Stability and deformation of biomolecular condensates under the action of shear flow.

Biomolecular condensates play a key role in cytoplasmic compartmentalization and cell functioning. Despite extensive research on the physico-chemical, thermodynamic, or crowding aspects of the formation and stabilization of the condensates, one less studied feature is the role of external perturbative fluid flow. In fact, in living cells, shear stress may arise from streaming or active transport processes. Here, we investigate how biomolecular condensates are deformed under different types of shear flows. We first model Couette flow perturbations via two-way coupling between the condensate dynamics and fluid flow by deploying Lattice Boltzmann Molecular Dynamics. We then show that a simplified approach where the shear flow acts as a static perturbation (one-way coupling) reproduces the main features of the condensate deformation and dynamics as a function of the shear rate. With this approach, which can be easily implemented in molecular dynamics simulations, we analyze the behavior of biomolecular condensates described through residue-based coarse-grained models, including intrinsically disordered proteins and protein/RNA mixtures. At lower shear rates, the fluid triggers the deformation of the condensate (spherical to oblated object), while at higher shear rates, it becomes extremely deformed (oblated or elongated object). At very high shear rates, the condensates are fragmented. We also compare how condensates of different sizes and composition respond to shear perturbation, and how their internal structure is altered by external flow. Finally, we consider the Poiseuille flow that realistically models the behavior in microfluidic devices in order to suggest potential experimental designs for investigating fluid perturbations in vitro.

Binding site plasticity regulation of the FimH catch-bond mechanism.

The bacterial fimbrial adhesin FimH is a remarkable and well-studied catch-bond protein found at the tip of E. coli type 1 pili, which allows pathogenic strains involved in urinary tract infections to bind high-mannose glycans exposed on human epithelia. The catch-bond behavior of FimH, where the strength of the interaction increases when a force is applied to separate the two partners, enables the bacteria to resist clearance when they are subjected to shear forces induced by urine flow. Two decades of experimental studies performed at the single-molecule level, as well as x-ray crystallography and modeling studies, have led to a consensus picture whereby force separates the binding domain from an inhibitor domain, effectively triggering an allosteric conformational change in the former. This force-induced allostery is thought to be responsible for an increased binding affinity at the core of the catch-bond mechanism. However, some important questions remain, the most challenging one being that the crystal structures corresponding to these two allosteric states show almost superimposable binding site geometries, which questions the molecular origin for the large difference in affinity. Using molecular dynamics with a combination of enhanced-sampling techniques, we demonstrate that the static picture provided by the crystal structures conceals a variety of binding site conformations that have a key impact on the apparent affinity. Crucially, the respective populations in each of these conformations are very different between the two allosteric states of the binding domain, which can then be related to experimental affinity measurements. We also evidence a previously unappreciated but important effect: in addition to the well-established role of the force as an allosteric regulator via domain separation, application of force tends to directly favor the high-affinity binding site conformations. We hypothesize that this additional "local" catch-bond effect could delay unbinding between the bacteria and the host cell before the "global" allosteric transition occurs, as well as stabilizing the complex even more once in the high-affinity allosteric state.

Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.

In this work, we investigated the lactate dehydrogenase (LDH) from Selenomonas ruminantium (S. rum), an enzyme that differs at key amino acid positions from canonical allosteric LDHs. The wild type (Wt) of this enzyme recognises pyuvate as all LDHs. However, introducing a single point mutation in the active site loop (I85R) allows S. Rum LDH to recognize the oxaloacetate substrate as a typical malate dehydrogenase (MalDH), whilst maintaining homotropic activation as an LDH. We report the tertiary structure of the Wt and I85RLDH mutant. The Wt S. rum enzyme structure binds NADH and malonate, whilst also resembling the typical compact R-active state of canonical LDHs. The structure of the mutant with I85R was solved in the Apo State (without ligand), and shows no large conformational reorganization such as that observed with canonical allosteric LDHs in Apo state. This is due to a local structural feature typical of S. rum LDH that prevents large-scale conformational reorganization. The S. rum LDH was also studied using Molecular Dynamics simulations, probing specific local deformations of the active site that allow the S. rum LDH to sample the T-inactive state. We propose that, with respect to the LDH/MalDH superfamily, the S. rum enzyme possesses a specificstructural and dynamical way to ensure homotropic activation.

