Recovering Protein Thermal Stability Using All-Atom Hamiltonian Replica-Exchange Simulations in Explicit Solvent

Recent Progress in Modeling and Simulation of Biomolecular Crowding and Condensation Inside Cells

Macromolecular crowding in the cellular cytoplasm can potentially impact diffusion rates of proteins, their intrinsic structural stability, binding of proteins to their corresponding partners as well as biomolecular organization and phase separation. While such intracellular crowding can have a large impact on biomolecular structure and function, the molecular mechanisms and driving forces that determine the effect of crowding on dynamics and conformations of macromolecules are so far not well understood. At a molecular level, computational methods can provide a unique lens to investigate the effect of macromolecular crowding on biomolecular behavior, providing us with a resolution that is challenging to reach with experimental techniques alone. In this review, we focus on the various physics-based and data-driven computational methods developed in the past few years to investigate macromolecular crowding and intracellular protein condensation. We review recent progress in modeling and simulation of biomolecular systems of varying sizes, ranging from single protein molecules to the entire cellular cytoplasm. We further discuss the effects of macromolecular crowding on different phenomena, such as diffusion, protein-ligand binding, and mechanical and viscoelastic properties, such as surface tension of condensates. Finally, we discuss some of the outstanding challenges that we anticipate the community addressing in the next few years in order to investigate biological phenomena in model cellular environments by reproducing in vivo conditions as accurately as possible.

Simulation-Guided Conformational Space Exploration to Assess Reactive Conformations of a Ribozyme

Self-splicing ribozymes are small ribonucleic acid (RNA) enzymes that catalyze their own cleavage through a transphosphoesterification reaction. While this process is involved in some specific steps of viral RNA replication and splicing, it is also of importance in the context of the (putative) first autocatalytic RNA-based systems that could have preceded the emergence of modern life. The uncatalyzed phosphoester bond formation is thermodynamically very unfavorable, and many experimental studies have focused on understanding the molecular features of catalysis in these ribozymes. However, chemical reaction paths are short-lived and not easily characterized by experimental approaches, so molecular simulation approaches appear as an ideal tool to unveil the molecular details of the reaction. Here, we focus on the model hairpin ribozyme. We show that identifying a relevant initial conformation for reactivity studies, which is frequently overlooked in mixed quantum-classical studies that predominantly concentrate on the chemical reaction itself, can be highly challenging. These challenges stem from limitations in both available experimental structures (which are chemically altered to prevent self-cleavage) and the accuracy of force fields, together with the necessity for comprehensive sampling. We show that molecular dynamics simulations, combined with extensive conformational phase space exploration with Hamiltonian replica-exchange simulations, enable us to characterize the relevant conformational basins of the minimal hairpin ribozyme in the ligated state prior to self-cleavage. We find that what is usually considered a canonical reactive conformation with active site geometries and hydrogen-bond patterns that are optimal for the addition-elimination reaction with general acid/general base catalysis is metastable and only marginally populated. The thermodynamically stable conformation appears to be consistent with the expectations of a mechanism that does not require the direct participation of ribozyme residues in the reaction. While these observations may suffer from forcefield inaccuracies, all investigated forcefields lead to the same conclusions upon proper sampling, contrasting with previous investigations on shorter timescales suggesting that at least one reparametrization of the Amber99 forcefield allowed to stabilize aligned active site conformations. Our study demonstrates that identifying the most pertinent reactant state conformation holds equal importance alongside the accurate determination of the thermodynamics and kinetics of the chemical steps of the reaction.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Atomistic simulations of RNA duplex thermal denaturation: Sequence- and forcefield-dependence

Double-stranded RNA is the end-product of template-based replication, and is also the functional state of some biological RNAs. Similarly to proteins and DNA, they can be denatured by temperature, with important physiological and technological implications. Here, we use an in silico strategy to probe the thermal denaturation of RNA duplexes. Following previous results that were obtained on a few different duplexes, and which nuanced the canonical 2-state picture of nucleic acid denaturation, we here specifically address three different aspects that greatly improve our description of the temperature-induced dsRNA separation. First, we investigate the effect of the spatial distribution of weak and strong base-pairs among the duplex sequence. We show that the deviations from the two-state dehybridization mechanism are more pronounced when a strong core is flanked with weak extremities, while duplexes with a weak core but strong extremities exhibit a two-state behavior, which can be explained by the key role played by base fraying. This was later verified by generating artificial hairpin or circular states containing one or two locked duplex extremities, which results in an important reinforcement of the entire HB structure of the duplex and higher melting temperatures. Finally, we demonstrate that our results are little sensitive to the employed combination of RNA and water forcefields. The trends in thermal stability among the different sequences as well as the observed unfolding mechanisms (and the deviations from a two-state scenario) remain the same regardless of the employed atomistic models. However, our study points to possible limitations of recent reparametrizations of the Amber RNA forcefield, which sometimes results in duplexes that readily denature under ambient conditions, in contradiction with available experimental results.

