AIMC Topic: Receptors, G-Protein-Coupled

Clear Filters Showing 71 to 80 of 80 articles

PRECOGx: exploring GPCR signaling mechanisms with deep protein representations.

Nucleic acids research Jul 5, 2022
In this study we show that protein language models can encode structural and functional information of GPCR sequences that can be used to predict their signaling and functional repertoire. We used the ESM1b protein embeddings as features and the bind...
Software Computers Genetic Predisposition to Disease Humans Machine Learning Alternative Splicing beta-Arrestins Heterotrimeric GTP-Binding Proteins Receptors, G-Protein-Coupled Internet Signal Transduction
View on PubMed DOI

DeepREAL: a deep learning powered multi-scale modeling framework for predicting out-of-distribution ligand-induced GPCR activity.

Bioinformatics (Oxford, England) Apr 28, 2022
MOTIVATION: Drug discovery has witnessed intensive exploration of predictive modeling of drug-target physical interactions over two decades. However, a critical knowledge gap needs to be filled for correlating drug-target interactions with clinical o...
Drug Discovery Deep Learning Amino Acid Sequence Ligands Receptors, G-Protein-Coupled
View on PubMed DOI

Predicting Residence Time of GPCR Ligands with Machine Learning.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug...
Humans Machine Learning Kinetics Protein Binding Receptors, G-Protein-Coupled Signal Transduction Ligands
View on PubMed DOI

Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.

Briefings in bioinformatics Sep 2, 2021
Structure-based virtual screenings (SBVSs) play an important role in drug discovery projects. However, it is still a challenge to accurately predict the binding affinity of an arbitrary molecule binds to a drug target and prioritize top ligands from ...
Databases, Protein Receptors, G-Protein-Coupled Molecular Structure Deep Learning Protein Binding Crystallization Protein Kinases Ligands Drug Evaluation, Preclinical Humans Molecular Docking Simulation Drug Discovery Algorithms
View on PubMed DOI

A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors.

The Journal of chemical physics Sep 28, 2020
Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rate...
Molecular Dynamics Simulation Receptors, G-Protein-Coupled Pharmaceutical Preparations Kinetics Machine Learning
View on PubMed DOI

Classification of particle trajectories in living cells: Machine learning versus statistical testing hypothesis for fractional anomalous diffusion.

Physical review. E Sep 1, 2020
Single-particle tracking (SPT) has become a popular tool to study the intracellular transport of molecules in living cells. Inferring the character of their dynamics is important, because it determines the organization and functions of the cells. For...
GTP-Binding Proteins Receptors, G-Protein-Coupled Models, Biological Diffusion Machine Learning Cell Survival Biological Transport Single Molecule Imaging
View on PubMed DOI

DeepFam: deep learning based alignment-free method for protein family modeling and prediction.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: A large number of newly sequenced proteins are generated by the next-generation sequencing technologies and the biochemical function assignment of the proteins is an important task. However, biological experiments are too expensive to cha...
Sequence Analysis, Protein Deep Learning Proteins Receptors, G-Protein-Coupled Software
View on PubMed DOI

WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound identification. However, not all ligands have experimentally determined activities. In particular, many G...
Humans Drug Discovery Deep Learning Animals Drug Evaluation, Preclinical Computational Biology Ligands Receptors, G-Protein-Coupled
View on PubMed DOI

Some Remarks on Prediction of Drug-Target Interaction with Network Models.

Current topics in medicinal chemistry Jan 1, 2017
System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-...
Ion Channels Humans Neural Networks, Computer Algorithms Pharmaceutical Preparations Ligands Molecular Docking Simulation Molecular Targeted Therapy Receptors, G-Protein-Coupled
View on PubMed DOI

A novel fractal approach for predicting G-protein-coupled receptors and their subfamilies with support vector machines.

Bio-medical materials and engineering Jan 1, 2015
G-protein-coupled receptors (GPCRs) are seven membrane-spanning proteins and regulate many important physiological processes, such as vision, neurotransmission, immune response and so on. GPCRs-related pathways are the targets of a large number of ma...
Amino Acid Sequence Databases, Protein Molecular Sequence Data Algorithms Data Mining Sequence Alignment Receptors, G-Protein-Coupled Sequence Analysis, Protein Pattern Recognition, Automated Support Vector Machine Fractals Structure-Activity Relationship
View on PubMed DOI
Popular Topics
Recent Journals