AIMC Topic: Protein Interaction Mapping

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Using AlphaFold Multimer to discover interkingdom protein-protein interactions.

The Plant journal : for cell and molecular biology Aug 17, 2024
Structural prediction by artificial intelligence can be powerful new instruments to discover novel protein-protein interactions, but the community still grapples with the implementation, opportunities and limitations. Here, we discuss and re-analyse ...
Plant Proteins Protein Interaction Mapping Sequence Alignment Artificial Intelligence
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DGCPPISP: a PPI site prediction model based on dynamic graph convolutional network and two-stage transfer learning.

BMC bioinformatics Jul 31, 2024
BACKGROUND: Proteins play a pivotal role in the diverse array of biological processes, making the precise prediction of protein-protein interaction (PPI) sites critical to numerous disciplines including biology, medicine and pharmacy. While deep lear...
Computational Biology Proteins Protein Interaction Mapping Databases, Protein Machine Learning Neural Networks, Computer Deep Learning
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A Hierarchical Graph Neural Network Framework for Predicting Protein-Protein Interaction Modulators With Functional Group Information and Hypergraph Structure.

IEEE journal of biomedical and health informatics Jul 2, 2024
Accurate prediction of small molecule modulators targeting protein-protein interactions (PPIMs) remains a significant challenge in drug discovery. Existing machine learning-based models rely on manual feature engineering, which is tedious and task-sp...
Deep Learning Protein Interaction Maps Computational Biology Algorithms Drug Discovery Protein Interaction Mapping Proteins Neural Networks, Computer
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Protein-Protein Interaction Prediction via Structure-Based Deep Learning.

Proteins Jun 23, 2024
Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with vario...
Protein Interaction Mapping Protein Interaction Maps Computational Biology Databases, Protein Amino Acid Sequence Humans Algorithms Proteins Neural Networks, Computer Animals Deep Learning
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DP-site: A dual deep learning-based method for protein-peptide interaction site prediction.

Methods (San Diego, Calif.) Jun 12, 2024
BACKGROUND: Protein-peptide interaction prediction is an important topic for several applications including various biological processes, understanding drug discovery, protein function abnormal cellular behaviors, and treating diseases. Over the year...
Neural Networks, Computer Software Peptides Humans Computational Biology Proteins Databases, Protein Deep Learning Protein Binding Binding Sites Protein Interaction Mapping
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DSSGNN-PPI: A Protein-Protein Interactions prediction model based on Double Structure and Sequence graph neural networks.

Computers in biology and medicine May 29, 2024
The process of experimentally confirming complex interaction networks among proteins is time-consuming and laborious. This study aims to address Protein-Protein Interactions (PPIs) prediction based on graph neural networks (GNN). A novel multilevel p...
Proteins Databases, Protein Protein Interaction Mapping Protein Interaction Maps Humans Computational Biology Neural Networks, Computer
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Protein-Protein Interfaces: A Graph Neural Network Approach.

International journal of molecular sciences May 28, 2024
Protein-protein interactions (PPIs) are fundamental processes governing cellular functions, crucial for understanding biological systems at the molecular level. Compared to experimental methods for PPI prediction and site identification, computationa...
Computational Biology Deep Learning Neural Networks, Computer Protein Interaction Mapping Databases, Protein Proteins Protein Interaction Maps Algorithms Protein Binding
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Prediction of Protein-Protein Interactions Based on Integrating Deep Learning and Feature Fusion.

International journal of molecular sciences May 27, 2024
Understanding protein-protein interactions (PPIs) helps to identify protein functions and develop other important applications such as drug preparation and protein-disease relationship identification. Deep-learning-based approaches are being intensel...
Protein Interaction Maps Mice Computational Biology Animals Deep Learning Protein Interaction Mapping Databases, Protein Caenorhabditis elegans Humans
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ProBAN: Neural network algorithm for predicting binding affinity in protein-protein complexes.

Proteins May 9, 2024
Determining binding affinities in protein-protein and protein-peptide complexes is a challenging task that directly impacts the development of peptide and protein pharmaceuticals. Although several models have been proposed to predict the value of the...
Proteins Databases, Protein Computational Biology Thermodynamics Neural Networks, Computer Algorithms Protein Interaction Mapping Binding Sites Protein Binding
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GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs.

BMC genomics May 9, 2024
Most proteins exert their functions by interacting with other proteins, making the identification of protein-protein interactions (PPI) crucial for understanding biological activities, pathological mechanisms, and clinical therapies. Developing effec...
Humans Neural Networks, Computer Protein Interaction Maps Computational Biology Algorithms Proteins Protein Interaction Mapping
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