Temperature sensitive contact modes allosterically gate TRPV3

TRPV Ion channels are sophisticated molecular sensors designed to respond to distinct temperature thresholds. The recent surge in cryo-EM structures has provided numerous insights into the structural rearrangements accompanying their opening and closing; however, the molecular mechanisms by which TRPV channels establish precise and robust temperature sensing remain elusive. In this work we employ molecular simulations, multi-ensemble contact analysis, graph theory, and machine learning techniques to reveal the temperature-sensitive residue-residue interactions driving allostery in TRPV3. We find that groups of residues exhibiting similar temperature-dependent contact frequency profiles cluster at specific regions of the channel. The dominant mode clusters on the ankyrin repeat domain and displays a linear melting trend while others display non-linear trends. These modes describe the residue-level temperature response patterns that underlie the channel's functional dynamics. With network analysis, we find that the community structure of the channel changes with temperature. And that a network of high centrality contacts connects distant regions of the protomer to the gate, serving as a means for the temperature-sensitive contact modes to allosterically regulate channel gating. Using a random forest model, we show that the contact states of specific temperature-sensitive modes are indeed predictive of the channel gate's state. Supporting the physical validity of these modes and networks are several residues identified with our analyses that are reported in literature to be functionally critical. Our results offer high resolution insight into thermo-TRP channel function and demonstrate the utility of temperature-sensitive contact analysis.

Temperature-Sensitive Contact Modes Allosterically Gate TRPV3

TRPV Ion channels are sophisticated molecular sensors designed to respond to distinct temperature thresholds. The recent surge in cryo-EM structures has provided numerous insights into the structural rearrangements accompanying their opening and closing; however, the molecular mechanisms by which TRPV channels establish precise and robust temperature sensing remain elusive. In this work we employ molecular simulations, multi-ensemble contact analysis, graph theory, and machine learning techniques to reveal the temperature-sensitive residue-residue interactions driving allostery in TRPV3. We find that groups of residues exhibiting similar temperature-dependent contact frequency profiles cluster at specific regions of the channel. The dominant mode clusters on the ankyrin repeat domain and displays a linear melting trend while others display non-linear trends. These modes describe the residue-level temperature response patterns that underlie the channel's functional dynamics. With network analysis, we find that the community structure of the channel changes with temperature. And that a network of high centrality contacts connects distant regions of the protomer to the gate, serving as a means for the temperature-sensitive contact modes to allosterically regulate channel gating. Using a random forest model, we show that the contact states of specific temperature-sensitive modes are indeed predictive of the channel gate's state. Supporting the physical validity of these modes and networks are several residues identified with our analyses that are reported in literature to be functionally critical. Our results offer high resolution insight into thermo-TRP channel function and demonstrate the utility of temperature-sensitive contact analysis.

Molecular dynamics simulations reveal the hidden EF-hand of EF-SAM as a possible key thermal sensor for STIM1 activation by temperature

Intracellular calcium signaling is essential for many cellular processes, including store-operated Ca2+ entry (SOCE), which is initiated by stromal interaction molecule 1 (STIM1) detecting endoplasmic reticulum (ER) Ca2+ depletion. STIM1 is also activated by temperature independent of ER Ca2+ depletion. Here we provide evidence, from advanced molecular dynamics simulations, that EF-SAM may act as a true temperature sensor for STIM1, with the prompt and extended unfolding of the hidden EF-hand subdomain (hEF) even at slightly elevated temperatures, exposing a highly conserved hydrophobic Phe108. Our study also suggests an interplay between Ca2+ and temperature sensing, as both, the canonical EF-hand subdomain (cEF) and the hidden EF-hand subdomain (hEF), exhibit much higher thermal stability in the Ca2+-loaded form compared to the Ca2+-free form. The SAM domain, surprisingly, displays high thermal stability compared to the EF-hands and may act as a stabilizer for the latter. We propose a modular architecture for the EF-hand-SAM domain of STIM1 composed of a thermal sensor (hEF), a Ca2+ sensor (cEF), and a stabilizing domain (SAM). Our findings provide important insights into the mechanism of temperature-dependent regulation of STIM1, which has broad implications for understanding the role of temperature in cellular physiology.

