AIMC Topic: Proteins

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MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.

International journal of biological macromolecules Jan 21, 2025
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental metho...
Protein Interaction Mapping Neural Networks, Computer Computational Biology Algorithms Graph Neural Networks Protein Conformation Proteins Protein Binding Binding Sites Models, Molecular
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Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling Jan 21, 2025
With the resolution revolution of cryo-electron microscopy (cryo-EM) and the rapid development of image processing technology, cryo-EM has become an indispensable experimental method for determining the three-dimensional structures of biological macr...
Protein Structure, Secondary Nucleic Acids Cryoelectron Microscopy Proteins Models, Molecular Deep Learning
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MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction.

Journal of chemical information and modeling Jan 20, 2025
Predicting drug-target binding affinity (DTA) is a crucial task in drug discovery research. Recent studies have demonstrated that pocket features and interactions between targets and drugs significantly improve the understanding of DTA. However, chal...
Humans Deep Learning Protein Binding Drug Discovery Binding Sites Proteins Pharmaceutical Preparations
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PPILS: Protein-protein interaction prediction with language of biological coding.

Computers in biology and medicine Jan 19, 2025
Protein-protein interactions within a cell are essential for various fundamental biological processes. Computational techniques have arisen in bioinformatics due to the challenging and resource-intensive nature of experimental protein pair interactio...
Protein Interaction Maps Computational Biology Databases, Protein Proteins Humans Protein Interaction Mapping Machine Learning
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Structure-Based Approaches for Protein-Protein Interaction Prediction Using Machine Learning and Deep Learning.

Biomolecules Jan 17, 2025
Protein-Protein Interaction (PPI) prediction plays a pivotal role in understanding cellular processes and uncovering molecular mechanisms underlying health and disease. Structure-based PPI prediction has emerged as a robust alternative to sequence-ba...
Proteomics Deep Learning Humans Proteins Protein Interaction Mapping Machine Learning Computational Biology Protein Conformation
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Active Learning to Select the Most Suitable Reagents and One-Step Organic Chemistry Reactions for Prioritizing Target-Specific Hits from Ultralarge Chemical Spaces.

Journal of chemical information and modeling Jan 16, 2025
Designing chemically novel and synthesizable ligands from the largest possible chemical space is a major issue in modern drug discovery to identify early hits that are easily amenable to medicinal chemistry optimization. Starting from the sole three-...
Ligands Indicators and Reagents Drug Discovery Proteins Machine Learning Molecular Docking Simulation
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Targeting protein-ligand neosurfaces with a generalizable deep learning tool.

Nature Jan 15, 2025
Molecular recognition events between proteins drive biological processes in living systems. However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules. Despite recent advanc...
Models, Molecular Ligands Proto-Oncogene Proteins c-bcl-2 Protein Binding Proteins Bridged Bicyclo Compounds, Heterocyclic Drug Design Deep Learning Humans
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Integrating CNN and Bi-LSTM for protein succinylation sites prediction based on Natural Language Processing technique.

Computers in biology and medicine Jan 10, 2025
Protein succinylation, a post-translational modification wherein a succinyl group (-CO-CH₂-CH₂-CO-) attaches to lysine residues, plays a critical regulatory role in cellular processes. Dysregulated succinylation has been implicated in the onset and p...
Neural Networks, Computer Computational Biology Protein Processing, Post-Translational Humans Natural Language Processing Succinic Acid Proteins Databases, Protein
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Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models.

Journal of chemical information and modeling Jan 9, 2025
The accurate identification of protein-nucleotide binding residues is crucial for protein function annotation and drug discovery. Numerous computational methods have been proposed to predict these binding residues, achieving remarkable performance. H...
Binding Sites Deep Learning Protein Binding Databases, Protein Nucleotides Proteins
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CovCysPredictor: Predicting Selective Covalently Modifiable Cysteines Using Protein Structure and Interpretable Machine Learning.

Journal of chemical information and modeling Jan 8, 2025
Targeted covalent inhibition is a powerful therapeutic modality in the drug discoverer's toolbox. Recent advances in covalent drug discovery, in particular, targeting cysteines, have led to significant breakthroughs for traditionally challenging targ...
Machine Learning Drug Discovery Proteins Humans Ligands Databases, Protein Models, Molecular Protein Conformation Cysteine
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