑ray Crystal Structure of Phosphodiesterase 2 in Complex with a Highly Selective, Nanomolar Inhibitor Reveals a Binding-Induced Pocket Important for Selectivity
To better understand the structural
origins of inhibitor selectivity
of human phosphodieasterase families (PDEs 1–11), here we report
the X-ray crystal structure of PDE2 in complex with a highly selective,
nanomolar inhibitor (BAY60-7550) at 1.9 Å resolution, and the
structure of apo PDE2 at 2.0 Å resolution. The crystal structures
reveal that the inhibitor binds to the PDE2 active site by using not
only the conserved glutamine-switch mechanism for substrate binding,
but also a binding-induced, hydrophobic pocket that was not reported
previously. <i>In silico</i> affinity profiling by molecular
docking indicates that the inhibitor binding to this pocket contributes
significantly to the binding affinity and thereby improves the inhibitor
selectivity for PDE2. Our results highlight a structure-based design
strategy that exploits the potential binding-induced pockets to achieve
higher selectivity in the PDE inhibitor development
X‑ray Crystal Structure of Phosphodiesterase 2 in Complex with a Highly Selective, Nanomolar Inhibitor Reveals a Binding-Induced Pocket Important for Selectivity
To better understand the structural
origins of inhibitor selectivity
of human phosphodieasterase families (PDEs 1–11), here we report
the X-ray crystal structure of PDE2 in complex with a highly selective,
nanomolar inhibitor (BAY60-7550) at 1.9 Å resolution, and the
structure of apo PDE2 at 2.0 Å resolution. The crystal structures
reveal that the inhibitor binds to the PDE2 active site by using not
only the conserved glutamine-switch mechanism for substrate binding,
but also a binding-induced, hydrophobic pocket that was not reported
previously. <i>In silico</i> affinity profiling by molecular
docking indicates that the inhibitor binding to this pocket contributes
significantly to the binding affinity and thereby improves the inhibitor
selectivity for PDE2. Our results highlight a structure-based design
strategy that exploits the potential binding-induced pockets to achieve
higher selectivity in the PDE inhibitor development
Additional file 4: Table S3. of Evolution, gene expression profiling and 3D modeling of CSLD proteins in cotton
Comparison of ML and Bayesian trees based on three alignments (Kalign, Mafft and Muscle) using Ktreedist. (DOCX 33Â kb
Additional file 10: Table S15. of Evolution, gene expression profiling and 3D modeling of CSLD proteins in cotton
Model validation scores of the full-length GrCSLD1 protein. (DOCX 22Â kb
Additional file 5: Figure S1. of Evolution, gene expression profiling and 3D modeling of CSLD proteins in cotton
The different topologies of cotton CSLD trees reconstructed from ML and Bayesian based on three alignments and the elision strategy. Support values are shown for A. thaliana-cotton and cotton CSLD nodes using different color circles as bootstrap proportions/SH-like aLRT scores/Bayesian posterior probabilities. The cotton CSLD protein clades are indicated by different colors. âOther CSLDâ indicates the CSLD proteins from other plant species. (TIFF 2007Â kb
Additional file 11: Table S4, 5 and 6. of Evolution, gene expression profiling and 3D modeling of CSLD proteins in cotton
The source of transcriptome data from G. hirsutum, G. arboreum and G. raimondii. (XLSX 12Â kb
Additional file 9: Figure S4. of Evolution, gene expression profiling and 3D modeling of CSLD proteins in cotton
Multiple sequence alignments of GrCSLD1, GhCESA1, BcsA and ATCSLD1. The secondary structure of GrCSLD1 was calculated using the DSS algorithm of PyMOL. The violet cylinders, yellow arrows, and black lines indicate the α-helices, β-strand and coil of GrCSLD1; the red rectangles and yellow rectangles indicate the α-helices and β-strand of GhCESA1, and the red lines and yellow lines indicate the α-helices and β-strand of BcsA. The plant-conserved region (P-CR) and class-specific region (CSR) are highlighted with blue and green lines. Large red letters indicate sites of episodic positive selection in GrCSLD1. (TIFF 4834 kb
Additional file 14: Table S14. of Evolution, gene expression profiling and 3D modeling of CSLD proteins in cotton
The relative expression level of CSLD genes of G. hirsutum by comparative 2-ÎÎCT method using qRT-PCR. (XLSX 10Â kb