AIMC Topic: Protein Binding

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OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

Frontiers in immunology Feb 28, 2025
The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune system are well established. This study aims to develop a novel machine learning framework for predicting antigen peptide presentation by MHC Class I and I...
Histocompatibility Antigens Class II Cancer Vaccines Antigen Presentation Vaccine Development Antigens, Neoplasm Female Histocompatibility Antigens Class I Humans Peptides Machine Learning Endometrial Neoplasms Protein Binding
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Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.

Cell genomics Feb 27, 2025
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how co...
Transcription Factors Binding Sites Chromatin Nucleosomes SOX9 Transcription Factor Deep Learning Protein Binding Mice Humans Animals
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Recent advances in AI-driven protein-ligand interaction predictions.

Current opinion in structural biology Feb 24, 2025
Structure-based drug discovery is a fundamental approach in modern drug development, leveraging computational models to predict protein-ligand interactions. AI-driven methodologies are significantly improving key aspects of the field, including ligan...
Humans Proteins Artificial Intelligence Ligands Molecular Docking Simulation Binding Sites Drug Discovery Deep Learning Protein Binding
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Natural Language Processing Methods for the Study of Protein-Ligand Interactions.

Journal of chemical information and modeling Feb 24, 2025
Natural Language Processing (NLP) has revolutionized the way computers are used to study and interact with human languages and is increasingly influential in the study of protein and ligand binding, which is critical for drug discovery and developmen...
Natural Language Processing Drug Discovery Ligands Protein Binding Humans Proteins Machine Learning
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Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.

Journal of chemical information and modeling Feb 21, 2025
Predicting interactions between proteins is fundamental for understanding the mechanisms underlying cellular processes, since protein-protein complexes are crucial in physiological conditions but also in many diseases, for example by seeding aggregat...
Surface Properties Binding Sites Proteins Hydrophobic and Hydrophilic Interactions Neural Networks, Computer Molecular Docking Simulation ROC Curve Protein Binding
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Estimating Absolute Protein-Protein Binding Free Energies by a Super Learner Model.

Journal of chemical information and modeling Feb 20, 2025
Protein-protein binding is central to most biochemical processes of all living beings. Its importance underlies mechanisms ranging from cell interactions to metabolic control, but also to biotechnology, such as the development of therapeutic monoclo...
Protein Binding Proteins Thermodynamics Machine Learning
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T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment.

Journal of chemical information and modeling Feb 18, 2025
There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to accurately predict the binding affinity of small molecules to a protein target in silico enables the...
Deep Learning Protein Binding Proteins SARS-CoV-2 Drug Discovery Ligands ErbB Receptors Uncertainty Humans Neural Networks, Computer
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CL-GNN: Contrastive Learning and Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling Feb 6, 2025
In the realm of drug discovery and design, the accurate prediction of protein-ligand binding affinity is of paramount importance as it underpins the functional interactions within biological systems. This study introduces a novel self-supervised lear...
Neural Networks, Computer Machine Learning Drug Discovery Protein Binding Ligands Proteins Graph Neural Networks
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Protein ligand structure prediction: From empirical to deep learning approaches.

Current opinion in structural biology Feb 5, 2025
Protein-ligand structure prediction methods, aiming to predict the three-dimensional complex structure and binding energy of a compound and target protein, are essential in many structure-based drug discovery pipelines, including virtual screening an...
Drug Discovery Deep Learning Protein Binding Models, Molecular Computational Biology Ligands Proteins Protein Conformation
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ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.) Jan 30, 2025
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...
Humans Neural Networks, Computer Machine Learning Algorithms RNA-Binding Proteins Protein Binding RNA Computational Biology Graph Neural Networks
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