ArticleProtein science : a publication of the Protein Society2024
Re-engineering of a carotenoid-binding protein based on NMR structure.
Article in Protein science : a publication of the Protein Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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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Who cites it
3 citing papers in PubMed.
- Limitations of the refolding pipeline for de novo protein design.Protein science : a publication of the Protein Society · 2026Article
- Engineering of soluble bacteriorhodopsin.Chemical science · 2025Article
- Re-engineering of a carotenoid-binding protein based on NMR structure.Protein science : a publication of the Protein Society · 2024Article
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Authors and funding
9 authors.
Funding
Abstract
Recently, a number of message passing neural network (MPNN)-based methods have been introduced that, based on backbone atom coordinates, efficiently recover native amino acid sequences of proteins and predict modifications that result in better expressing, more soluble, and stable variants. However, usually, X-ray structures, or artificial structures generated by algorithms trained on X-ray structures, were employed to define target backbone conformations. Here, we show that commonly used algorithms ProteinMPNN and SolubleMPNN display low sequence recovery on structures determined using NMR. We subsequently propose a computational approach that we successfully apply to re-engineer AstaP, a protein that natively binds a large hydrophobic ligand astaxanthin (C
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