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De novo design of small beta barrel proteins

Journal Article · · Proceedings of the National Academy of Sciences of the United States of America
 [1];  [2];  [3];  [3];  [3];  [3];  [3];  [3];  [3];  [3];  [3];  [3];  [2];  [2];  [4];  [3]
  1. Univ. of Washington, Seattle, WA (United States); University of Washington, Seattle, WA (United States)
  2. Univ. of Wisconsin, Milwaukee, WI (United States)
  3. Univ. of Washington, Seattle, WA (United States)
  4. Harvard Univ., Cambridge, MA (United States)

Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.

Research Organization:
Univ. of Washington, Seattle, WA (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
SC0018940; AC02-06CH11357
OSTI ID:
2472357
Journal Information:
Proceedings of the National Academy of Sciences of the United States of America, Journal Name: Proceedings of the National Academy of Sciences of the United States of America Journal Issue: 11 Vol. 120; ISSN 0027-8424
Publisher:
National Academy of SciencesCopyright Statement
Country of Publication:
United States
Language:
English

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