AIMC Topic: Binding Sites

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Uncertainty Quantification and Temperature Scaling Calibration for Protein-RNA Binding Site Prediction.

Journal of chemical information and modeling Jun 2, 2025
The black-box nature of deep learning has increasingly drawn attention to the reliability and uncertainty of predictive models. Currently, several uncertainty quantification (UQ) methods have been proposed and successfully applied in the fields of mo...
Neural Networks, Computer Temperature Calibration Binding Sites Uncertainty RNA-Binding Proteins RNA Protein Binding
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Molecular insights into the unique activation and allosteric modulation mechanisms of the human mas-related G-protein-coupled receptor X1.

International journal of biological macromolecules May 30, 2025
MRGPRX1 plays dual roles in mediating nociception and pruritus, making it a promising target for alleviating itch and inhibiting pain. However, the mechanisms underlying MRGPRX1 activation and allosteric modulation remain poorly understood, posing si...
Humans Protein Binding Allosteric Regulation Molecular Dynamics Simulation Receptors, Neuropeptide Protein Conformation Receptors, G-Protein-Coupled Binding Sites
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CrypToth: Cryptic Pocket Detection through Mixed-Solvent Molecular Dynamics Simulations-Based Topological Data Analysis.

Journal of chemical information and modeling May 22, 2025
Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still di...
Protein Conformation Binding Sites Molecular Dynamics Simulation Ligands Solvents Proteins
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Predictive biophysical neural network modeling of a compendium of in vivo transcription factor DNA binding profiles for Escherichia coli.

Nature communications May 7, 2025
The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs us...
Transcription Factors Neural Networks, Computer Escherichia coli Escherichia coli Proteins Binding Sites Chromatin Immunoprecipitation Sequencing Protein Binding DNA, Bacterial
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A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites.

PloS one May 7, 2025
BACKGROUND: Predicting protein-DNA binding sites in vivo is a challenging but urgent task in many fields such as drug design and development. Most promoters contain many transcription factor (TF) binding sites, yet only a few have been identified thr...
Computational Biology Algorithms Humans Binding Sites Deep Learning Neural Networks, Computer Transcription Factors Promoter Regions, Genetic Protein Binding
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Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.

Genome research May 2, 2025
Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F crosses with extensive genetic diversity...
Drosophila melanogaster Binding Sites Drosophila Genetic Variation Embryonic Development Drosophila Proteins Transcription Factors Alleles Animals Deep Learning Protein Binding
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Dual-Site Targeting by Peptide Inhibitors of the N-Terminal Domain of Hsp90: Mechanism and Design.

Journal of chemical information and modeling May 1, 2025
Heat shock protein 90 (Hsp90) is a pivotal molecular chaperone crucial in the maturation of client proteins, positioning it as a significant target for cancer therapy. However, the design of effective Hsp90 inhibitors presents substantial challenges ...
Protein Binding Protein Domains Molecular Dynamics Simulation Molecular Docking Simulation Drug Design HSP90 Heat-Shock Proteins Adenosine Triphosphate Binding Sites Machine Learning Peptides Humans
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Enhancing Transthyretin Binding Affinity Prediction with a Consensus Model: Insights from the Tox24 Challenge.

Chemical research in toxicology Apr 26, 2025
Transthyretin (TTR) plays a vital role in thyroid hormone transport and homeostasis in both the blood and target tissues. Interactions between exogenous compounds and TTR can disrupt the function of the endocrine system, potentially causing toxicity....
Binding Sites Humans Deep Learning Ligands Prealbumin Protein Binding
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Artificial intelligence for RNA-ligand interaction prediction: advances and prospects.

Drug discovery today Apr 24, 2025
Accurate prediction of RNA-ligand interactions is vital for understanding biological processes and advancing RNA-targeted drug discovery. Given their complexity, artificial intelligence (AI) is revolutionizing the study of RNA-ligand interactions, of...
Binding Sites RNA Ligands Humans Drug Discovery Models, Molecular Artificial Intelligence
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The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

International journal of biological macromolecules Apr 21, 2025
Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and folding, and are essential for guiding drug design in the medical field. Accurately predicting the ...
Deep Learning Computational Biology Small Molecule Libraries Ligands Nucleic Acid Conformation Models, Molecular Binding Sites RNA
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