ArticleActa pharmacologica Sinica2025
AlphaFold3 versus experimental structures: assessment of the accuracy in ligand-bound G protein-coupled receptors.
Article in Acta pharmacologica Sinica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed.
- Article
- Structure-guided design of a PCSK9 epitope vaccine with efficacy against hyperlipidemia and atherosclerosis.Life metabolism · 2026Article
- Potential for the Terminal SKP1 Glycosyltransferase to Exert Non-Enzymatic Control of SKP1 inbioRxiv : the preprint server for biology · 2026Article
- Benchmarking AI Protein Structure Predictors Reveals a Persistent Bias in Multi-State Proteins.bioRxiv : the preprint server for biology · 2026Article
- Chemical adaptation: bridging synthetic chemistry with drug development.Science China. Life sciences · 2026Review
- A brief guideline for the studies of structure-function relationship of ion channels using AlphaFold3.Fundamental research · 2026Review
- Broad and durable protection against SARS-CoV-2 and SARS-CoV by an intranasal chimpanzee adenovirus vaccine expressing tandem RBDs and nucleocapsid.PLoS pathogens · 2026Article
- Navigating the uncharted: AI-driven advances in protein structure, dynamics, interactions and ligand interactions for understudied families.BioData mining · 2026Review
- Computer-aided structural modeling and drug discovery for G-protein-coupled receptors in the age of artificial intelligence.Current opinion in structural biology · 2026Review
- Deep learning-driven decoding of ubiquitination: from regulatory mechanisms to targeted protein degradation.Biology direct · 2026Review
- Improving AlphaFold2 Performance in Virtual Screens Targeting GPCRs by Enhancing Binding-Site Conformational Sampling.Journal of chemical information and modeling · 2026Article
- Benchmarking co-folding methods to predict the structures of covalent protein-ligand complexes.Acta pharmacologica Sinica · 2026Article
- Adhesion G protein-coupled receptors.Pharmacological reviews · 2026Review
- Article
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
- AI-Driven Design of Miniproteins as Potential Allosteric Modulators.Pharmaceuticals (Basel, Switzerland) · 2026Review
- TheScience advances · 2026Article
- Bacterial Chemoreceptors Transmit Stimulus Signals Through Coupled Entropic Switches.Journal of molecular biology · 2026Article
- Structure-Based Prediction of Molecular Interactions for Stabilizing Volatile Drugs.Pharmaceutics · 2026Article
- The transformative impact of AI-enabled AlphaFold 3: evolution, current status, and future prospects in structural biology.Frontiers in artificial intelligence · 2026Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
G protein-coupled receptors (GPCRs) are critical drug targets involved in numerous physiological processes, yet many of their structures remain unresolved due to inherent flexibility and diverse ligand interactions. This study systematically evaluates the accuracy of AlphaFold3-predicted GPCR structures compared to experimentally determined structures, with a primary focus on ligand-bound states. Our analysis reveals that while AlphaFold3 shows improved performance over AlphaFold2 in predicting overall GPCR backbone architecture, significant discrepancies persist in ligand-binding poses, particularly for ions, peptides, and proteins. Despite advancements, these limitations constrain the utility of AlphaFold3 models in functional studies and structure-based drug design, where high-resolution details of ligand interactions are crucial. We assess the accuracy of predicted structures across various ligand types, quantifying deviations in binding pocket geometries and ligand orientations. Our findings highlight specific challenges in the computational prediction of ligand-bound GPCR structures, emphasizing areas where further refinement is needed. This study provides valuable insights for researchers using AlphaFold3 in GPCR studies, underscores the ongoing necessity for experimental structure determination, and offers direction for improving protein-ligand interaction predictions in future computational models.
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