Toward a Molecular Mechanism of Complementary RNA Duplexes Denaturation

RNA duplexes are relatively rare but play very important biological roles. As an end-product of template-based RNA replication, they also have key implications for hypothetical primitive forms of life. Unless they are specifically separated by enzymes, these duplexes denature upon a temperature increase. However, mechanistic and kinetic aspects of RNA (and DNA) duplex thermal denaturation remain unclear at the microscopic level. We propose an in silico strategy that probes the thermal denaturation of RNA duplexes and allows for an extensive conformational space exploration along a wide temperature range with atomistic precision. We show that this approach first accounts for the strong sequence and length dependence of the duplexes melting temperature, reproducing the trends seen in the experiments and predicted by nearest-neighbor models. The simulations are then instrumental at providing a molecular picture of the temperature-induced strand separation. The textbook canonical "all-or-nothing" two-state model, very much inspired by the protein folding mechanism, can be nuanced. We demonstrate that a temperature increase leads to significantly distorted but stable structures with extensive base-fraying at the extremities, and that the fully formed duplexes typically do not form around melting. The duplex separation therefore appears as much more gradual than commonly thought.

Evolution of large Aβ16-22 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 β-rich aggregates of Y and elongated topologies predicted by coarse-grained simulations and consisting of more than 100 Aβ16-22 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 Aβ sequences.

Temperature-sensitive contacts in disordered loops tune enzyme I activity

Homologous enzymes with identical folds often exhibit different thermal and kinetic behaviors. Understanding how an enzyme sequence encodes catalytic activity at functionally optimal temperatures is a fundamental problem in biophysics. Recently it was shown that the residues that tune catalytic activities of thermophilic/mesophilic variants of the C-terminal domain of bacterial enzyme I (EIC) are largely localized within disordered loops, offering a model system with which to investigate this phenomenon. In this work, we use molecular dynamics simulations and mutagenesis experiments to reveal a mechanism of sequence-dependent activity tuning of EIC homologs. We find that a network of contacts in the catalytic loops is particularly sensitive to changes in temperature, with some contacts exhibiting distinct linear or nonlinear temperature-dependent trends. Moreover, these trends define structurally clustered dynamical modes and can distinguish regions that tend toward order or disorder at higher temperatures. Assaying several thermophilic EIC mutants, we show that complementary mesophilic mutations to the most temperature-sensitive positions exhibit the most enhanced activity, while mutations to relatively temperature insensitive positions exhibit the least enhanced activities. These results provide a mechanistic explanation of sequence-dependent temperature tuning and offer a computational method for rational enzyme modification.

Computer-aided comprehensive explorations of RNA structural polymorphism through complementary simulation methods

While RNA folding was originally seen as a simple problem to solve, it has been shown that the promiscuous interactions of the nucleobases result in structural polymorphism, with several competing structures generally observed for non-coding RNA. This inherent complexity limits our understanding of these molecules from experiments alone, and computational methods are commonly used to study RNA. Here, we discuss three advanced sampling schemes, namely Hamiltonian-replica exchange molecular dynamics (MD), ratchet-and-pawl MD and discrete path sampling, as well as the HiRE-RNA coarse-graining scheme, and highlight how these approaches are complementary with reference to recent case studies. While all computational methods have their shortcomings, the plurality of simulation methods leads to a better understanding of experimental findings and can inform and guide experimental work on RNA polymorphism.

