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Protein Binding

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Structure-Aware Graph Attention Diffusion Network for Protein-Ligand Binding Affinity Prediction.

IEEE transactions on neural networks and learning systems Dec 2, 2024
Accurate prediction of protein-ligand binding affinities can significantly advance the development of drug discovery. Several graph neural network (GNN)-based methods learn representations of protein-ligand complexes via modeling intermolecule intera...
Humans Neural Networks, Computer Proteins Databases, Protein Ligands Algorithms Drug Discovery Protein Binding
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Rational design of potent phosphopeptide binders to endocrine Snk PBD domain by integrating machine learning optimization, molecular dynamics simulation, binding energetics rescoring, and in vitro affinity assay.

European biophysics journal : EBJ Nov 29, 2024
Human Snk is an evolutionarily conserved serine/threonine kinase essential for the maintenance of endocrine stability. The protein consists of a N-terminal catalytic domain and a C-terminal polo-box domain (PBD) that determines subcellular localizati...
Phosphopeptides Molecular Dynamics Simulation Humans Protein Binding Amino Acid Sequence Machine Learning Thermodynamics Protein Serine-Threonine Kinases Drug Design Protein Domains
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SurfDock is a surface-informed diffusion generative model for reliable and accurate protein-ligand complex prediction.

Nature methods Nov 27, 2024
Accurately predicting protein-ligand interactions is crucial for understanding cellular processes. We introduce SurfDock, a deep-learning method that addresses this challenge by integrating protein sequence, three-dimensional structural graphs and su...
Deep Learning Protein Binding Proteins Ligands Protein Conformation Software Algorithms Molecular Docking Simulation Humans
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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...
Molecular Docking Simulation Proteins Deep Learning Databases, Protein Protein Binding Ligands
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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...
Drug Discovery Deep Learning Protein Binding Proteins Ligands Small Molecule Libraries
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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...
Databases, Protein Models, Molecular Protein Conformation Protein Binding Proteins Protein Interaction Mapping Neural Networks, Computer
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Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Ligands Acetylcholinesterase Cholinesterase Inhibitors Databases, Chemical Binding Sites Molecular Docking Simulation Humans Protein Binding Machine Learning Molecular Dynamics Simulation
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Improving drug-target interaction prediction through dual-modality fusion with InteractNet.

Journal of bioinformatics and computational biology Nov 11, 2024
In the drug discovery process, accurate prediction of drug-target interactions is crucial to accelerate the development of new drugs. However, existing methods still face many challenges in dealing with complex biomolecular interactions. To this end,...
Deep Learning Machine Learning Protein Binding Proteins Algorithms Humans Computational Biology Neural Networks, Computer Ligands Drug Discovery Databases, Protein Pharmaceutical Preparations Binding Sites
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LGS-PPIS: A Local-Global Structural Information Aggregation Framework for Predicting Protein-Protein Interaction Sites.

Proteins Nov 9, 2024
Exploring protein-protein interaction sites (PPIS) is of significance to elucidating the intrinsic mechanisms of diverse biological processes. On this basis, recent studies have applied deep learning-based technologies to overcome the high cost of we...
Deep Learning Protein Binding Computational Biology Humans Algorithms Binding Sites Proteins Protein Interaction Mapping Databases, Protein Protein Interaction Domains and Motifs
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Small molecule inhibitors of IL-1R1/IL-1β interaction identified via transfer machine learning QSAR modelling.

International journal of biological macromolecules Nov 7, 2024
The human interleukin-1 receptor I (IL-1R1) is a cytokine receptor recognized by interleukin 1β (IL-1β), among other cytokines. Over activation of IL-1R1 has been implicated in various inflammatory conditions. This research aims to identify small-mol...
Receptors, Interleukin-1 Type I Quantitative Structure-Activity Relationship Small Molecule Libraries Humans Protein Binding Machine Learning Interleukin-1beta Molecular Docking Simulation Molecular Dynamics Simulation
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