ArticleNature chemical biology2024
Rationally seeded computational protein design of ɑ-helical barrels.
Article in Nature chemical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed.
- De Novo-Designed Bifunctional Proteins for Targeted Protein Degradation.Journal of the American Chemical Society · 2026Article
- Article
- Review
- Exploring the Blueprint of Life: The Innovation in Antibody and Protein Design.Combinatorial chemistry & high throughput screening · 2026Article
- Protein Design Meets Single-Molecule Detection: Towards Programmable Nanopore Sensors.International journal of molecular sciences · 2025Review
- Article
- Structural and functional analysis of theProceedings of the National Academy of Sciences of the United States of America · 2025Article
- De Novo Design of Parallel and Antiparallel ABiochemistry · 2025Article
- Confinement and Catalysis withinJournal of the American Chemical Society · 2025Article
- Exchange, promiscuity, and orthogonality inChemical science · 2025Article
- Design of an abiotic unimolecular three-helix bundle.Chemical science · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Computational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix-turn-helix-turn-helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression in Escherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.
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Registered trials
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