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The hERG1 gene (Kv11.1) encodes a voltage-gated potassium channel. Mutations in this gene lead to one form of the Long QT Syndrome (LQTS) in humans. Promiscuous binding of drugs to hERG1 is known to alter the structure/function of the channel leading to an acquired form of the LQTS. Expectably, creation and validation of reliable 3D model of the channel have been a key target in molecular cardiology and pharmacology for the last decade. Although many models were built, they all were limited to pore domain. In this work, a full model of the hERG1 channel is developed which includes all transmembrane segments. We tested a template-driven de-novo design with ROSETTA-membrane modeling using side-chain placements optimized by subsequent molecular dynamics (MD) simulations. Although backbone templates for the homology modeled parts of the pore and voltage sensors were based on the available structures of KvAP, Kv1.2 and Kv1.2-Kv2.1 chimera channels, the missing parts are modeled de-novo. The impact of several alignments on the structure of the S4 helix in the voltage-sensing domain was also tested. Herein, final models are evaluated for consistency to the reported structural elements discovered mainly on the basis of mutagenesis and electrophysiology. These structural elements include salt bridges and close contacts in the voltage-sensor domain; and the topology of the extracellular S5-pore linker compared with that established by toxin foot-printing and nuclear magnetic resonance studies. Implications of the refined hERG1 model to binding of blockers and channels activators (potent new ligands for channel activations) are discussed.
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http://dx.doi.org/10.1002/prot.22815 | DOI Listing |
JCI Insight
September 2025
Diabetes & Metabolism Research Center, University of Utah, Salt Lake City, United States of America.
Impaired muscle regrowth in aging is underpinned by reduced pro-inflammatory macrophage function and subsequently impaired muscle cellular remodeling. Macrophage phenotype is metabolically controlled through TCA intermediate accumulation and activation of HIF1A. We hypothesized that transient hypoxia following disuse in old mice would enhance macrophage metabolic inflammatory function thereby improving muscle cellular remodeling and recovery.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Life Science Center for Survival Dynamics, Tsukuba Advanced Research Alliance, University of Tsukuba, Tsukuba 305-8577, Japan.
All organisms are exposed to various stressors, which can sometimes lead to organismal death, depending on their intensity. While stress-induced organismal death has been observed in many species, the underlying mechanisms remain unclear. In this study, we investigated the molecular mechanisms of stress-induced organismal death in the fruit fly .
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Soft Matter Sciences and Engineering, CNRS, École supérieure de Physique et de Chimie Industrielles de la Ville de Paris, Université Paris Sciences et Lettres, Sorbonne Université, Paris 75005, France.
The sliding motion of aqueous droplets on hydrophobic surfaces leads to charge separation at the trailing edge, with implications from triple-line friction to hydrovoltaic energy generation. Charges deposited on the solid surface have been attributed to ions or electrons ripped off from the liquid drop. However, the dynamics and exact physicochemical nature of these surface-trapped charges remains poorly explored.
View Article and Find Full Text PDFJ Biomol Struct Dyn
September 2025
Department of Biology, Faculty of Science, University of Sistan and Baluchestan, Zahedan, Iran.
Acetylesterase, produced by , plays a crucial role in deacetylating hemicellulose during pulp production. Thermostable variants of this enzyme, although rare, can significantly enhance industrial efficiency by retaining activity at high temperatures. This research aims to design a thermostable variant of acetylesterase from (EC 3.
View Article and Find Full Text PDFNanoscale
September 2025
School of Materials Science and Engineering, Beihang University, Beijing 100191, China.
The challenge of photocatalytic hydrogen production has motivated a targeted search for MXenes as a promising class of materials for this transformation because of their high mobility and high light absorption. High-throughput screening has been widely used to discover new materials, but the relatively high cost limits the chemical space for searching MXenes. We developed a deep-learning-enabled high-throughput screening approach that identified 14 stable candidates with suitable band alignment for water splitting from 23 857 MXenes.
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