Metastable alpha-rich and beta-rich conformations of small Aß42 peptide oligomers.

Probing the structures of amyloid-ß (Aß) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and simulations on Aß42 monomer point to random coil conformations with either transient helical or ß-strand content. Our current conformational description of small Aß42 oligomers is funneled toward amorphous aggregates with some ß-sheet content and rare high energy states with well-ordered assemblies of ß-sheets. In this study, we emphasize another view based on metastable α-helix bundle oligomers spanning the C-terminal residues, which are predicted by the machine-learning AlphaFold2 method and supported indirectly by low-resolution experimental data on many amyloid polypeptides. This finding has consequences in developing novel chemical tools and to design potential therapies to reduce aggregation and toxicity.

Evolution of large Aß16-22 aggregates at atomic details and potential of mean force associated to peptide unbinding and fragmentation events.

Atomic characterization of large nonfibrillar aggregates of amyloid polypeptides cannot be determined by experimental means. Starting from ß-rich aggregates of Y and elongated topologies predicted by coarse-grained simulations and consisting of more than 100 Aß16-22 peptides, we performed atomistic molecular dynamics (MD), replica exchange with solute scaling (REST2), and umbrella sampling simulations using the CHARMM36m force field in explicit solvent. Here, we explored the dynamics within 3 µs, the free energy landscape, and the potential of mean force associated with either the unbinding of one single peptide in different configurations within the aggregate or fragmentation events of a large number of peptides. Within the time scale of MD and REST2, we find that the aggregates experience slow global conformational plasticity, and remain essentially random coil though we observe slow beta-strand structuring with a dominance of antiparallel beta-sheets over parallel beta-sheets. Enhanced REST2 simulation is able to capture fragmentation events, and the free energy of fragmentation of a large block of peptides is found to be similar to the free energy associated with fibril depolymerization by one chain for longer Aß sequences.

Protein Conformational Space at the Edge of Allostery: Turning a Nonallosteric Malate Dehydrogenase into an "Allosterized" Enzyme Using Evolution-Guided Punctual Mutations.

We unveil the intimate relationship between protein dynamics and allostery by following the trajectories of model proteins in their conformational and sequence spaces. Starting from a nonallosteric hyperthermophilic malate dehydrogenase, we have tracked the role of protein dynamics in the evolution of the allosteric capacity. Based on a large phylogenetic analysis of the malate (MalDH) and lactate dehydrogenase (LDH) superfamily, we identified two amino acid positions that could have had a major role for the emergence of allostery in LDHs, which we targeted for investigation by site-directed mutagenesis. Wild-type MalDH and the single and double mutants were tested with respect to their substrate recognition profiles. The double mutant displayed a sigmoid-shaped profile typical of homotropic activation in LDH. By using molecular dynamics simulations, we showed that the mutations induce a drastic change in the protein sampling of its conformational landscape, making transiently T-like (inactive) conformers, typical of allosteric LDHs, accessible. Our data fit well with the seminal key concept linking protein dynamics and evolvability. We showed that the selection of a new phenotype can be achieved by a few key dynamics-enhancing mutations causing the enrichment of low-populated conformational substates.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis.

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aß, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

An operative framework to model mucus clearance in silico by coupling cilia motion with the liquid environment.

Mucociliary clearance is the first defense mechanism of the respiratory tract against inhaled particles. This mechanism is based on the collective beating motion of cilia at the surface of epithelial cells. Impaired clearance, either caused by malfunctioning or absent cilia, or mucus defects, is a symptom of many respiratory diseases. Here, by exploiting the lattice Boltzmann particle dynamics technique, we develop a model to simulate the dynamics of multiciliated cells in a two-layer fluid. First, we tuned our model to reproduce the characteristic length- and time-scales of the cilia beating. We then check for the emergence of the metachronal wave as a consequence of hydrodynamic mediated correlations between beating cilia. Finally, we tune the viscosity of the top fluid layer to simulate the mucus flow upon cilia beating, and evaluate the pushing efficiency of a carpet of cilia. With this work, we build a realistic framework that can be used to explore several important physiological aspects of mucociliary clearance.

