ArticleJournal of molecular graphics & modelling2025
Comparing models and experimental structures of the GPR101 receptor: Artificial intelligence yields highly accurate models.
Article in Journal of molecular graphics & modelling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Computer-aided structural modeling and drug discovery for G-protein-coupled receptors in the age of artificial intelligence.Current opinion in structural biology · 2026Review
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4 authors.
Funding
Abstract
Experimental structures solved through cryo-electron microscopy have recently been published for GPR101, a G protein-coupled receptor (GPCR) implicated in the genetic condition X-linked acrogigantism (X-LAG). Here, we compared these experimental structures with computational models that we previously published, including our internally developed homology models and third-party models generated through the AlphaFold2 and AlphaFold-Multistate artificial intelligence (AI) methods. Our analysis revealed considerable accuracy for both homology models and AI-generated models. However, it also revealed the general superiority of AI methods. Particularly noteworthy is the model generated by AlphaFold2, which captured with high fidelity various structural aspects, including the challenging second extracellular loop. Our previously published homology model of the GPR101-G
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