Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

Author:

King Neil P.1,Sheffler William1,Sawaya Michael R.2,Vollmar Breanna S.3,Sumida John P.4,André Ingemar5,Gonen Tamir3,Yeates Todd O.67,Baker David18

Affiliation:

1. Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.

2. Howard Hughes Medical Institute, University of California at Los Angeles, and U.S. Department of Energy (UCLA-DOE) Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA.

3. Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.

4. Department of Medicinal Chemistry, University of Washington, Seattle, WA 98177, USA.

5. Department of Biochemistry and Structural Biology, Lund University, SE-221 00 Lund, Sweden.

6. Department of Chemistry and Biochemistry, University of California at Los Angeles, Los Angeles, CA 90095, USA.

7. UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA.

8. Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.

Abstract

Design and Build Self-assembling biomolecules are attractive building blocks in the development of functional materials. Sophisticated DNA-based materials have been developed; however, progress in designing protein-based materials has been slower. King et al. (p. 1171 ) describe a general computational method in which protein building blocks are first symmetrically docked onto a target architecture, and then binding interfaces that drive self-assembly of the building blocks are designed. As a proof of principle, trimeric building blocks were used to design self-assembling 12-subunit complexes with tetrahedral symmetry and 24-subunit complexes with octahedral symmetry. Lai et al. (p. 1129 ) were able to build a 12-subunit tetrahedral protein cage from fused oligomeric protein domains.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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