Crowding induces differences in the diffusion of thermophilic and mesophilic proteins: a new look at neutron scattering results

Decoding the Role of the Global Proteome Dynamics for Cellular Thermal Stability

Molecular mechanisms underlying the thermal response of cells remain elusive. On the basis of the recent result that the short-time diffusive dynamics of the Escherichia coli proteome is an excellent indicator of temperature-dependent bacterial metabolism and death, we used neutron scattering (NS) spectroscopy and molecular dynamics (MD) simulations to investigate the sub-nanosecond proteome mobility in psychro-, meso-, and hyperthermophilic bacteria over a wide temperature range. The magnitude of thermal fluctuations, measured by atomic mean square displacements, is similar among all studied bacteria at their respective thermal cell death. Global roto-translational motions turn out to be the main factor distinguishing the bacterial dynamical properties. We ascribe this behavior to the difference in the average proteome net charge, which becomes less negative for increasing bacterial thermal stability. We propose that the chemical-physical properties of the cytoplasm and the global dynamics of the resulting proteome are fine-tuned by evolution to uphold optimal thermal stability conditions.

Protein Condensation, Cellular Organization, and Spatiotemporal Regulation of Cytoplasmic Properties

The cytoplasm is an aqueous, highly crowded solution of active macromolecules. Its properties influence the behavior of proteins, including their folding, motion, and interactions. In particular, proteins in the cytoplasm can interact to form phase-separated assemblies, so-called biomolecular condensates. The interplay between cytoplasmic properties and protein condensation is critical in a number of functional contexts and is the subject of this review. The authors first describe how cytoplasmic properties can affect protein behavior, in particular condensate formation, and then describe the functional implications of this interplay in three cellular contexts, which exemplify how protein self-organization can be adapted to support certain physiological phenotypes. The authors then describe the formation of RNA-protein condensates in highly polarized cells such as neurons, where condensates play a critical role in the regulation of local protein synthesis, and describe how different stressors trigger extensive reorganization of the cytoplasm, both through signaling pathways and through direct stress-induced changes in cytoplasmic properties. Finally, the authors describe changes in protein behavior and cytoplasmic properties that may occur in extremophiles, in particular organisms that have adapted to inhabit environments of extreme temperature, and discuss the implications and functional importance of these changes.

Variance of Atomic Coordinates as a Dynamical Metric to Distinguish Proteins and Protein-Protein Interactions in Molecular Dynamics Simulations

Protein dynamics is a manifestation of the complex trajectories of these biomolecules on a multidimensional rugged potential energy surface (PES) driven by thermal energy. At present, computational methods such as atomistic molecular dynamics (MD) simulations can describe thermal protein conformational changes in fully solvated environments over millisecond timescales. Despite these advances, a quantitative assessment of protein dynamics remains a complicated topic, intricately linked to issues such as sampling convergence and the identification of appropriate reaction coordinates/structural features to describe protein conformational states and motions. Here, we present the cumulative variance of atomic coordinate fluctuations (CVCF) along trajectories as an intuitive PES sensitive metric to assess both the extent of sampling and protein dynamics captured in MD simulations. We first examine the sampling problem in model one- (1D) and two-dimensional (2D) PES to demonstrate that the CVCF when traced as a function of the sampling variable (time in MD simulations) can identify local and global equilibria. Further, even far from global equilibrium, a situation representative of standard MD trajectories of proteins, the CVCF can distinguish different PES and therefore resolve the resultant protein dynamics. We demonstrate the utility of our CVCF analysis by applying it to distinguish the dynamics of structurally homologous proteins from the ubiquitin family (ubiquitin, SUMO1, SUMO2) and ubiquitin protein-protein interactions. Our CVCF analysis reveals that differential side-chain dynamics from the structured part of the protein (the conserved β-grasp fold) present distinct protein PES to distinguish ubiquitin from SUMO isoforms. Upon binding to two functionally distinct protein partners (UBCH5A and UEV), intrinsic ubiquitin dynamics changes to reflect the binding context even though the two proteins have similar binding modes, which lead to negligible (sub-angstrom scale) structural changes.

Protein thermal stability

Proteins, in general, fold to a well-organized three-dimensional structure in order to function. The stability of this functional shape can be perturbed by external environmental conditions, such as temperature. Understanding the molecular factors underlying the resistance of proteins to the thermal stress has important consequences. First of all, it can aid the design of thermostable enzymes able to perform efficient catalysis in the high-temperature regime. Second, it is an essential brick of knowledge required to decipher the evolutionary pathways of life adaptation on Earth. Thanks to the development of atomistic simulations and ad hoc enhanced sampling techniques, it is now possible to investigate this problem in silico, and therefore provide support to experiments. After having described the methodological aspects, the chapter proposes an extended discussion on two problems. First, we focus on thermophilic proteins, a perfect model to address the issue of thermal stability and molecular evolution. Second, we discuss the issue of how protein thermal stability is affected by crowded in vivo-like conditions.

