Artificial di-iron proteins: solution characterization of four helix bundles containing two distinct types of inter-helical loops

J Biol Inorg Chem. 2005 Aug;10(5):539-49. doi: 10.1007/s00775-005-0002-8. Epub 2005 Sep 23.

Abstract

Peptide-based models have an enormous impact for the development of metalloprotein models, as they seem appropriate candidates to mimic both the structural characteristics and reactivity of the natural systems. Through the de novo design of four-helix bundles, we developed the DF (Due Ferri) family of artificial proteins, as models of di-iron and di-manganese metalloproteins. The goal of our research is to elucidate how the electrostatic environment, polarity and solvent accessibility of the metal-binding site, influence the functional properties of di-iron proteins. The first two subsets of the DF protein family, DF1 and DF2, consist of two non-covalently associated helix-loop-helix motifs, which bind the di-metal cofactor near the center of the structure. The DF2 subset was designed to improve the properties of DF1: DF2 and DF2t have several changes in their sequences to improve solubility and metal ion access, as well as a change in the loop connecting the two helices. In order to evaluate how these changes affect the overall structure of the model proteins, we solved the NMR structures of the di-Zn(II) complexes of DF2 and DF2t, and compared these structures with those recently obtained from X-ray crystallography. Further, we examined the thermodynamic consequences associated with the mutations, by measuring the stability of DF2t in the presence of different metal ions, and comparing the results with the data already obtained for DF2. Taken together, analysis of all the data showed the importance of the turn conformation in the design and stability of four-helix bundle.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Amino Acid Sequence
  • Iron / chemistry*
  • Molecular Sequence Data
  • Proteins / chemistry*
  • Sequence Alignment
  • Sequence Homology, Amino Acid
  • Thermodynamics

Substances

  • Proteins
  • Iron