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Introduction: Excessive phosphorylation of tau protein by the tau-tubulin kinase 1 (TTBK1) enzyme is implicated in the pathogenesis of several neurodegenerative diseases. Based on a comprehensive literature review and availability of the co-crystal structure of TTBK1 in complex inhibitor (pdb id 4BTK), we designed a multiscale computational approach to identify novel hits from the ZINC13 chemical library.
Methods: The High-Throughput Virtual Screening (HTVS) of the ZINC13 database (containing 13,195,609 molecules) was carried out against TTBK1 protein (PDB id 4BTK). Top-scoring molecules and reference molecules were further subjected to MD simulations, PCA analysis, DCCM assay, binding free energies calculations, and in-silico ADME calculations.
Results: From a preliminary HTVS study, six molecules were identified based on their docking scores: ZINC37289024, ZINC89755080, ZINC20993115, ZINC72445968, ZINC28247630, and ZINC16638515, with the docking score of -10.186, -09.229, -09.045, -09.021, -08.920 and -08.821, respectively. In subsequent MD simulations studies, the protein backbone RMSD values were observed to be 1.978, 1.8178, 2.2309, 1.7933, 1.8837, 1.9461, and 1.8711 Å, respectively. Similarly, the protein backbone RMSF values were 0.9511, 1.0172, 1.2023, 1.0591, 1.0029, 1.9755, and 0.9200 Å, respectively. PCA, DCCM, and MMGBSA analysis indicated that these complexes were quite stable throughout the 100 ns MD simulations. In-silico ADME predictions of identified top six hits suggested that these top six hits possess favorable drug-like properties, supporting their potential as the lead candidates for therapeutic development.
Conclusion: A multiscale molecular modelling approach was employed, and six top-scoring hits were identified as promising TTBK1 inhibitors. Analysis of the in-silico data suggested that ZINC37289024 would be the most promising clinical candidate for AD. However, further in-vitro and in-vivo experimental data would be needed for validation of these results.
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http://dx.doi.org/10.2174/0115734099366145250526081959 | DOI Listing |
IEEE Trans Med Imaging
September 2025
Computed Tomography (CT) to Cone-Beam Computed Tomography (CBCT) image registration is crucial for image-guided radiotherapy and surgical procedures. However, achieving accurate CT-CBCT registration remains challenging due to various factors such as inconsistent intensities, low contrast resolution and imaging artifacts. In this study, we propose a Context-Aware Semantics-driven Hierarchical Network (referred to as CASHNet), which hierarchically integrates context-aware semantics-encoded features into a coarse-to-fine registration scheme, to explicitly enhance semantic structural perception during progressive alignment.
View Article and Find Full Text PDFJ Comput Neurosci
September 2025
School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China.
Transcranial alternating current stimulation (tACS) enables non-invasive modulation of brain activity, holding promise for cognitive research and clinical applications. However, it remains unclear how the spiking activity of cortical neurons is modulated by specific electric field (E-field) distributions. Here, we use a multi-scale computational framework that integrates an anatomically accurate head model with morphologically realistic neuron models to simulate the responses of layer 5 pyramidal cells (L5 PCs) to the E-fields generated by conventional M1-SO tACS.
View Article and Find Full Text PDFNucleic Acids Res
September 2025
School of Software, Shandong University, Jinan 250101, Shandong, China.
Spatial transcriptomics (ST) reveals gene expression distributions within tissues. Yet, predicting spatial gene expression from histological images still faces the challenges of limited ST data that lack prior knowledge, and insufficient capturing of inter-slice heterogeneity and intra-slice complexity. To tackle these challenges, we introduce FmH2ST, a foundation model-based method for spatial gene expression prediction.
View Article and Find Full Text PDFFood Res Int
November 2025
Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences (CAAS) / Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China; College of Food Science, Shenyang Agricultural University, Shenyang 110866, China. Electronic a
While restructuring agricultural products enhances heat and mass transfer during freeze-drying, the underlying mechanisms remain poorly understood. This study employed a multiscale approach, combining freezing dynamics, sublimation drying kinetics, X-ray tomography, gas permeability assessments, thermodynamic parameters analysis, and mathematical modeling to systematically investigate the differences in transfer properties between natural and restructured peaches across the freezing and sublimation drying processes. Key results demonstrated that restructuring decreased the freezing time by 21.
View Article and Find Full Text PDFBiomed Phys Eng Express
September 2025
College of Computer Science and Technology, China University of Petroleum East China - Qingdao Campus, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China, Qingdao, Shandong, 266580, CHINA.
Purpose: Cerebrovascular segmentation is crucial for the diagnosis and treatment of cerebrovascular diseases. However, accurately extracting cerebral vessels from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) remains challenging due to the topological complexity and anatomical variability.
Methods: This paper presents a novel Y-shaped segmentation network with fast Fourier convolution and Mamba, termed F-Mamba-YNet.