Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy

Jeremy H. Mills, Sagar D. Khare, Jill M. Bolduc, Farhad Forouhar, Vikram Khipple Mulligan, Scott Lew, Jayaraman Seetharaman, Liang Tong, Barry L. Stoddard, David Baker

Research output: Contribution to journalArticle

69 Scopus citations

Abstract

Genetically encoded unnatural amino acids could facilitate the design of proteins and enzymes of novel function, but correctly specifying sites of incorporation and the identities and orientations of surrounding residues represents a formidable challenge. Computational design methods have been used to identify optimal locations for functional sites in proteins and design the surrounding residues but have not incorporated unnatural amino acids in this process. We extended the Rosetta design methodology to design metalloproteins in which the amino acid (2,2′-bipyridin-5yl)alanine (Bpy-Ala) is a primary ligand of a bound metal ion. Following initial results that indicated the importance of buttressing the Bpy-Ala amino acid, we designed a buried metal binding site with octahedral coordination geometry consisting of Bpy-Ala, two protein-based metal ligands, and two metal-bound water molecules. Experimental characterization revealed a Bpy-Ala-mediated metalloprotein with the ability to bind divalent cations including Co2+, Zn2+, Fe 2+, and Ni2+, with a Kd for Zn2+ of ∼40 pM. X-ray crystal structures of the designed protein bound to Co 2+ and Ni2+ have RMSDs to the design model of 0.9 and 1.0 Å respectively over all atoms in the binding site.

Original languageEnglish (US)
Pages (from-to)13393-13399
Number of pages7
JournalJournal of the American Chemical Society
Volume135
Issue number36
DOIs
StatePublished - Sep 11 2013

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry
  • Catalysis
  • Colloid and Surface Chemistry

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    Mills, J. H., Khare, S. D., Bolduc, J. M., Forouhar, F., Mulligan, V. K., Lew, S., Seetharaman, J., Tong, L., Stoddard, B. L., & Baker, D. (2013). Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy. Journal of the American Chemical Society, 135(36), 13393-13399. https://doi.org/10.1021/ja403503m