Phosphoenolpyruvate carboxykinase (PCK) catalyzes the conversion of oxaloacetate (OAA) to PEP and carbon dioxide with the subsequent conversion of nucleoside triphosphate to nucleoside diphosphate (NDP). The 1.9 A resolution structure of Escherichia coli PCK consisted of a 275-residue N-terminal domain and a 265-residue C-terminal domain with the active site located in a cleft between these domains. Each domain has an alpha/beta topology and the overall structure represents a new protein fold. Furthermore, PCK has a unique mononucleotide-binding fold. The 1.8 A resolution structure of the complex of ATP/Mg(2+)/oxalate with PCK revealed a 20 degrees hinge-like rotation of the N- and C-terminal domains, which closed the active site cleft. The ATP was found in the unusual syn conformation as a result of binding to the enzyme. Along with the side chain of Lys254, Mg(2+) neutralizes charges on the P beta and P gamma oxygen atoms of ATP and stabilizes an extended, eclipsed conformation of the P beta and P gamma phosphoryl groups. The sterically strained high-energy conformation likely lowers the free energy of activation for phosphoryl transfer. Additionally, the gamma-phosphoryl group becomes oriented in-line with the appropriate enolate oxygen atom, which strongly supports a direct S(N)2-type displacement of this gamma-phosphoryl group by the enolate anion. In the 2.0 A resolution structure of the complex of PCK/ADP/Mg(2+)/AlF(3), the AlF(3) moiety represents the phosphoryl group being transferred during catalysis. There are three positively charged groups that interact with the fluorine atoms, which are complementary to the three negative charges that would occur for an associative transition state.
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http://dx.doi.org/10.1016/j.bbapap.2003.11.030 | DOI Listing |
Sci Rep
December 2024
Department of Civil Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Deep learning models are widely used for traffic forecasting on freeways due to their ability to learn complex temporal and spatial relationships. In particular, graph neural networks, which integrate graph theory into deep learning, have become popular for modeling traffic sensor networks. However, traditional graph convolutional networks (GCNs) face limitations in capturing long-range spatial correlations, which can hinder accurate long-term predictions.
View Article and Find Full Text PDFThe proximity ligation-based Hi-C and derivative methods are the mainstream tools to study genome-wide chromatin interactions. These methods often fragment the genome using enzymes functionally irrelevant to the interactions per se, restraining the efficiency in identifying structural features and the underlying regulatory elements. Here we present Footprint-C, which yields high-resolution chromatin contact maps built upon intact and genuine footprints protected by transcription factor (TF) binding.
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December 2024
School of Computer and Information Engineering, Hubei Normal University, Huangshi, 435002, China.
For finely representation of complex reservoir units, higher computing overburden and lower spatial resolution are limited to traditional stochastic simulation. Therefore, based on Generative Adversarial Networks (GANs), spatial distribution patterns of regional variables can be reproduced through high-order statistical fitting. However, parameters of GANs cannot be optimized under insufficient training samples.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.
Neurodegeneration in Huntington's disease (HD) is accompanied by the aggregation of fragments of the mutant huntingtin protein, a biomarker of disease progression. A particular pathogenic role has been attributed to the aggregation-prone huntingtin exon 1 (HTTex1), generated by aberrant splicing or proteolysis, and containing the expanded polyglutamine (polyQ) segment. Unlike amyloid fibrils from Parkinson's and Alzheimer's diseases, the atomic-level structure of HTTex1 fibrils has remained unknown, limiting diagnostic and treatment efforts.
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December 2024
Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA.
Millimeter-wave and terahertz integrated circuits and chips are expected to serve as the backbone for future wireless networks and high resolution sensing. However, design of these integrated circuits and chips can be quite complex, requiring years of human expertise, careful tailoring of hand crafted circuit topologies and co-design with parameterized and pre-selected templates of electromagnetic structures. These structures (radiative and non-radiative, single-port and multi-ports) are subsequently optimized through ad-hoc methods and parameter sweeps.
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