AIMC Topic: Receptors, G-Protein-Coupled

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Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution.

Biochemical and biophysical research communications Mar 9, 2021
Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diabetes mellitus, and various small-molecule agonists have been developed. However, most FFAR1 agonists as well as endogenous ligands, such as linoleic a...
Cell Line Regression Analysis Receptors, G-Protein-Coupled Insulin Machine Learning Protein Binding Peptides Peptide Library Humans HEK293 Cells Cloning, Molecular Amino Acid Substitution Transforming Growth Factor alpha Glucose Drug Evaluation, Preclinical Amino Acid Sequence
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Trends in application of advancing computational approaches in GPCR ligand discovery.

Experimental biology and medicine (Maywood, N.J.) Feb 27, 2021
G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefo...
Drug Design Drug Discovery Receptors, G-Protein-Coupled Humans Ligands Machine Learning
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Spatiotemporal identification of druggable binding sites using deep learning.

Communications biology Oct 27, 2020
Identification of novel protein binding sites expands druggable genome and opens new opportunities for drug discovery. Generally, presence or absence of a binding site depends on the three-dimensional conformation of a protein, making binding site id...
Models, Biological Adenosine Triphosphate Protein Conformation Protein Binding Receptors, G-Protein-Coupled Models, Molecular Binding Sites Ion Channel Gating Receptors, Purinergic P2X3 Software Drug Delivery Systems Deep Learning
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Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Scientific reports Oct 8, 2020
Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision medicine and drug discovery. In this study, we perf...
Humans Neural Networks, Computer Algorithms Drug Discovery Receptors, G-Protein-Coupled Antineoplastic Agents Deep Learning Triple Negative Breast Neoplasms
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Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening.

Journal of chemical information and modeling Sep 16, 2020
Docking is one of the most important steps in virtual screening pipelines, and it is an established method for examining potential interactions between ligands and receptors. However, this method is computationally expensive, and it is often among th...
Protein Binding Receptors, G-Protein-Coupled Ligands Software Retrospective Studies Molecular Docking Simulation Neural Networks, Computer
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Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition.

Methods (San Diego, Calif.) Jul 6, 2020
In the last decade, machine learning and artificial intelligence applications have received a significant boost in performance and attention in both academic research and industry. The success behind most of the recent state-of-the-art methods can be...
Supervised Machine Learning Ligands Neural Networks, Computer Deep Learning Artificial Intelligence Software Receptors, G-Protein-Coupled Machine Learning Drug Discovery
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Novel scaffold of natural compound eliciting sweet taste revealed by machine learning.

Food chemistry Apr 18, 2020
Sugar replacement is still an active issue in the food industry. The use of structure-taste relationships remains one of the most rational strategy to expand the chemical space associated to sweet taste. A new machine learning model has been setup ba...
Taste Sweetening Agents Humans Machine Learning Receptors, G-Protein-Coupled
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Machine Learning to Identify Flexibility Signatures of Class A GPCR Inhibition.

Biomolecules Mar 14, 2020
We show that machine learning can pinpoint features distinguishing inactive from active states in proteins, in particular identifying key ligand binding site flexibility transitions in GPCRs that are triggered by biologically active ligands. Our anal...
Protein Binding Humans Protein Domains Receptors, G-Protein-Coupled Machine Learning Ligands
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A Machine Learning Approach for Drug-target Interaction Prediction using Wrapper Feature Selection and Class Balancing.

Molecular informatics Feb 11, 2020
Drug-Target interaction (DTI) plays a crucial role in drug discovery, drug repositioning and understanding the drug side effects which helps to identify new therapeutic profiles for various diseases. However, the exponential growth in the genomic and...
Algorithms Computer Simulation Drug Discovery Drug Development Databases, Protein Receptors, G-Protein-Coupled Machine Learning Receptors, Cytoplasmic and Nuclear Pharmaceutical Preparations Enzymes Amino Acid Sequence Ion Channels Databases, Chemical
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Integrated structural modeling and super-resolution imaging resolve GPCR oligomers.

Progress in molecular biology and translational science Dec 6, 2019
Formation of G protein-coupled receptors (GPCRs) dimers and higher order oligomers represents a key mechanism in pleiotropic signaling, yet how individual protomers function within oligomers remains poorly understood. For the Class A/rhodopsin subfam...
Protein Interaction Mapping Protein Structure, Secondary Protein Multimerization Ligands Fluorescence Resonance Energy Transfer Protein Binding Software Receptors, G-Protein-Coupled Allosteric Site Crystallography, X-Ray Humans Computational Biology Mutation Algorithms Neural Networks, Computer Molecular Dynamics Simulation Support Vector Machine Animals Machine Learning
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