ArticleScientific reports2016
Function-specific virtual screening for GPCR ligands using a combined scoring method.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
37 citing papers in PubMed, 89 citations in OpenAlex.
- Trial
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- Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition.Nature reviews. Drug discovery · 2024Review
- VirtuousPocketome: a computational tool for screening protein-ligand complexes to identify similar binding sites.Scientific reports · 2024Article
- Computational drug development for membrane protein targets.Nature biotechnology · 2024Review
- Activity Map and Transition Pathways of G Protein-Coupled Receptor Revealed by Machine Learning.Journal of chemical information and modeling · 2023Article
- One class classification for the detection of β2 adrenergic receptor agonists using single-ligand dynamic interaction data.Journal of cheminformatics · 2022Article
- Combined docking and machine learning identify key molecular determinants of ligand pharmacological activity on β2 adrenoceptor.Pharmacology research & perspectives · 2022Article
- Optimization of Peptide Linker-Based Fluorescent Ligands for the Histamine HJournal of medicinal chemistry · 2022Article
- Main protease inhibitors and drug surface hotspots for the treatment of COVID-19: A drug repurposing and molecular docking approach.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021Article
- Ligands of Adrenergic Receptors: A Structural Point of View.Biomolecules · 2021Review
- Discovery of Novel Allosteric Modulators Targeting an Extra-Helical Binding Site of GLP-1R Using Structure- and Ligand-Based Virtual Screening.Biomolecules · 2021Article
- Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study.Journal of cheminformatics · 2021Article
- Molecular Modeling of Histamine Receptors-Recent Advances in Drug Discovery.Molecules (Basel, Switzerland) · 2021Review
- New machine learning and physics-based scoring functions for drug discovery.Scientific reports · 2021Article
- G protein-coupled receptors: structure- and function-based drug discovery.Signal transduction and targeted therapy · 2021Review
- Computational Prediction of Chemical Tools for Identification and Validation of Synthetic Lethal Interaction Networks.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches.Molecules (Basel, Switzerland) · 2020Review
- A Focus on Unusual ECL2 Interactions Yields βChemMedChem · 2020Article
- Application of MM-PBSA Methods in Virtual Screening.Molecules (Basel, Switzerland) · 2020Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability of scoring functions to correctly select and rank docking poses of small molecules in protein binding sites is highly target dependent, which presents a challenge for structure-based drug discovery. Here we describe a virtual screening method that combines an energy-based docking scoring function with a molecular interaction fingerprint (IFP) to identify new ligands based on G protein-coupled receptor (GPCR) crystal structures. The consensus scoring method is prospectively evaluated by: 1) the discovery of chemically novel, fragment-like, high affinity histamine H1 receptor (H1R) antagonists/inverse agonists, 2) the selective structure-based identification of ß2-adrenoceptor (ß2R) agonists, and 3) the experimental validation and comparison of the combined and individual scoring approaches. Systematic retrospective virtual screening simulations allowed the definition of scoring cut-offs for the identification of H1R and ß2R ligands and the selection of an optimal ß-adrenoceptor crystal structure for the discrimination between ß2R agonists and antagonists. The consensus approach resulted in the experimental validation of 53% of the ß2R and 73% of the H1R virtual screening hits with up to nanomolar affinities and potencies. The selective identification of ß2R agonists shows the possibilities of structure-based prediction of GPCR ligand function by integrating protein-ligand binding mode information.
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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.