AIMC Topic: Proteins

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Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.

Journal of chemical information and modeling Nov 22, 2024
The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity between liga...
Deep Learning Protein Binding Databases, Protein Ligands Proteins Molecular Docking Simulation
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MERIT: Accurate Prediction of Multi Ligand-binding Residues with Hybrid Deep Transformer Network, Evolutionary Couplings and Transfer Learning.

Journal of molecular biology Nov 20, 2024
Multi-ligand binding residues (MLBRs) are amino acids in protein sequences that interact with multiple different ligands that include proteins, peptides, nucleic acids, and a variety of small molecules. MLBRs are implicated in a number of cellular fu...
Deep Learning Protein Binding Machine Learning Software Databases, Protein Humans Ligands Binding Sites Neural Networks, Computer Computational Biology Proteins
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PredIDR: Accurate prediction of protein intrinsic disorder regions using deep convolutional neural network.

International journal of biological macromolecules Nov 19, 2024
The involvement of protein intrinsic disorder in essential biological processes, it is well known in structural biology. However, experimental methods for detecting intrinsic structural disorder and directly measuring highly dynamic behavior of prote...
Proteins Databases, Protein Algorithms Intrinsically Disordered Proteins Computational Biology Neural Networks, Computer Software
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CPIScore: A Deep Learning Approach for Rapid Scoring and Interpretation of Protein-Ligand Binding Interactions.

Journal of chemical information and modeling Nov 19, 2024
Protein-ligand binding affinity prediction is a crucial and challenging task in the field of drug discovery. However, traditional simulation-based computational approaches are often prohibitively time-consuming, limiting their practical utility. In t...
Ligands Small Molecule Libraries Drug Discovery Protein Binding Proteins Deep Learning
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DeepKlapred: A deep learning framework for identifying protein lysine lactylation sites via multi-view feature fusion.

International journal of biological macromolecules Nov 19, 2024
Lysine lactylation (Kla) is a post-translational modification (PTM) that holds significant importance in the regulation of various biological processes. While traditional experimental methods are highly accurate for identifying Kla sites, they are bo...
Lysine Proteins Amino Acid Sequence Computational Biology Protein Processing, Post-Translational Algorithms Deep Learning
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ProAffinity-GNN: A Novel Approach to Structure-Based Protein-Protein Binding Affinity Prediction via a Curated Data Set and Graph Neural Networks.

Journal of chemical information and modeling Nov 18, 2024
Protein-protein interactions (PPIs) are crucial for understanding biological processes and disease mechanisms, contributing significantly to advances in protein engineering and drug discovery. The accurate determination of binding affinities, essenti...
Neural Networks, Computer Protein Binding Models, Molecular Protein Conformation Protein Interaction Mapping Proteins Databases, Protein
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DMHGNN: Double multi-view heterogeneous graph neural network framework for drug-target interaction prediction.

Artificial intelligence in medicine Nov 17, 2024
Accurate identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared with traditional experimental methods that are labor-intensive and time-consuming, computational methods for drug-target interactions predicti...
Algorithms Drug Interactions Proteins Drug Discovery Pharmaceutical Preparations Humans Computational Biology Neural Networks, Computer
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Predicting Protein-Ligand Binding Affinity Using Fusion Model of Spatial-Temporal Graph Neural Network and 3D Structure-Based Complex Graph.

Interdisciplinary sciences, computational life sciences Nov 14, 2024
The investigation of molecular interactions between ligands and their target molecules is becoming more significant as protein structure data continues to develop. In this study, we introduce PLA-STGCNnet, a deep fusion spatial-temporal graph neural ...
Ligands Protein Binding Protein Conformation Proteins Neural Networks, Computer Graph Neural Networks Algorithms
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deepBBQ: A Deep Learning Approach to the Protein Backbone Reconstruction.

Biomolecules Nov 14, 2024
Coarse-grained models have provided researchers with greatly improved computational efficiency in modeling structures and dynamics of biomacromolecules, but, to be practically useful, they need fast and accurate conversion methods back to the all-ato...
Proteins Models, Molecular Deep Learning Computational Biology Neural Networks, Computer Software
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An experimental analysis of graph representation learning for Gene Ontology based protein function prediction.

PeerJ Nov 14, 2024
Understanding protein function is crucial for deciphering biological systems and facilitating various biomedical applications. Computational methods for predicting Gene Ontology functions of proteins emerged in the 2000s to bridge the gap between the...
Computational Biology Algorithms Proteins Humans Gene Ontology Protein Interaction Maps Machine Learning
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