Explicit Models of Motion to Understand Protein Side-Chain Dynamics.

Nuclear magnetic relaxation is widely used to probe protein dynamics. For decades, most analyses of relaxation in proteins have relied successfully on the model-free approach, forgoing mechanistic descriptions of motion. Model-free types of correlation functions cannot describe a large carbon-13 relaxation dataset in protein side chains. Here, we use molecular dynamics simulations to design explicit models of motion and solve Fokker-Planck diffusion equations. These models of motion provide better agreement with relaxation data, mechanistic insight, and a direct link to configuration entropy.

Artificial Water Channels Form Precursors to Sponge-Like Aggregates in Water-Ethanol Mixtures.

Self-assembled artificial water channels (AWCs) are reshaping current water desalination technologies. Recently, the improvements achieved by incorporating hydrophilic compounds into polyamide membranes (PA) at the interface were confirmed experimentally. However, the determination of the nanoscale structures of AWCs remains unclear. An important step in the preparation of PA membranes is the solubilization of a colloidal suspension of the solid phase in a water-ethanol mixture. We perform molecular dynamics simulations to study the nanoscale structures of AWC aggregates. We characterize the size and shape of the aggregates at several key locations in the ternary phase diagram. The role of ethanol in the formation of the interface between the solvent and the solute phase is highlighted. We found that the structure of the aggregates formed in the ternary solution resembled the disordered sponge-like structures observed when AWCs were inserted into lipid membranes. Such permeable sponge architectures allow the passage of water despite their noncrystalline organization and were previously shown to be consistent with AWC permeation measurements in membrane environments.

Biochemical, structural and dynamical studies reveal strong differences in the thermal-dependent allosteric behavior of two extremophilic lactate dehydrogenases.

In this work, we combined biochemical and structural investigations with molecular dynamics (MD) simulations to analyze the very different thermal-dependent allosteric behavior of two lactate dehydrogenases (LDH) from thermophilic bacteria. We found that the enzyme from Petrotoga mobilis (P. mob) necessitates an absolute requirement of the allosteric effector (fructose 1, 6-bisphosphate) to ensure functionality. In contrast, even without allosteric effector, the LDH from Thermus thermophilus (T. the) is functional when the temperature is raised. We report the crystal structure of P. mob LDH in the Apo state solved at 1.9 Å resolution. We used this structure and the one from T. the, obtained previously, as a starting point for MD simulations at various temperatures. We found clear differences between the thermal dynamics, which accounts for the behavior of the two enzymes. Our work demonstrates that, within an allosteric enzyme, some areas act as local gatekeepers of signal transmission, allowing the enzyme to populate either the T-inactive or the R-active states with different degrees of stringency.

Sequestration of Proteins in Stress Granules Relies on the In-Cell but Not the In Vitro Folding Stability.

Stress granules (SGs) are among the most studied membraneless organelles that form upon heat stress (HS) to sequester unfolded, misfolded, or aggregated protein, supporting protein quality control (PQC) clearance. The folding states that are primarily associated with SGs, as well as the function of the phase separated environment in adjusting the energy landscapes, remain unknown. Here, we investigate the association of superoxide dismutase 1 (SOD1) proteins with different folding stabilities and aggregation propensities with condensates in cells, in vitro and by simulation. We find that irrespective of aggregation the folding stability determines the association of SOD1 with SGs in cells. In vitro and in silico experiments however suggest that the increased flexibility of the unfolded state constitutes only a minor driving force to associate with the dynamic biomolecular network of the condensate. Specific protein-protein interactions in the cytoplasm in comparison to SGs determine the partitioning of folding states between the respective phases during HS.

Hydroxy Channels-Adaptive Pathways for Selective Water Cluster Permeation.

Artificial water channels (AWCs) are known to selectively transport water, with ion exclusion. Similarly to natural porins, AWCs encapsulate water wires or clusters, offering continuous and iterative H-bonding that plays a vital role in their stabilization. Herein, we report octyl-ureido-polyol AWCs capable of self-assembly into hydrophilic hydroxy channels. Variants of ethanol, propanediol, and trimethanol are used as head groups to modulate the water transport permeabilities, with rejection of ions. The hydroxy channels achieve a single-channel permeability of 2.33 × 108 water molecules per second, which is within the same order of magnitude as the transport rates for aquaporins. Depending on their concentration in the membrane, adaptive channels are observed in the membrane. Over increased concentrations, a significant shift occurs, initiating unexpected higher water permeation. Molecular simulations probe that spongelike or cylindrical aggregates can form to generate transient cluster water pathways through the bilayer. Altogether, the adaptive self-assembly is a key feature influencing channel efficiency. The adaptive channels described here may be considered an important milestone contributing to the systematic discovery of artificial water channels for water desalination.