Computational Insights into the Unfolding of a Destabilized Superoxide Dismutase 1 Mutant

In this work, we investigate the β-barrel of superoxide dismutase 1 (SOD1) in a mutated form, the isoleucine 35 to alanine (I35A) mutant, commonly used as a model system to decipher the role of the full-length apoSOD1 protein in amyotrophic lateral sclerosis (ALS). It is known from experiments that the mutation reduces the stability of the SOD1 barrel and makes it largely unfolded in the cell at 37 degrees Celsius. We deploy state-of-the-art computational machinery to examine the thermal destabilization of the I35A mutant by comparing two widely used force fields, Amber a99SB-disp and CHARMM36m. We find that only the latter force field, when combined with the Replica Exchange with Solute Scaling (REST2) approach, reproduces semi-quantitatively the experimentally observed shift in the melting between the original and the mutated SOD1 barrel. In addition, we analyze the unfolding process and the conformational landscape of the mutant, finding these largely similar to those of the wildtype. Nevertheless, we detect an increased presence of partially misfolded states at ambient temperatures. These states, featuring conformational changes in the region of the β-strands β4-β6, might provide a pathway for nonnative aggregation.

Structural basis for the hyperthermostability of an archaeal enzyme induced by succinimide formation

Stability of proteins from hyperthermophiles (organisms existing under boiling water conditions) enabled by a reduction of conformational flexibility is realized through various mechanisms. A succinimide (SNN) arising from the post-translational cyclization of the side chains of aspartyl/asparaginyl residues with the backbone amide -NH of the succeeding residue would restrain the torsion angle Ψ and can serve as a new route for hyperthermostability. However, such a succinimide is typically prone to hydrolysis, transforming to either an aspartyl or β-isoaspartyl residue. Here, we present the crystal structure of Methanocaldococcus jannaschii glutamine amidotransferase and, using enhanced sampling molecular dynamics simulations, address the mechanism of its increased thermostability, up to 100°C, imparted by an unexpectedly stable succinimidyl residue at position 109. The stability of SNN109 to hydrolysis is seen to arise from its electrostatic shielding by the side-chain carboxylate group of its succeeding residue Asp110, as well as through n → π^∗ interactions between SNN109 and its preceding residue Glu108, both of which prevent water access to SNN. The stable succinimidyl residue induces the formation of an α-turn structure involving 13-atom hydrogen bonding, which locks the local conformation, reducing protein flexibility. The destabilization of the protein upon replacement of SNN with a Φ-restricted prolyl residue highlights the specificity of the succinimidyl residue in imparting hyperthermostability to the enzyme. The conservation of the succinimide-forming tripeptide sequence (E(N/D)(E/D)) in several archaeal GATases strongly suggests an adaptation of this otherwise detrimental post-translational modification as a harbinger of thermostability.

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.

Specific Interactions and Environment Flexibility Tune Protein Stability under Extreme Crowding

Macromolecular crowding influences protein mobility and stability in vivo. A precise description of the crowding effect on protein thermal stability requires the estimate of the combined effects of excluded volume, specific protein-environment interactions, as well as the thermal response of the crowders. Here, we explore an ideal model system, the lysozyme protein in powder state, to dissect the factors controlling the melting of the protein under extreme crowding. By deploying state-of-the art molecular simulations, supported by calorimetric experiments, we assess the role of the environment flexibility and of intermolecular electrostatic interactions. In particular, we show that the temperature-dependent flexibility of the macromolecular crowders, along with specific interactions, significantly alleviates the stabilizing contributions of the static volume effect.

Stabilizing or Destabilizing: Simulations of Chymotrypsin Inhibitor 2 under Crowding Reveal Existence of a Crossover Temperature

The effect of macromolecular crowding on the stability of proteins can change with temperature. This dependence might reveal a delicate balance between two factors: the entropic excluded volume and the stability-modulating quinary interactions. Here we computationally investigate the thermal stability of the native state of chymotrypsin inhibitor 2 (CI2), which was previously shown by experiments to be destabilized by protein crowders at room temperature. Mimicking experimental conditions, our enhanced-sampling atomistic simulations of CI2 surrounded by lysozyme and bovine serum albumin reproduce this destabilization but also provide evidence of a crossover temperature above which lysozyme is found to become stabilizing, as previously predicted by analysis of thermodynamic data. We relate this crossover to the different CI2-crowder interactions and the local packing experienced by CI2. In fact, we clearly show that the pronounced stabilization induced by lysozyme at high temperatures stems from the tight local packing created around CI2 by this smaller crowder.

