AIMC Topic: Protein Binding

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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,...
Ligands Binding Sites Humans Neural Networks, Computer Machine Learning Deep Learning Algorithms Protein Binding Drug Discovery Computational Biology Proteins Databases, Protein Pharmaceutical Preparations
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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...
Binding Sites Protein Interaction Mapping Protein Interaction Domains and Motifs Computational Biology Deep Learning Humans Proteins Protein Binding Algorithms Databases, Protein
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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...
Humans Machine Learning Molecular Docking Simulation Quantitative Structure-Activity Relationship Small Molecule Libraries Receptors, Interleukin-1 Type I Protein Binding Interleukin-1beta Molecular Dynamics Simulation
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Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction.

Nature communications Nov 7, 2024
Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While...
Models, Molecular Protein Interaction Mapping Neural Networks, Computer Machine Learning Algorithms Protein Binding Computational Biology Proteins
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An Integrated TCN-CrossMHA Model for Predicting circRNA-RBP Binding Sites.

Interdisciplinary sciences, computational life sciences Nov 6, 2024
Circular RNA (circRNA) has the capacity to bind with RNA binding protein (RBP), thereby exerting a substantial impact on diseases. Predicting binding sites aids in comprehending the interaction mechanism, thereby offering insights for disease treatme...
Protein Binding Computational Biology RNA-Binding Proteins Binding Sites RNA, Circular Humans Neural Networks, Computer Algorithms
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Interaction-Based Inductive Bias in Graph Neural Networks: Enhancing Protein-Ligand Binding Affinity Predictions From 3D Structures.

IEEE transactions on pattern analysis and machine intelligence Nov 6, 2024
Inductive bias in machine learning (ML) is the set of assumptions describing how a model makes predictions. Different ML-based methods for protein-ligand binding affinity (PLA) prediction have different inductive biases, leading to different levels o...
Humans Neural Networks, Computer Machine Learning Ligands Protein Conformation SARS-CoV-2 Protein Binding Proteins COVID-19 Algorithms
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GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning.

Structure (London, England : 1993) Nov 1, 2024
The identification of protein binding residues is essential for understanding their functions in vivo. However, it remains a computational challenge to accurately identify binding sites due to the lack of known residue binding patterns. Local residue...
Proteins DNA Models, Molecular Protein Binding Computational Biology RNA Ligands Binding Sites Deep Learning
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The state-of-the-art machine learning model for plasma protein binding prediction: Computational modeling with OCHEM and experimental validation.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences Oct 28, 2024
Plasma protein binding (PPB) is closely related to pharmacokinetics, pharmacodynamics and drug toxicity. Existing models for predicting PPB often suffer from low prediction accuracy and poor interpretability, especially for high PPB compounds, and ar...
Humans Models, Biological Machine Learning Protein Binding Computer Simulation Blood Proteins Pharmaceutical Preparations
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GraphPBSP: Protein binding site prediction based on Graph Attention Network and pre-trained model ProstT5.

International journal of biological macromolecules Oct 28, 2024
Protein-protein/peptide interactions play crucial roles in various biological processes. Exploring their interactions attracts wide attention. However, accurately predicting their binding sites remains a challenging task. Here, we develop an effectiv...
Proteins Neural Networks, Computer Binding Sites Algorithms Protein Binding Computational Biology
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ANTIPASTI: Interpretable prediction of antibody binding affinity exploiting normal modes and deep learning.

Structure (London, England : 1993) Oct 25, 2024
The high binding affinity of antibodies toward their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a convolutional neural network mod...
Neural Networks, Computer Deep Learning Protein Binding Humans Antigen-Antibody Complex Antibody Affinity Binding Sites, Antibody Models, Molecular Antibodies Antigens
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