Molecular dynamics simulations reveal statistics and microscopic mechanisms of water permeation in membrane-embedded artificial water channel nanoconstructs.

Understanding water transport mechanisms at the nanoscale level remains a challenge for theoretical chemical physics. Major advances in chemical synthesis have allowed us to discover new artificial water channels, rivaling with or even surpassing water conductance and selectivity of natural protein channels. In order to interpret experimental features and understand microscopic determinants for performance improvements, numerical approaches based on all-atom molecular dynamics simulations and enhanced sampling methods have been proposed. In this study, we quantify the influence of microscopic observables, such as channel radius and hydrogen bond connectivity, and of meso-scale features, such as the size of self-assembly blocks, on the permeation rate of a self-assembled nanocrystal-like artificial water channel. Although the absolute permeation rate extrapolated from these simulations is overestimated by one order of magnitude compared to the experimental measurement, the detailed analysis of several observed conductive patterns in large assemblies opens new pathways to scalable membranes with enhanced water conductance for the future design.

Thermal Adaptation of Enzymes: Impacts of Conformational Shifts on Catalytic Activation Energy and Optimum Temperature.

Thermal adaptation of enzymes is essential for both living organism development in extreme conditions and efficient biocatalytic applications. However, the molecular mechanisms leading to a shift in catalytic activity optimum temperatures remain unclear, and there is increasing experimental evidence that thermal adaptation involves complex changes in both structural and reactive properties. Here, a combination of enhanced protein conformational sampling with an explicit chemical reaction description was applied to mesophilic and thermophilic homologues of the dihydrofolate reductase enzyme, and a quantitative description of the stability and catalytic activity shifts between homologues was obtained. The key role played by temperature-induced shifts in protein conformational distributions is revealed. In contrast with pictures focusing on protein flexibility and dynamics, it is shown that while the homologues' reaction free energies are similar, the striking discrepancy between their activation energies is caused by their different conformational changes with temperature. An analytic model is proposed that combines catalytic activity and structural stability, and which quantitatively predicts the shift in homologue optimum temperatures. It is shown that this general model provides a molecular explanation of changes in optimum temperatures for several other enzymes.

Differences in thermal structural changes and melting between mesophilic and thermophilic dihydrofolate reductase enzymes.

A key aspect of life's evolution on Earth is the adaptation of proteins to be stable and work in a very wide range of temperature conditions. A detailed understanding of the associated molecular mechanisms would also help to design enzymes optimized for biotechnological processes. Despite important advances, a comprehensive picture of how thermophilic enzymes succeed in functioning under extreme temperatures remains incomplete. Here, we examine the temperature dependence of stability and of flexibility in the mesophilic monomeric Escherichia coli (Ec) and thermophilic dimeric Thermotoga maritima (Tm) homologs of the paradigm dihydrofolate reductase (DHFR) enzyme. We use all-atom molecular dynamics simulations and a replica-exchange scheme that allows to enhance the conformational sampling while providing at the same time a detailed understanding of the enzymes' behavior at increasing temperatures. We show that this approach reproduces the stability shift between the two homologs, and provides a molecular description of the denaturation mechanism by identifying the sequence of secondary structure elements melting as temperature increases, which is not straightforwardly obtained in the experiments. By repeating our approach on the hypothetical TmDHFR monomer, we further determine the respective effects of sequence and oligomerization in the exceptional stability of TmDFHR. We show that the intuitive expectation that protein flexibility and thermal stability are correlated is not verified. Finally, our simulations reveal that significant conformational fluctuations already take place much below the melting temperature. While the difference between the TmDHFR and EcDHFR catalytic activities is often interpreted via a simplified two-state picture involving the open and closed conformations of the key M20 loop, our simulations suggest that the two homologs' markedly different activity temperature dependences are caused by changes in the ligand-cofactor distance distributions in response to these conformational changes.

