AIMC Topic: Receptors, G-Protein-Coupled

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Development of New Methods Needs Proper Evaluation-Benchmarking Sets for Machine Learning Experiments for Class A GPCRs.

Journal of chemical information and modeling Nov 22, 2019
New computational approaches for virtual screening applications are constantly being developed. However, before a particular tool is used to search for new active compounds, its effectiveness in the type of task must be examined. In this study, we co...
Receptors, G-Protein-Coupled Benchmarking Drug Evaluation, Preclinical Ligands Machine Learning User-Computer Interface
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Big Data Challenges Targeting Proteins in GPCR Signaling Pathways; Combining PTML-ChEMBL Models and [S]GTPγS Binding Assays.

ACS chemical neuroscience Nov 4, 2019
G-protein-coupled receptors (GPCRs), also known as 7-transmembrane receptors, are the single largest class of drug targets. Consequently, a large amount of preclinical assays having GPCRs as molecular targets has been released to public sources like ...
Cerebral Cortex Guanosine 5'-O-(3-Thiotriphosphate) Serotonin Agents Signal Transduction Receptors, G-Protein-Coupled Aged Databases, Chemical Adult Male Middle Aged Big Data Protein Binding Humans Machine Learning Female Sulfur Radioisotopes
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A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs.

Molecules (Basel, Switzerland) Jun 2, 2019
G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Muc...
Humans Machine Learning Algorithms Protein Binding Receptors, G-Protein-Coupled Molecular Dynamics Simulation Ligands Molecular Docking Simulation Drug Design Drug Discovery Receptor, Serotonin, 5-HT2A Quantitative Structure-Activity Relationship Binding Sites
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Exploring the Potential of Spherical Harmonics and PCVM for Compounds Activity Prediction.

International journal of molecular sciences May 2, 2019
Biologically active chemical compounds may provide remedies for several diseases. Meanwhile, Machine Learning techniques applied to Drug Discovery, which are cheaper and faster than wet-lab experiments, have the capability to more effectively identif...
Support Vector Machine Databases, Protein Receptors, G-Protein-Coupled Humans Machine Learning Algorithms Animals Drug Discovery
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Applications of machine learning in GPCR bioactive ligand discovery.

Current opinion in structural biology Apr 18, 2019
GPCRs constitute the largest druggable family having targets for 475 Food and Drug Administration (FDA) approved drugs. As GPCRs are of great interest to pharmaceutical industry, enormous efforts are being expended to find relevant and potent GPCR li...
Ligands Drug Design Drug Discovery Receptors, G-Protein-Coupled Humans Machine Learning
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Automated discovery of GPCR bioactive ligands.

Current opinion in structural biology Mar 23, 2019
While G-protein-coupled receptors (GPCRs) constitute the largest class of membrane proteins, structures and endogenous ligands of a large portion of GPCRs remain unknown. Because of the involvement of GPCRs in various signaling pathways and physiolog...
Protein Conformation Machine Learning Molecular Docking Simulation Drug Design Humans Molecular Dynamics Simulation Ligands Drug Discovery Receptors, G-Protein-Coupled
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Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure.

Genomics Dec 11, 2018
The identification of drug-target interactions has great significance for pharmaceutical scientific research. Since traditional experimental methods identifying drug-target interactions is costly and time-consuming, the use of machine learning method...
Ion Channels Machine Learning Receptors, G-Protein-Coupled Software Position-Specific Scoring Matrices Drug Development Protein Conformation Databases, Protein Receptors, Cytoplasmic and Nuclear
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Using machine learning tools for protein database biocuration assistance.

Scientific reports Jul 5, 2018
Biocuration in the omics sciences has become paramount, as research in these fields rapidly evolves towards increasingly data-dependent models. As a result, the management of web-accessible publicly-available databases becomes a central task in biolo...
Receptors, G-Protein-Coupled Data Curation Machine Learning Support Vector Machine Databases, Protein
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Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features.

The journal of physical chemistry letters Apr 17, 2018
Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (...
Fatty Acids Humans Ligands Receptors, Odorant Machine Learning Animals Neoplasm Proteins Protein Binding Models, Molecular Mice Drug Evaluation, Preclinical Receptors, G-Protein-Coupled
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Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Jan 30, 2018
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or si...
Binding Sites Amino Acid Motifs Sequence Analysis, Protein Protein Binding Receptors, G-Protein-Coupled Algorithms Humans Area Under Curve Reproducibility of Results Machine Learning ROC Curve Quercetin Software Ligands False Positive Reactions
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