A Suite of Designed Protein Cages Using Machine Learning Algorithms and Protein Fragment-Based Protocols.

Meador, Kyle; Castells-Graells, Roger; Aguirre, Roman; Sawaya, Michael R; Arbing, Mark A; Sherman, Trent; Senarathne, Chethaka; Yeates, Todd O

Meador, Kyle; Castells-Graells, Roger; Aguirre, Roman; Sawaya, Michael R; Arbing, Mark A; Sherman, Trent; Senarathne, Chethaka; Yeates, Todd O.

Afiliación

Meador K; Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095.
Castells-Graells R; UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, USA 90095.
Aguirre R; Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095.
Sawaya MR; UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, USA 90095.
Arbing MA; UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, USA 90095.
Sherman T; Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095.
Senarathne C; Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095.
Yeates TO; Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095.

bioRxiv ; 2023 Oct 09.

Article en En | MEDLINE | ID: mdl-37873110

Palabras clave

cryoEM; de novo interface design; machine learning; protein cages; protein-protein docking; self-assembly; symmetry

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

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