Critical structural fluctuations of proteins upon thermal unfolding challenge the Lindemann criterion.

Internal subnanosecond timescale motions are key for the function of proteins, and are coupled to the surrounding solvent environment. These fast fluctuations guide protein conformational changes, yet their role for protein stability, and for unfolding, remains elusive. Here, in analogy with the Lindemann criterion for the melting of solids, we demonstrate a common scaling of structural fluctuations of lysozyme protein embedded in different environments as the thermal unfolding transition is approached. By combining elastic incoherent neutron scattering and advanced molecular simulations, we show that, although different solvents modify the protein melting temperature, a unique dynamical regime is attained in proximity of thermal unfolding in all solvents that we tested. This solvation shell-independent dynamical regime arises from an equivalent sampling of the energy landscape at the respective melting temperatures. Thus, we propose that a threshold for the conformational entropy provided by structural fluctuations of proteins exists, beyond which thermal unfolding is triggered.

Probing the quality control mechanism of the Escherichia coli twin-arginine translocase with folding variants of a de novo-designed heme protein.

Protein transport across the cytoplasmic membrane of bacterial cells is mediated by either the general secretion (Sec) system or the twin-arginine translocase (Tat). The Tat machinery exports folded and cofactor-containing proteins from the cytoplasm to the periplasm by using the transmembrane proton motive force as a source of energy. The Tat apparatus apparently senses the folded state of its protein substrates, a quality-control mechanism that prevents premature export of nascent unfolded or misfolded polypeptides, but its mechanistic basis has not yet been determined. Here, we investigated the innate ability of the model Escherichia coli Tat system to recognize and translocate de novo-designed protein substrates with experimentally determined differences in the extent of folding. Water-soluble, four-helix bundle maquette proteins were engineered to bind two, one, or no heme b cofactors, resulting in a concomitant reduction in the extent of their folding, assessed with temperature-dependent CD spectroscopy and one-dimensional 1H NMR spectroscopy. Fusion of the archetypal N-terminal Tat signal peptide of the E. coli trimethylamine-N-oxide (TMAO) reductase (TorA) to the N terminus of the protein maquettes was sufficient for the Tat system to recognize them as substrates. The clear correlation between the level of Tat-dependent export and the degree of heme b-induced folding of the maquette protein suggested that the membrane-bound Tat machinery can sense the extent of folding and conformational flexibility of its substrates. We propose that these artificial proteins are ideal substrates for future investigations of the Tat system's quality-control mechanism.

Stability Effect of Quinary Interactions Reversed by Single Point Mutations.

In cells, proteins are embedded in a crowded environment that controls their properties via manifold avenues including weak protein-macromolecule interactions. A molecular level understanding of these quinary interactions and their contribution to protein stability, function, and localization in the cell is central to modern structural biology. Using a mutational analysis to quantify the energetic contributions of single amino acids to the stability of the ALS related protein superoxide dismutase I (SOD1) in mammalian cells, we show that quinary interactions destabilize SOD1 by a similar energetic offset for most of the mutants, but there are notable exceptions: Mutants that alter its surface properties can even lead to a stabilization of the protein in the cell as compared to the test tube. In conclusion, quinary interactions can amplify and even reverse the mutational response of proteins, being a key aspect in pathogenic protein misfolding and aggregation.

Multi-scale simulations of biological systems using the OPEP coarse-grained model.

Biomolecules are complex machines that are optimized by evolution to properly fulfill or contribute to a variety of biochemical tasks in the cellular environment. Computer simulations based on quantum mechanics and atomistic force fields have been proven to be a powerful microscope for obtaining valuable insights into many biological, physical, and chemical processes. Many interesting phenomena involve, however, a time scale and a number of degrees of freedom, notably if crowding is considered, that cannot be explored at an atomistic resolution. To bridge the gap between reality and simulation, many different advanced computational techniques and coarse-grained (CG) models have been developed. Here, we report some applications of the CG OPEP protein model to amyloid fibril formation, the response of catch-bond proteins to two types of fluid flow, and interactive simulations to fold peptides with well-defined 3D structures or with intrinsic disorder.