ArticleNature chemical biology2026
Customizing the structure of minimal TIM barrels to craft efficient de novo enzymes.
Article in Nature chemical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Multistate Enzyme Design Enables Efficient and Stereoselective Multistep Catalysis.bioRxiv : the preprint server for biology · 2026Article
- Stability and cooperativity in chimeric de novo TIM barrels via quarter swapping.Protein science : a publication of the Protein Society · 2026Article
- Designing de novo TIM barrels: insights into stabilization, diversification, and functionalization strategies.Biochemical Society transactions · 2026Review
- Protein engineering: status report.Protein engineering, design & selection : PEDS · 2026Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The TIM barrel is the most prevalent fold in natural enzymes, supporting efficient catalysis of diverse reactions. While de novo TIM barrels have been designed, their minimalistic architecture lacks structural elements essential for substrate binding and catalysis. Here, we present CANVAS, a computational workflow that introduces a structural lid into a minimal de novo TIM barrel to anchor catalytic residues and form an active site. Starting from two scaffolds, we designed nine variants with tailored lids for the Kemp elimination. Four showed measurable activity, with the most active reaching a catalytic efficiency of 21,000 M
Identifiers
42297966What OpenQuestion holds
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.