Quinary protein structure and the consequences of crowding in living cells: Leaving the test‐tube behind

Wirth, Anna Jean; Gruebele, Martin

doi:10.1002/bies.201300080

Cited by 124 publications

(155 citation statements)

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“…6 not only add physical−chemical detail to the effects of intracellular crowding (4,12,27,53) but also provide a tool for rational protein surface design. Applications can include optimization of target proteins for in-cell NMR detection (54), surface optimization of protein therapeutics (55), and mutational examination of the yet poorly understood relation between protein motion, spatial localization, and function (7,56,57). The message stands clear and simple to test: Can any protein be tuned to desired rotational motion in E. coli.…”

Section: Discussionmentioning

confidence: 99%

Physicochemical code for quinary protein interactions inEscherichia coli

Choi

Lang

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

116

235

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How proteins sense and navigate the cellular interior to find their functional partners remains poorly understood. An intriguing aspect of this search is that it relies on diffusive encounters with the crowded cellular background, made up of protein surfaces that are largely nonconserved. The question is then if/how this protein search is amenable to selection and biological control. To shed light on this issue, we examined the motions of three evolutionary divergent proteins in the Escherichia coli cytoplasm by in-cell NMR. The results show that the diffusive in-cell motions, after all, follow simplistic physical−chemical rules: The proteins reveal a common dependence on (i) net charge density, (ii) surface hydrophobicity, and (iii) the electric dipole moment. The bacterial protein is here biased to move relatively freely in the bacterial interior, whereas the human counterparts more easily stick. Even so, the in-cell motions respond predictably to surface mutation, allowing us to tune and intermix the protein's behavior at will. The findings show how evolution can swiftly optimize the diffuse background of protein encounter complexes by just single-point mutations, and provide a rational framework for adjusting the cytoplasmic motions of individual proteins, e.g., for rescuing poor in-cell NMR signals and for optimizing protein therapeutics.in-cell NMR | protein surface properties | intracellular diffusion D espite considerable progress in mapping out how proteins interact functionally through structure and evolved interfaces (1-3), there is yet little known about how proteins interact nonspecifically upon random diffusive encounters (4-10). Although these nonspecific "quinary" (11) interactions are typically weak and short-lived, they are still expected to affect function because of their sheer numbers: Under crowded cellular conditions, they compete with specific binding (6-8), control diffusion (12), and skew structural stability (5,(13)(14)(15)(16)(17)(18)(19). The question is then to what extent this dynamic background of nonspecific interactions is biologically controlled and optimized. Part of the answer is hinted by the tendency of soluble proteins, nucleic acids, and membranes to carry a repulsive net-negative charge (20,21 , and PO 4 2− (22). However, proteins expose also positive, polar, and hydrophobic moieties that operate against the net-negative charge repulsion by engaging in attractive interactions upon diffusive encounters. The strength and duration of these attractive interactions depend on the proteins' detailed surface composition, relative orientations, and ability to adapt complementary shapes. Following Elcock's estimate for the Escherichia coli cytoplasm, each protein experiences at all times approximately five putative interaction partners in its immediate cellular environment (8). Sometimes, mutual fits enable strong functional binding (1, 2), but, most often, the proteins just separate after a brief tête-à-tête (3), in search of higher-affinity partners. A key detail is that the eff...

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Section: Discussionmentioning

confidence: 99%

Physicochemical code for quinary protein interactions inEscherichia coli

Choi

Lang

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

116

235

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“…The reaction order and K d can be estimated from χ green and χ red as a function of cell-volume change (as shown in SI Appendix, section S3). Thus, our method is particularly useful for detection of weak quinary interactions between proteins inside cells (5,14). For the association between AcGFP1 and mCherry (Fig.…”

Section: Analysis Of Quinary Interactions Using a Quantitative Volumementioning

confidence: 99%

“…The sensitivity of quinary interactions makes them important in fine-tuning cellular processes. For example, it has been proposed that sequential metabolic enzymes could associate to improve substrate transfer between catalytic enzymes (10), that weak protein association can mediate cytokine release (11), or that phase-separated protein droplets held together by quinary interactions could serve for cellular storage or stress response (12, 13).Despite growing interest, quantification of quinary interactions is technically challenging because it requires detection in situ using a mildly perturbing technique (6,14). Previous studies of quinary interactions rely on measurements of large cell populations expressing labeled proteins, e.g., through the use of incell NMR with Escherichia coli (15, 16).…”

