AIMC Topic: Binding Sites

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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 ...
Peptides Molecular Docking Simulation Drug Design Humans Machine Learning HSP90 Heat-Shock Proteins Protein Binding Protein Domains Adenosine Triphosphate Molecular Dynamics Simulation Binding Sites
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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....
Ligands Prealbumin Binding Sites Deep Learning Protein Binding Humans
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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 Artificial Intelligence Models, Molecular
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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 ...
Ligands Nucleic Acid Conformation Small Molecule Libraries Binding Sites Computational Biology Deep Learning Models, Molecular RNA
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TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data.

Nature communications Apr 16, 2025
It is challenging to identify regulatory transcriptional regulators (TRs), which control gene expression via regulatory elements and epigenomic signals, in context-specific studies on the onset and progression of diseases. The use of large-scale mult...
Chromatin Epigenomics Transcription Factors Computational Biology Binding Sites Regulatory Elements, Transcriptional Humans Gene Expression Regulation Deep Learning
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A comprehensive review of computational methods for Protein-DNA binding site prediction.

Analytical biochemistry Apr 8, 2025
Accurately identifying protein-DNA binding sites is essential for understanding the molecular mechanisms underlying biological processes, which in turn facilitates advancements in drug discovery and design. While biochemical experiments provide the m...
Humans Machine Learning DNA DNA-Binding Proteins Binding Sites Protein Binding Computational Biology Deep Learning
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Deep-ProBind: binding protein prediction with transformer-based deep learning model.

BMC bioinformatics Mar 22, 2025
Binding proteins play a crucial role in biological systems by selectively interacting with specific molecules, such as DNA, RNA, or peptides, to regulate various cellular processes. Their ability to recognize and bind target molecules with high speci...
Proteins Databases, Protein Sequence Analysis, Protein Binding Sites Deep Learning Neural Networks, Computer Protein Binding Algorithms Computational Biology
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RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning.

Nature communications Mar 21, 2025
RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. However, docking struggles to scale w...
Nucleic Acid Conformation Molecular Docking Simulation Deep Learning Binding Sites Riboswitch RNA
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TopEC: prediction of Enzyme Commission classes by 3D graph neural networks and localized 3D protein descriptor.

Nature communications Mar 20, 2025
Tools available for inferring enzyme function from general sequence, fold, or evolutionary information are generally successful. However, they can lead to misclassification if a deviation in local structural features influences the function. Here, we...
Graph Neural Networks Binding Sites Enzymes Algorithms Computational Biology Protein Conformation Neural Networks, Computer Software
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CacPred: a cascaded convolutional neural network for TF-DNA binding prediction.

BMC genomics Mar 18, 2025
BACKGROUND: Transcription factors (TFs) regulate the genes' expression by binding to DNA sequences. Aligned TFBSs of the same TF are seen as cis-regulatory motifs, and substantial computational efforts have been invested to find motifs. In recent yea...
Algorithms Convolutional Neural Networks Neural Networks, Computer Computational Biology Software Chromatin Immunoprecipitation Sequencing Transcription Factors Protein Binding DNA Binding Sites
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