ArticleJournal of chemical information and modeling2019
Understanding Ligand Binding Selectivity in a Prototypical GPCR Family.
Article in Journal of chemical information and modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 40 citations in OpenAlex.
- Dynamic mechanism for subtype selectivity of endocannabinoids.The Journal of biological chemistry · 2026Article
- Identification of Subtype-Selective Binding Sites in the Opioid Receptor Family.Journal of chemical information and modeling · 2026Article
- Structural Determinants of Buprenorphine Partial Agonism at the μ-Opioid Receptor.Journal of chemical information and modeling · 2025Article
- Ligand-Directed Labeling of the Adenosine AJournal of medicinal chemistry · 2024Article
- Entropy drives the ligand recognition in G-protein-coupled receptor subtypes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery.Signal transduction and targeted therapy · 2024Review
- GPCR-IPL score: multilevel featurization of GPCR-ligand interaction patterns and prediction of ligand functions from selectivity to biased activation.Briefings in bioinformatics · 2024Article
- Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor.Journal of chemical theory and computation · 2023Article
- The full activation mechanism of the adenosine AProceedings of the National Academy of Sciences of the United States of America · 2022Article
- Molecular mechanism of allosteric modulation for the cannabinoid receptor CB1.Nature chemical biology · 2022Article
- Optimization of 2-Amino-4,6-diarylpyrimidine-5-carbonitriles as Potent and Selective AJournal of medicinal chemistry · 2022Article
- Prediction of GPCR activity using machine learning.Computational and structural biotechnology journal · 2022Article
- Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?PLoS computational biology · 2021Article
- Ligand design by targeting a binding site water.Chemical science · 2020Article
- Ligand binding free-energy calculations with funnel metadynamics.Nature protocols · 2020Article
- Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies.Journal of chemical theory and computation · 2020Article
- A Taxicab geometry quantification system to evaluate the performance of in silico methods: a case study on adenosine receptors ligands.Journal of computer-aided molecular design · 2020Article
- In Silico Drug Design for Purinergic GPCRs: Overview on Molecular Dynamics Applied to Adenosine and P2Y Receptors.Biomolecules · 2020Review
- Quantitative prediction of selectivity between the AJournal of cheminformatics · 2020Article
- New Insights into Key Determinants for Adenosine 1 Receptor Antagonists Selectivity Using Supervised Molecular Dynamics Simulations.Biomolecules · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adenosine receptors are involved in many pathological conditions and are thus promising drug targets. However, developing drugs that target this GPCR subfamily is a challenging task. A number of drug candidates fail due to lack of selectivity which results in unwanted side effects. The extensive structural similarity of adenosine receptors complicates the design of selective ligands. The problem of selective targeting is a general concern in GPCRs, and in this respect adenosine receptors are a prototypical example. Here we use enhanced sampling simulations to decipher the determinants of selectivity of ligands in A
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.