ArticlePLoS computational biology2020
Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 42 citations in OpenAlex.
- Improving AlphaFold2 Performance in Virtual Screens Targeting GPCRs by Enhancing Binding-Site Conformational Sampling.Journal of chemical information and modeling · 2026Article
- Integrated Computer-Aided Drug Design: Advances in GPCR Natural Ligand Discovery.Cell biochemistry and biophysics · 2026Review
- Multimodal out-of-distribution individual uncertainty quantification enhances binding affinity prediction for polypharmacology.Nature machine intelligence · 2025Article
- Orphan GPCRs in Neurodegenerative Disorders: Integrating Structural Biology and Drug Discovery Approaches.Current issues in molecular biology · 2024Review
- Elucidation of the structural basis for ligand binding and translocation in conserved insect odorant receptor co-receptors.Nature communications · 2023Article
- A practical guide to machine-learning scoring for structure-based virtual screening.Nature protocols · 2023Review
- Physiological activation of human and mouse bitter taste receptors by bile acids.Communications biology · 2023Article
- Human Gingival Fibroblasts as a Novel Cell Model Describing the Association between Bitter Taste Thresholds and Interleukin-6 Release.Journal of agricultural and food chemistry · 2023Article
- Homology Modeling of the G Protein-Coupled Receptors.Methods in molecular biology (Clifton, N.J.) · 2023Article
- End-to-end sequence-structure-function meta-learning predicts genome-wide chemical-protein interactions for dark proteins.PLoS computational biology · 2023Article
- Mind the Gap-Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence.Pharmaceuticals (Basel, Switzerland) · 2022Review
- Reinforcement learning for systems pharmacology-oriented and personalized drug design.Expert opinion on drug discovery · 2022Review
- Insect RDL Receptor Models for Virtual Screening: Impact of the Template Conformational State in Pentameric Ligand-Gated Ion Channels.ACS omega · 2022Article
- Computational approaches for the design of novel dopamine DIn silico pharmacology · 2022Article
- Recent Advances in Structure, Function, and Pharmacology of Class A Lipid GPCRs: Opportunities and Challenges for Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2021Review
- Overcoming Depression with 5-HTInternational journal of molecular sciences · 2021Review
- Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology.Research square · 2021Article
- A practical guide to large-scale docking.Nature protocols · 2021Review
- Article
- Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?PLoS computational biology · 2021Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even yielded ligand enrichment comparable to or better than that of the D2R and 5-HT2AR crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models.
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