The Unfolding Journey of Superoxide Dismutase 1 Barrels under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions with Crowders

The thermal stability of the superoxide dismutase 1 protein in a crowded solution is investigated by performing enhanced sampling molecular simulations. By complementing thermal unfolding experiments done close to physiological conditions (200 mg/mL), we provide evidence that the presence of the protein crowder bovine serum albumin in different packing states has only a minor, and essentially destabilizing, effect. The finding that quinary interactions counteract the pure stabilization contribution stemming from excluded volume is rationalized here by exploring the SOD1 unfolding mechanism in microscopic detail. In agreement with recent experiments, we unveil the importance of intermediate unfolded states as well as the correlation between protein conformations and local packing with the crowders. This link helps us to elucidate why certain SOD1 mutations involved in the ALS disease reverse the stability effect of the intracellular environment.

Structural transitions in the RNA 7SK 5' hairpin and their effect on HEXIM binding

7SK RNA, as part of the 7SK ribonucleoprotein complex, is crucial to the regulation of transcription by RNA-polymerase II, via its interaction with the positive transcription elongation factor P-TEFb. The interaction is induced by binding of the protein HEXIM to the 5′ hairpin (HP1) of 7SK RNA. Four distinct structural models have been obtained experimentally for HP1. Here, we employ computational methods to investigate the relative stability of these structures, transitions between them, and the effects of mutations on the observed structural ensembles. We further analyse the results with respect to mutational binding assays, and hypothesize a mechanism for HEXIM binding. Our results indicate that the dominant structure in the wild type exhibits a triplet involving the unpaired nucleotide U40 and the base pair A43-U66 in the GAUC/GAUC repeat. This conformation leads to an open major groove with enough potential binding sites for peptide recognition. Sequence mutations of the RNA change the relative stability of the different structural ensembles. Binding affinity is consequently lost if these changes alter the dominant structure.

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.

Aggregation of disease-related peptides

Protein misfolding and aggregation of amyloid proteins is the fundamental cause of more than 20 diseases. Molecular mechanisms of the self-assembly and the formation of the toxic aggregates are still elusive. Computer simulations have been intensively used to study the aggregation of amyloid peptides of various amino acid lengths related to neurodegenerative diseases. We review atomistic and coarse-grained simulations of short amyloid peptides aimed at determining their transient oligomeric structures and the early and late aggregation steps.

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

The thermal resistance of two homolog enzymes is investigated, with an emphasis on their local stability and flexibility, and on the possible implications regarding their reactivity.

Residual Structures and Transient Long-Range Interactions of p53 Transactivation Domain: Assessment of Explicit Solvent Protein Force Fields

Molecular dynamics simulations using physics-based atomistic force fields have been increasingly used to characterize the heterogeneous structural ensembles of intrinsically disordered proteins (IDPs). To evaluate the accuracy of the latest atomistic explicit-solvent force fields in modeling larger IDPs with nontrivial structural features, we focus on the 61-residue N-terminal transactivation domain (TAD) of tumor suppressor p53, an important protein in cancer biology that has been extensively studied, and abundant experimental data is available for evaluation of simulated ensembles. We performed extensive replica exchange with solute tempering simulations, in excess of 1.0 μs/replica, to generate disordered structural ensembles of p53-TAD using six latest explicit solvent protein force fields. Multiple local and long-range structural properties, including chain dimension, residual secondary structures, and transient long-range contacts, were analyzed and compared against available experimental data. The results show that IDPs such as p53-TAD remain highly challenging for atomistic simulations due to conformational complexity and difficulty in achieving adequate convergence. Structural ensembles of p53-TAD generated using various force fields differ significantly from each other. The a99SB-disp force field demonstrates the best agreement with experimental data at all levels and proves to be suitable for simulating unbound p53-TAD and how its conformational properties may be modulated by phosphorylation and other cellular signals or cancer-associated mutations. Feasibility of such detailed structural characterization is a key step toward establishing the sequence-disordered ensemble-function-disease relationship of p53 and other biologically important IDPs.