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confidence: 99%

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Weak protein–protein interactions in live cells are quantified by cell-volume modulation

Sukenik

Ren

Gruebele

2017

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

104

123

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Weakly bound protein complexes play a crucial role in metabolic, regulatory, and signaling pathways, due in part to the high tunability of their bound and unbound populations. This tunability makes weak binding (micromolar to millimolar dissociation constants) difficult to quantify under biologically relevant conditions. Here, we use rapid perturbation of cell volume to modulate the concentration of weakly bound protein complexes, allowing us to detect their dissociation constant and stoichiometry directly inside the cell. We control cell volume by modulating media osmotic pressure and observe the resulting complex association and dissociation by FRET microscopy. We quantitatively examine the interaction between GAPDH and PGK, two sequential enzymes in the glycolysis catalytic cycle. GAPDH and PGK have been shown to interact weakly, but the interaction has not been quantified in vivo. A quantitative model fits our experimental results with log K d = −9.7 ± 0.3 and a 2:1 prevalent stoichiometry of the GAPDH:PGK complex. Cellular volume perturbation is a widely applicable tool to detect transient protein interactions and other biomolecular interactions in situ. Our results also suggest that cells could use volume change (e.g., as occurs upon entry to mitosis) to regulate function by altering biomolecular complex concentrations.quinary interactions | protein-protein interactions | cell volume | FRET | live-cell microscopy F rom forming active enzymatic complexes to facilitating signal transduction in regulatory networks, protein interactions are pivotal to cell function. Strong interactions, with dissociation constants (K d ) of nanomolar and lower (1, 2), can be measured accurately both in vitro and in vivo (3, 4). These interactions are ideal in cases where the complex should form with high fidelity and persist. The downside of strong binding is that its regulation in the cellular environment is limited: Once a complex is formed, it seldom dissociates.Another type of protein complexes relies on weak, transient interactions, collectively termed quinary interactions (5-7). Such interactions, with a K d in the micromolar to millimolar range, are emerging as important components of the cell's signaling, regulatory, and stress adaptation mechanisms (6,8,9). Their transient nature is key to their function: Unlike tightly bound complexes, quinary interactions are highly sensitive to variations in their environment and respond rapidly to changes in temperature, pressure, pH, or the local concentration of surrounding molecules. The sensitivity of quinary interactions makes them important in fine-tuning cellular processes. For example, it has been proposed that sequential metabolic enzymes could associate to improve substrate transfer between catalytic enzymes (10), that weak protein association can mediate cytokine release (11), or that phase-separated protein droplets held together by quinary interactions could serve for cellular storage or stress response (12, 13).Despite growing interest, quantification of quinary inte...

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“…As a result, the precise origin of non-steric effects is much less well understood in this case than in that of urea and TMAO. Another problem of current interest with links to macromolecular crowding is the formation of protein-rich droplets through reversible liquid-liquid phase separation [39][40][41].…”

Section: Introductionmentioning

confidence: 99%

Protein folding/unfolding in the presence of interacting macromolecular crowders

Irbäck

Mohanty

2017

Eur. Phys. J. Spec. Top.

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Abstract. Recent years have seen an increasing number of biophysical studies of proteins being conducted in cells and concentrated protein solutions. In these experiments, compared to dilute-solution data, both stabilization and destabilization of globular proteins have been observed, which cannot be explained in terms of volume exclusion alone. For a fundamental understanding of the observed effects, there is a need for computational modeling beyond the level of hard-sphere crowders. This mini-review discusses recent efforts to simulate folding/unfolding properties of proteins in the presence of explicit macromolecular crowders. A Monte Carlo-based approach by us is described, which we recently applied to study the equilibrium folding thermodynamics of two peptides in the presence of explicit protein crowders.

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Quinary protein structure and the consequences of crowding in living cells: Leaving the test‐tube behind

Cited by 124 publications

References 93 publications

Physicochemical code for quinary protein interactions inEscherichia coli

Physicochemical code for quinary protein interactions inEscherichia coli

Weak protein–protein interactions in live cells are quantified by cell-volume modulation

Protein folding/unfolding in the presence of interacting macromolecular crowders

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