AIMC Topic: Ligands

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AdptDilatedGCN: Protein-ligand binding affinity prediction based on multi-scale interaction fusion mechanism and dilated GCN.

International journal of biological macromolecules Apr 30, 2025
Predicting protein-ligand binding affinity is crucial for drug discovery. However, existing prediction methods often make insufficient use of the features of proteins and ligands, lack interactions between different information, and have difficulty i...
Deep Learning Protein Binding Computational Biology Proteins Ligands
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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....
Protein Binding Ligands Humans Deep Learning Prealbumin Binding Sites
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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 Drug Discovery Models, Molecular RNA Ligands Humans Artificial Intelligence
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Identification of potential riboswitch elements in Homo sapiens mRNA 5'UTR sequences using positive-unlabeled machine learning.

PloS one Apr 24, 2025
Riboswitches are a class of noncoding RNA structures that interact with target ligands to cause a conformational change that can then execute some regulatory purpose within the cell. Riboswitches are ubiquitous and well characterized in bacteria and ...
Base Sequence Nucleic Acid Conformation RNA, Messenger Riboswitch Humans 5' Untranslated Regions Ligands Machine Learning
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Encoding and decoding selectivity and promiscuity in the human chemokine-GPCR interaction network.

Cell Apr 23, 2025
In humans, selective and promiscuous interactions between 46 secreted chemokine ligands and 23 cell surface chemokine receptors of the G-protein-coupled receptor (GPCR) family form a complex network to coordinate cell migration. While chemokines and ...
Protein Binding Receptors, G-Protein-Coupled Humans Ligands Chemokines Receptors, Chemokine Models, Molecular Amino Acid Sequence
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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 Binding Sites Small Molecule Libraries Models, Molecular RNA Deep Learning Computational Biology
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DrugGen enhances drug discovery with large language models and reinforcement learning.

Scientific reports Apr 18, 2025
Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials. Deep learning advancements, particularly generative models, offer potential solutions...
Humans Algorithms Large Language Models Drug Design Deep Learning Drug Discovery Ligands
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Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction.

Journal of chemical information and modeling Apr 16, 2025
Artificial intelligence (AI) is revolutionizing drug discovery with unprecedented speed and efficiency. In computer-aided drug design, structure-based and ligand-based methodologies are the main driving forces for innovation. In cases where no experi...
Humans Bayes Theorem Machine Learning Ligands Drug Discovery
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QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Journal of chemical information and modeling Apr 8, 2025
Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand force fields continue to impact prediction accuracy. In this work, we ...
Proteins Molecular Dynamics Simulation Ligands Neural Networks, Computer Thermodynamics Quantum Theory Protein Binding
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Edge-enhanced interaction graph network for protein-ligand binding affinity prediction.

PloS one Apr 8, 2025
Protein-ligand interactions are crucial in drug discovery. Accurately predicting protein-ligand binding affinity is essential for screening potential drugs. Graph neural networks have proven highly effective in modeling spatial relationships and thre...
Drug Discovery Protein Binding Neural Networks, Computer Algorithms Proteins Ligands
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