Differential Effects of Hydrophobic Core Packing Residues for Thermodynamic and Mechanical Stability of a Hyperthermophilic Protein

Proteins from organisms that have adapted to environmental extremes provide attractive systems to explore and determine the origins of protein stability. Improved hydrophobic core packing and decreased loop-length flexibility can increase the thermodynamic stability of proteins from hyperthermophilic organisms. However, their impact on protein mechanical stability is not known. Here, we use protein engineering, biophysical characterization, single-molecule force spectroscopy (SMFS), and molecular dynamics (MD) simulations to measure the effect of altering hydrophobic core packing on the stability of the cold shock protein TmCSP from the hyperthermophilic bacterium Thermotoga maritima. We make two variants of TmCSP in which a mutation is made to reduce the size of aliphatic groups from buried hydrophobic side chains. In the first, a mutation is introduced in a long loop (TmCSP L40A); in the other, the mutation is introduced on the C-terminal β-strand (TmCSP V62A). We use MD simulations to confirm that the mutant TmCSP L40A shows the most significant increase in loop flexibility, and mutant TmCSP V62A shows greater disruption to the core packing. We measure the thermodynamic stability (ΔGD-N) of the mutated proteins and show that there is a more significant reduction for TmCSP L40A (ΔΔG = 63%) than TmCSP V62A (ΔΔG = 47%), as might be expected on the basis of the relative reduction in the size of the side chain. By contrast, SMFS measures the mechanical stability (ΔG*) and shows a greater reduction for TmCSP V62A (ΔΔG* = 8.4%) than TmCSP L40A (ΔΔG* = 2.5%). While the impact on the mechanical stability is subtle, the results demonstrate the power of tuning noncovalent interactions to modulate both the thermodynamic and mechanical stability of a protein. Such understanding and control provide the opportunity to design proteins with optimized thermodynamic and mechanical properties.

Multi-Conformation Monte Carlo: A Method for Introducing Flexibility in Efficient Simulations of Many-Protein Systems

We present a novel multi-conformation Monte Carlo simulation method that enables the modeling of protein-protein interactions and aggregation in crowded protein solutions. This approach is relevant to a molecular-scale description of realistic biological environments, including the cytoplasm and the extracellular matrix, which are characterized by high concentrations of biomolecular solutes (e.g., 300-400 mg/mL for proteins and nucleic acids in the cytoplasm of Escherichia coli). Simulation of such environments necessitates the inclusion of a large number of protein molecules. Therefore, computationally inexpensive methods, such as rigid-body Brownian dynamics (BD) or Monte Carlo simulations, can be particularly useful. However, as we demonstrate herein, the rigid-body representation typically employed in simulations of many-protein systems gives rise to certain artifacts in protein-protein interactions. Our approach allows us to incorporate molecular flexibility in Monte Carlo simulations at low computational cost, thereby eliminating ambiguities arising from structure selection in rigid-body simulations. We benchmark and validate the methodology using simulations of hen egg white lysozyme in solution, a well-studied system for which extensive experimental data, including osmotic second virial coefficients, small-angle scattering structure factors, and multiple structures determined by X-ray and neutron crystallography and solution NMR, as well as rigid-body BD simulation results, are available for comparison.

How conformational flexibility stabilizes the hyperthermophilic elongation factor G-domain

Proteins from thermophilic organisms are stable and functional well above ambient temperature. Understanding the molecular mechanism underlying such a resistance is of crucial interest for many technological applications. For some time, thermal stability has been assumed to correlate with high mechanical rigidity of the protein matrix. In this work we address this common belief by carefully studying a pair of homologous G-domain proteins, with their melting temperatures differing by 40 K. To probe the thermal-stability content of the two proteins we use extensive simulations covering the microsecond time range and employ several different indicators to assess the salient features of the conformational landscape and the role of internal fluctuations at ambient condition. At the atomistic level, while the magnitude of fluctuations is comparable, the distribution of flexible and rigid stretches of amino-acids is more regular in the thermophilic protein causing a cage-like correlation of amplitudes along the sequence. This caging effect is suggested to favor stability at high T by confining the mechanical excitations. Moreover, it is found that the thermophilic protein, when folded, visits a higher number of conformational substates than the mesophilic homologue. The entropy associated with the occupation of the different substates and the thermal resilience of the protein intrinsic compressibility provide a qualitative insight on the thermal stability of the thermophilic protein as compared to its mesophilic homologue. Our findings potentially open the route to new strategies in the design of thermostable proteins.

Diffusion of two molecular species in a crowded environment: theory and experiments

Diffusion of a two component fluid is studied in the framework of differential equations, but where these equations are systematically derived from a well-defined microscopic model. The model has a finite carrying capacity imposed upon it at the mesoscopic level and this is shown to lead to nonlinear cross diffusion terms that modify the conventional Fickean picture. After reviewing the derivation of the model, the experiments carried out to test the model are described. It is found that it can adequately explain the dynamics of two dense ink drops simultaneously evolving in a container filled with water. The experiment shows that molecular crowding results in the formation of a dynamical barrier that prevents the mixing of the drops. This phenomenon is successfully captured by the model. This suggests that the proposed model can be justifiably viewed as a generalization of standard diffusion to a multispecies setting, where crowding and steric interferences are taken into account.