AIMC Topic: Proteins

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SSGraphCPI: A Novel Model for Predicting Compound-Protein Interactions Based on Deep Learning.

International journal of molecular sciences Mar 29, 2022
Identifying compound-protein (drug-target, DTI) interactions (CPI) accurately is a key step in drug discovery. Including virtual screening and drug reuse, it can significantly reduce the time it takes to identify drug candidates and provide patients ...
Humans Neural Networks, Computer Deep Learning Proteins Drug Delivery Systems Drug Discovery
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Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging Mar 29, 2022
Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to cla...
Artificial Intelligence Drug Discovery Proteins Drug Repositioning
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PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods.

Computers in biology and medicine Mar 28, 2022
Bioinformatic annotation of protein function is essential but extremely sophisticated, which asks for extensive efforts to develop effective prediction method. However, the existing methods tend to amplify the representativeness of the families with ...
Proteins Molecular Sequence Annotation Deep Learning Computational Biology Neural Networks, Computer
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Fast protein structure comparison through effective representation learning with contrastive graph neural networks.

PLoS computational biology Mar 24, 2022
Protein structure alignment algorithms are often time-consuming, resulting in challenges for large-scale protein structure similarity-based retrieval. There is an urgent need for more efficient structure comparison approaches as the number of protein...
Algorithms Learning Proteins Neural Networks, Computer Software
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Affinity prediction using deep learning based on SMILES input for D3R grand challenge 4.

Journal of computer-aided molecular design Mar 22, 2022
Modern molecular docking comprises the prediction of pose and affinity. Prediction of docking poses is required for affinity prediction when three-dimensional coordinates of the ligand have not been provided. However, a large number of feature engine...
Binding Sites Thermodynamics Protein Conformation Protein Binding Proteins Databases, Protein Ligands Drug Design Deep Learning Molecular Docking Simulation Humans
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BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction.

Journal of molecular biology Mar 21, 2022
Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating ...
Internet Use Proteins Datasets as Topic Binding Sites Protein Interaction Mapping Software Protein Binding Machine Learning
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Hierarchical representation for PPI sites prediction.

BMC bioinformatics Mar 20, 2022
BACKGROUND: Protein-protein interactions have pivotal roles in life processes, and aberrant interactions are associated with various disorders. Interaction site identification is key for understanding disease mechanisms and design new drugs. Effectiv...
Amino Acids Machine Learning Proteins
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PharmRF: A machine-learning scoring function to identify the best protein-ligand complexes for structure-based pharmacophore screening with high enrichments.

Journal of computational chemistry Mar 18, 2022
Structure-based pharmacophore models are often developed by selecting a single protein-ligand complex with good resolution and better binding affinity data which prevents the analysis of other structures having a similar potential to act as better te...
Ligands Protein Binding Proteins Machine Learning Molecular Docking Simulation
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Predicting residues involved in anti-DNA autoantibodies with limited neural networks.

Medical & biological engineering & computing Mar 18, 2022
Computer-aided rational vaccine design (RVD) and synthetic pharmacology are rapidly developing fields that leverage existing datasets for developing compounds of interest. Computational proteomics utilizes algorithms and models to probe proteins for ...
Neural Networks, Computer Autoantibodies Binding Sites Proteins DNA Algorithms
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Protein p Prediction by Tree-Based Machine Learning.

Journal of chemical theory and computation Mar 15, 2022
Protonation states of ionizable protein residues modulate many essential biological processes. For correct modeling and understanding of these processes, it is crucial to accurately determine their p values. Here, we present four tree-based machine l...
Humans Proteins Kinetics Machine Learning Algorithms
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