Quinary structure modulates protein stability in cells

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.T he inside of cells is packed with macromolecules whose concentrations reach 300-400 g/L (1). Compared with the ideal (dilute) environments conventionally used to study proteins, crowding inside cells can significantly alter the biophysical landscape of proteins, including their equilibrium thermodynamic stability (2-6). Experimental and computational efforts establish that crowding effects arise from a combination of short-range (steric) repulsions and longer-range (often called soft) interactions between macromolecules (7-13). Despite a growing number of incell protein studies (2-6), there is no quantitative information about the energetics of quinary interactions.Amide proton exchange experiments have been used for more than 50 y to measure equilibrium protein stability, defined as the Gibbs free energy required to open the protein and expose individual backbone amide protons to solvent, ΔG°′ op (14). For the B1 domain of protein G (GB1), ΔG°′ op equals −RTln(k obs /k uns ), where R is the gas constant, T is the absolute temperature, k obs is the observed rate of exchange, and k uns is the rate in an unstructured peptide (6). We know that the cytoplasm does not affect k uns (15). Most importantly, we know that for exchange under these conditions ΔG°′ op approximates the free energy required to denature the protein, ΔG°′ den (6). Therefore, these experiments provide a thermodynamically rigorous measure of equilibrium global protein stability. Using this information, we quantified the stability of GB1 at the residue level in Escherichia coli (6) via NMRdetected backbone amide hydrogen/deuterium exchange (16).Thermodynamic cycles (17) can be used to quantify the energetics of interactions between proteins in specific protein complexes (17,18) and between side chains in globular proteins (19,20). Briefly, the individual effects of two single-site amino acid changes are compared with the combined effect of both mutations. If the sites interact, the sum of the contributions from the single-site changes will not equal the contributi...

In-cell thermodynamics and a new role for protein surfaces

“…1C). T m and ΔG°′ U either decreased or were unchanged compared with buffer (SI Appendix, Tables S1 and S2), consistent with other studies, (13,(15)(16)(17)(18) but inconsistent with previously accepted crowding theory (1,2). ΔC°′ p,U is the same in buffer and in cells (SI Appendix, Table S1).…”

“…Recent modifications to theory (22), as well as simulations of intracellular dynamics, are pointing the way (27). Most importantly, our data, and those of others (13,(15)(16)(17)(18), show that studying protein folding in living cells is key to gaining information needed to understand the many roles of proteins in biology.…”

“…This approach probably overestimates ΔG°′ U, T (gives the maximum stability, "cells-corrected" in Fig. 1C) because in vitro studies with protein crowders as well as in-cell studies show that destabilizing weak attractive interactions often dominate stabilizing hard-core excluded volume effect (13)(14)(15). We expect the true ΔG°′ U, T lies between the two values.…”

Markov modeling of peptide folding in the presence of protein crowders

“…[1][2][3] To understand the role of other interactions, in recent years, there have been increasing efforts to perform computer simulations with realistic crowder molecules, 4-11 rather than hard-sphere crowders. When analyzing these large systems, a major challenge lies in identifying the main states and dynamical modes, which may not be easily anticipated.…”

Charge matters

“…How do proteins remain soluble, yet interact specifically in complex, high-concentration fluids like cell cytosol or plasma? What gives rise to the quinary (McConkey 1982;Monteith et al 2015) structure of the cytosol? What molecular characteristics would be most important when trying to develop a high-concentration biopharmaceutical formulation?…”