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A generic framework for hierarchical de novo protein design.
Harteveld, Zander; Bonet, Jaume; Rosset, Stéphane; Yang, Che; Sesterhenn, Fabian; Correia, Bruno E.
Afiliación
  • Harteveld Z; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.
  • Bonet J; Swiss Institute of Bioinformatics, Lausanne CH-1015, Switzerland.
  • Rosset S; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.
  • Yang C; Swiss Institute of Bioinformatics, Lausanne CH-1015, Switzerland.
  • Sesterhenn F; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.
  • Correia BE; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.
Proc Natl Acad Sci U S A ; 119(43): e2206111119, 2022 10 25.
Article en En | MEDLINE | ID: mdl-36252041
De novo protein design enables the exploration of novel sequences and structures absent from the natural protein universe. De novo design also stands as a stringent test for our understanding of the underlying physical principles of protein folding and may lead to the development of proteins with unmatched functional characteristics. The first fundamental challenge of de novo design is to devise "designable" structural templates leading to sequences that will adopt the predicted fold. Here, we built on the TopoBuilder (TB) de novo design method, to automatically assemble structural templates with native-like features starting from string descriptors that capture the overall topology of proteins. Our framework eliminates the dependency of hand-crafted and fold-specific rules through an iterative, data-driven approach that extracts geometrical parameters from structural tertiary motifs. We evaluated the TopoBuilder framework by designing sequences for a set of five protein folds and experimental characterization revealed that several sequences were folded and stable in solution. The TopoBuilder de novo design framework will be broadly useful to guide the generation of artificial proteins with customized geometries, enabling the exploration of the protein universe.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas / Pliegue de Proteína Tipo de estudio: Prognostic_studies Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas / Pliegue de Proteína Tipo de estudio: Prognostic_studies Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2022 Tipo del documento: Article País de afiliación: Suiza