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. 2015 Feb 10;112(6):1739-42.
doi: 10.1073/pnas.1417415112. Epub 2015 Jan 26.

Quinary structure modulates protein stability in cells

William B Monteith  1 , Rachel D Cohen  1 , Austin E Smith  1 , Emilio Guzman-Cisneros  1 , Gary J Pielak  2
Affiliations

Quinary structure modulates protein stability in cells

William B Monteith et al. Proc Natl Acad Sci U S A. .

Abstract

Protein quinary interactions organize the cellular interior and its metabolism. Although the interactions stabilizing secondary, tertiary, and quaternary protein structure are well defined, details about the protein-matrix contacts that comprise quinary structure remain elusive. This gap exists because proteins function in the crowded cellular environment, but are traditionally studied in simple buffered solutions. We use NMR-detected H/D exchange to quantify quinary interactions between the B1 domain of protein G and the cytosol of Escherichia coli. We demonstrate that a surface mutation in this protein is 10-fold more destabilizing in cells than in buffer, a surprising result that firmly establishes the significance of quinary interactions. Remarkably, the energy involved in these interactions can be as large as the energies that stabilize specific protein complexes. These results will drive the critical task of implementing quinary structure into models for understanding the proteome.

Keywords: H/D exchange; protein NMR; protein thermodynamics; quinary interactions.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Thermodynamic cycle used to quantify quinary interactions.
Fig. 2.
Fig. 2.
Stability change from charge reversal is small in buffer, but large in cells. (A and B) Changes in stability (ΔΔGop,mut°′=ΔGop,var°′−ΔGop,WT°′) caused by the (A) I6L and (B) D40K mutations in cells (green) and in buffer (blue) for quantifiable residues. The number of residues is limited by overlap in NMR spectra and by rates of exchange that are too large to quantify. Error bars represent the uncertainty propagated from triplicate measurements. Complete datasets for D40K and D40N are given in SI Appendix. The datasets for the WT protein and the I6L variant in cells have been published (6).
Fig. 3.
Fig. 3.
Interaction free energies (δΔΔGop,int°′=ΔΔGop,mut,cell°′−ΔΔGop,mut,buff°′) with the cytosol are large for charge-changing mutations. Values for I6L, D40A, D40N, and D40K variants are shown in blue, green, and red, respectively. Error bars represent the uncertainty propagated from triplicate measurements. Dashed lines and associated error bars are the average δΔΔGop,int°′ values and their SDs of the mean. K4 crosspeak volume was insufficient for quantification in the D40K variant.
Fig. 4.
Fig. 4.
Structure of WT GB1 (Protein Data Bank ID code 1pgb) colored by the strength of quinary interactions (δΔΔGop,int°′) in the variants. The coupled effect of mutating GB1 in cells is significantly more destabilizing to D40K, where the mutation involves a charged surface residue. Gray residues yield no data.
Fig. 5.
Fig. 5.
Overlaid in-cell 15N-1H HSQC spectra of WT, D40K, and D40N GB1. Expression of I6L GB1 is too low to observe crosspeaks. The in-cell samples were gently harvested after acquisition and the supernatants analyzed. Lack of crosspeaks in all supernatant spectra indicate the proteins do not leak during the course of the experiments.
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