Random encounters between proteins in crowded cells are by no means passive, but found to be under selective control. This control enables proteome solubility, helps to optimise the diffusive search for interaction partners, and allows for adaptation to environmental extremes. Interestingly, the residues that modulate the encounters act mesoscopically through protein surface hydrophobicity and net charge, meaning that their detailed signatures vary across organisms with different intracellular constraints. To examine such variations, we use in-cell NMR relaxation to compare the diffusive behaviour of bacterial and human proteins in both human and Escherichia coli cytosols. We find that proteins that ‘stick’ in E. coli are generally less restricted in mammalian cells. Furthermore, the rotational diffusion in the mammalian cytosol is less sensitive to surface-charge mutations. This implies that, in terms of protein motions, the mammalian cytosol is more forgiving to surface alterations than E. coli cells. The cellular differences seem not linked to the proteome properties per se, but rather to a 6-fold difference in protein concentrations. Our results outline a scenario in which the tolerant cytosol of mammalian cells, found in long-lived multicellular organisms, provides an enlarged evolutionary playground, where random protein-surface mutations are less deleterious than in short-generational bacteria.

Biochemical processes inside living cells take place in a confined and highly crowded environment. As such, macromolecular crowding, one of the most important physicochemical properties of cytoplasm, is an essential element of cell physiology. It not only gives rise to steric repulsion, but also promotes non-specific, transient, interactions (referred to as diffusive interactions) between molecules. Since diffusive interactions are a key way to achieving a highly organized intracellular environment, without such interactions, the cell is just “a bag of molecules”. Therefore, understanding how diffusive interactions modulate protein behavior in live cells is of fundamental importance for revealing the mechanisms of molecular recognition, as well as for understanding the cause of protein misfolding diseases.

This thesis focuses on how macromolecular crowding influences the stability and diffusive motions of proteins within living cells by modulating their diffusive interactions. First, we investigated the thermal stability of superoxide dismutase 1 (SOD1), a protein involved in the development of familial amyotrophic lateral sclerosis (ALS), in mammalian and E. coli cells. Intriguingly, the major thermodynamic consequence of macromolecular crowding is due not only to conventional steric repulsions, but primarily to the detailed chemical nature of the diffusive protein interactions in live cells. Secondly, we presented a mutational study of how these diffusive interactions influence the rotation of proteins in the mammalian and bacterial cytosol. The result is a quantitative description of the physicochemical code for the intracellular protein motion, showing that it depends critically on the surface details of protein and the type of the host cell as well. Thirdly, we characterized the impact of  intracellular protein concentration by altering the volume of E. coli cells by osmotic shock. The results obtained show that the intracellular diffusion of proteins is not determined by the chemical properties of the protein surface alone, but also by the frequency of concentration-dependent encounters. Moreover, it appears that eukaryotes and bacteria have achieved fidelity of biological processes through different evolutionary strategies. Overall, these observations have numerous implications for both functional protein design and deciphering the evolution of the surface characteristics of proteins.

Subsequently, we attempted to shed new light on the Hofmeister series, using protein-folding kinetics as observable. The results indicate that the Hofmeister series cannot be explained entirely by the traditional Kosmotropes/Chaotropes classification. Strong hetero-ion pairing cannot be ignored when trying to understand the effects of salts on protein salting-in and salting-out behaviors.

A conspicuous feature of the amyotrophic lateral sclerosis (ALS)-associated protein SOD1 is that its maturation into a functional enzyme relies on local folding of two disordered loops into a catalytic subdomain. To drive the disorder-to-order transition, the protein employs a single Zn2+ ion. The question is then if the entropic penalty of maintaining such disordered loops in the immature apoSOD1 monomer is large enough to explain its unusually low stability, slow folding, and pathological aggregation in ALS. To find out, we determined the effects of systematically altering the SOD1-loop lengths by protein redesign. The results show that the loops destabilize the apoSOD1 monomer by similar to 3 kcal/mol, rendering the protein marginally stable and accounting for its aggregation behavior. Yet the effect on the global folding kinetics remains much smaller with a transition-state destabilization of <1 kcal/mol. Notably, this 1/3 transition-state to folded-state stability ratio provides a clear-cut example of the enigmatic disagreement between the Leffler alpha value from loop-length alterations (typically 1/3) and the standard reaction coordinates based on solvent perturbations (typically >2/3). Reconciling the issue, we demonstrate that the disagreement disappears when accounting for the progressive loop shortening that occurs along the folding pathway. The approach assumes a consistent Flory loop entropy scaling factor of c = 1.48 for both equilibrium and kinetic data and has the added benefit of verifying the tertiary interactions of the folding nucleus as determined by phi-value analysis. Thus, SOD1 not only represents a case where evolution of key catalytic function has come with the drawback of a destabilized apo state but also stands out as a well-suited model system for exploring the physicochemical details of protein self-organization.

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.

Although protein folding and stability have been well explored under simplified conditions in vitro, it is yet unclear how these basic self-organization events are modulated by the crowded interior of live cells. To find out, we use here in-cell NMR to follow at atomic resolution the thermal unfolding of a beta-barrel protein inside mammalian and bacterial cells. Challenging the view from in vitro crowding effects, we find that the cells destabilize the protein at 37 degrees C but with a conspicuous twist: While the melting temperature goes down the cold unfolding moves into the physiological regime, coupled to an augmented heat-capacity change. The effect seems induced by transient, sequence-specific, interactions with the cellular components, acting preferentially on the unfolded ensemble. This points to a model where the in vivo influence on protein behavior is case specific, determined by the individual protein's interplay with the functionally optimized interaction landscape of the cellular interior.