AIMC Topic: Receptors, G-Protein-Coupled

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Multi-source transfer learning with Graph Neural Network for excellent modelling the bioactivities of ligands targeting orphan G protein-coupled receptors.

Mathematical biosciences and engineering : MBE Nov 25, 2022
G protein-coupled receptors (GPCRs) have been the targets for more than 40% of the currently approved drugs. Although neural networks can effectively improve the accuracy of prediction with the biological activity, the result is undesirable in the li...
Signal Transduction Receptors, G-Protein-Coupled Ligands Neural Networks, Computer Machine Learning
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Computational model of the full-length TSH receptor.

eLife Oct 28, 2022
(GPCR)The receptor for TSH receptor (TSHR), a G protein coupled receptor (GPCR), is of particular interest as the primary antigen in autoimmune hyperthyroidism (Graves' disease) caused by stimulating TSHR antibodies. To date, only one domain of the e...
Ligands Leucine Receptors, Thyrotropin Artificial Intelligence Thyrotropin Receptors, G-Protein-Coupled Autoantibodies
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A machine learning model for classifying G-protein-coupled receptors as agonists or antagonists.

BMC bioinformatics Aug 18, 2022
BACKGROUND: G-protein coupled receptors (GPCRs) sense and transmit extracellular signals into the intracellular machinery by regulating G proteins. GPCR malfunctions are associated with a variety of signaling-related diseases, including cancer and di...
Receptors, G-Protein-Coupled Area Under Curve Ligands Machine Learning
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An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.

Journal of chemical information and modeling Mar 8, 2022
Molecular dynamics (MD) simulations have made great contribution to revealing structural and functional mechanisms for many biomolecular systems. However, how to identify functional states and important residues from vast conformation space generated...
Receptors, G-Protein-Coupled Molecular Dynamics Simulation Neural Networks, Computer Software
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Development and validation of multiple machine learning algorithms for the classification of G-protein-coupled receptors using molecular evolution model-based feature extraction strategy.

Amino acids Sep 25, 2021
Machine learning is one of the most potential ways to realize the function prediction of the incremental large-scale G-protein-coupled receptors (GPCR). Prior research reveals that the key to determining the overall classification accuracy of GPCR is...
Multigene Family Sequence Alignment Machine Learning Algorithms Receptors, G-Protein-Coupled Amino Acid Sequence Evolution, Molecular
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Prediction of Drug-Target Interactions by Combining Dual-Tree Complex Wavelet Transform with Ensemble Learning Method.

Molecules (Basel, Switzerland) Sep 3, 2021
Identification of drug-target interactions (DTIs) is vital for drug discovery. However, traditional biological approaches have some unavoidable shortcomings, such as being time consuming and expensive. Therefore, there is an urgent need to develop no...
Drug Development Support Vector Machine Databases, Protein Receptors, Cytoplasmic and Nuclear Enzymes Ion Channels Receptors, G-Protein-Coupled Wavelet Analysis
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Accurate prediction of protein structures and interactions using a three-track neural network.

Science (New York, N.Y.) Jul 15, 2021
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track ...
Protein Subunits Sphingosine N-Acyltransferase Protein Folding Multiprotein Complexes Computer Simulation Deep Learning Neural Networks, Computer Amino Acid Sequence ADAM Proteins Databases, Protein Protein Conformation Membrane Proteins Crystallography, X-Ray Receptors, G-Protein-Coupled Cryoelectron Microscopy Models, Molecular Proteins
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Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol.

Molecules (Basel, Switzerland) May 20, 2021
Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins,...
Humans Molecular Dynamics Simulation Machine Learning Ligands Receptors, G-Protein-Coupled Protein Conformation
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An Integrated Approach toward NanoBRET Tracers for Analysis of GPCR Ligand Engagement.

Molecules (Basel, Switzerland) May 12, 2021
Gaining insight into the pharmacology of ligand engagement with G-protein coupled receptors (GPCRs) under biologically relevant conditions is vital to both drug discovery and basic research. NanoLuc-based bioluminescence resonance energy transfer (Na...
Binding, Competitive Protein Binding Bioluminescence Resonance Energy Transfer Techniques Receptors, G-Protein-Coupled HEK293 Cells Molecular Docking Simulation Luminescent Agents Transfection Humans Luciferases Drug Discovery Ligands Machine Learning
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Artificial Intelligence Approaches to Assessing Primary Cilia.

Journal of visualized experiments : JoVE May 1, 2021
Cilia are microtubule based cellular appendages that function as signaling centers for a diversity of signaling pathways in many mammalian cell types. Cilia length is highly conserved, tightly regulated, and varies between different cell types and ti...
Microtubules Cilia Signal Transduction Artificial Intelligence Receptors, G-Protein-Coupled Animals
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