Three Weaknesses for Three Perturbations: Comparing Protein Unfolding Under Shear, Force, and Thermal Stresses

The perturbation of a protein conformation by a physiological fluid flow is crucial in various biological processes including blood clotting and bacterial adhesion to human tissues. Investigating such mechanisms by computer simulations is thus of great interest, but it requires development of ad hoc strategies to mimic the complex hydrodynamic interactions acting on the protein from the surrounding flow. In this study, we apply the Lattice Boltzmann Molecular Dynamics (LBMD) technique built on the implicit solvent coarse-grained model for protein Optimized Potential for Efficient peptide structure Prediction (OPEP) and a mesoscopic representation of the fluid solvent, to simulate the unfolding of a small globular cold-shock protein in shear flow and to compare it to the unfolding mechanisms caused either by mechanical or thermal perturbations. We show that each perturbation probes a specific weakness of the protein and causes the disruption of the native fold along different unfolding pathways. Notably, the shear flow and the thermal unfolding exhibit very similar pathways, while because of the directionality of the perturbation, the unfolding under force is quite different. For force and thermal disruption of the native state, the coarse-grained simulations are compared to all-atom simulations in explicit solvent, showing an excellent agreement in the explored unfolding mechanisms. These findings encourage the use of LBMD based on the OPEP model to investigate how a flow can affect the function of larger proteins, for example, in catch-bond systems.

Communication: Self-assembly of a model supramolecular polymer studied by replica exchange with solute tempering

Conventional molecular-dynamics (cMD) simulation has a well-known limitation in accessible time and length scales, and thus various enhanced sampling techniques have been proposed to alleviate the problem. In this paper, we explore the utility of replica exchange with solute tempering (REST) (i.e., a variant of Hamiltonian replica exchange methods) to simulate the self-assembly of a supramolecular polymer in explicit solvent and compare the performance with temperature-based replica exchange MD (T-REMD) as well as cMD. As a test system, we consider a relatively simple all-atom model of supramolecular polymerization (namely, benzene-1,3,5-tricarboxamides in methylcyclohexane solvent). Our results show that both REST and T-REMD are able to predict highly ordered polymer structures with helical H-bonding patterns, in contrast to cMD which completely fails to obtain such a structure for the present model. At the same time, we have also experienced some technical challenge (i.e., aggregation-dispersion transition and the resulting bottleneck for replica traversal), which is illustrated numerically. Since the computational cost of REST scales more moderately than T-REMD, we expect that REST will be useful for studying the self-assembly of larger systems in solution with enhanced rearrangement of monomers.

Mechanics of Protein Adaptation to High Temperatures

Inspired by Somero's corresponding state principle that relates protein enhanced thermal stability with mechanical rigidity, we deployed state of the art computational techniques (based on atomistic steered molecular dynamics and Hamiltonian-replica exchange simulations) to study the in silico realization of mechanical and thermal unfolding of two homologous Csp proteins that have evolved to thrive in different thermal environments. By complementing recent single-molecule experiments, we unambiguously show that, for these homologues whose structures are very similar, the increased thermal resistance of the thermophilic variant is not associated with an increased mechanical stability. Our approach provides microscopic insights that are otherwise inaccessible to experimental techniques, and explains why the protein weak spots for thermal and mechanical denaturation are distinct.

Enhanced Sampling of Intrinsic Structural Heterogeneity of the BH3-Only Protein Binding Interface of Bcl-xL

Antiapoptotic Bcl-xL plays central roles in regulating programed cell death. Partial unfolding of Bcl-xL has been observed at the interface upon specific binding to the pro-apoptotic BH3-only protein PUMA, which in turn disrupts the interaction of Bcl-xL with tumor suppressor p53 and promotes apoptosis. Previous analysis of existing Bcl-xL structures and atomistic molecular dynamics (MD) simulations have suggested that substantial intrinsic structure heterogeneity exists at the BH3-only protein binding interface of Bcl-xL to facilitate its conformational transitions upon binding. In this study, enhanced sampling is applied to further characterize the interfacial conformations of unbound Bcl-xL in explicit solvent. Extensive replica exchange with solute tempering (REST) simulations, with a total accumulated time of 16 μs, were able to cover much wider conformational spaces for the interfacial region of Bcl-xL. The resulting structural ensembles are much better converged, with local and long-range structural features that are highly consistent with existing NMR data. These simulations further demonstrate that the BH3-only protein binding interface of Bcl-xL is intrinsically disordered and samples many rapidly interconverting conformations. Intriguingly, all previously observed conformers are well represented in the unbound structure ensemble. Such intrinsic structural heterogeneity and flexibility may be critical for Bcl-xL to undergo partial unfolding induced by PUMA binding, and likely provide a robust basis that allows Bcl-xL to respond sensitively to binding of various ligands in cellular signaling and regulation.

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.