Influence of denatured and intermediate states of folding on protein aggregation

Connecting Protein Millisecond Conformational Dynamics to Protein Thermal Stability

The stability of protein folded states is crucial for its function, yet the relationship with the protein sequence remains poorly understood. Prior studies have focused on the amino acid composition and thermodynamic couplings within a single folded conformation, overlooking the potential contribution of protein dynamics. Here, we address this gap by systematically analyzing the impact of alanine mutations in the C-terminal β-strand (β5) of ubiquitin, a model protein exhibiting millisecond timescale interconversion between two conformational states differing in the β5 position. Our findings unveil a negative correlation between millisecond dynamics and thermal stability, with alanine substitutions at seemingly flexible C-terminal residues significantly enhancing thermostability. Integrating spectroscopic and computational approaches, we demonstrate that the thermally unfolded state retains a substantial secondary structure but lacks β5 engagement, recapitulating the transition state for millisecond dynamics. Thus, alanine mutations that modulate the stabilities of the folded states with respect to the partially unfolded state impact both the dynamics and stability. Our findings underscore the importance of conformational dynamics with implications for protein engineering and design.

Macromolecular condensation buffers intracellular water potential

Optimum protein function and biochemical activity critically depends on water availability because solvent thermodynamics drive protein folding and macromolecular interactions1. Reciprocally, macromolecules restrict the movement of 'structured' water molecules within their hydration layers, reducing the available 'free' bulk solvent and therefore the total thermodynamic potential energy of water, or water potential. Here, within concentrated macromolecular solutions such as the cytosol, we found that modest changes in temperature greatly affect the water potential, and are counteracted by opposing changes in osmotic strength. This duality of temperature and osmotic strength enables simple manipulations of solvent thermodynamics to prevent cell death after extreme cold or heat shock. Physiologically, cells must sustain their activity against fluctuating temperature, pressure and osmotic strength, which impact water availability within seconds. Yet, established mechanisms of water homeostasis act over much slower timescales2,3; we therefore postulated the existence of a rapid compensatory response. We find that this function is performed by water potential-driven changes in macromolecular assembly, particularly biomolecular condensation of intrinsically disordered proteins. The formation and dissolution of biomolecular condensates liberates and captures free water, respectively, quickly counteracting thermal or osmotic perturbations of water potential, which is consequently robustly buffered in the cytoplasm. Our results indicate that biomolecular condensation constitutes an intrinsic biophysical feedback response that rapidly compensates for intracellular osmotic and thermal fluctuations. We suggest that preserving water availability within the concentrated cytosol is an overlooked evolutionary driver of protein (dis)order and function.

The denatured state of HIV-1 protease under native conditions

The denatured state of several proteins has been shown to display transient structures that are relevant for folding, stability, and aggregation. To detect them by nuclear magnetic resonance (NMR) spectroscopy, the denatured state must be stabilized by chemical agents or changes in temperature. This makes the environment different from that experienced in biologically relevant processes. Using high‐resolution heteronuclear NMR spectroscopy, we have characterized several denatured states of a monomeric variant of HIV‐1 protease, which is natively structured in water, induced by different concentrations of urea, guanidinium chloride, and acetic acid. We have extrapolated the chemical shifts and the relaxation parameters to the denaturant‐free denatured state at native conditions, showing that they converge to the same values. Subsequently, we characterized the conformational properties of this biologically relevant denatured state under native conditions by advanced molecular dynamics simulations and validated the results by comparison to experimental data. We show that the denatured state of HIV‐1 protease under native conditions displays rich patterns of transient native and non‐native structures, which could be of relevance to its guidance through a complex folding process.

Interaction of a Model Hydrophobic Drug Dimethylcurcumin with Albumin Nanoparticles

The aim of present study was to investigate the binding interactions of a model hydrophobic molecule, dimethylcurcumin (DMC) with nanoparticle form of bovine serum albumin (BSA) using fluorescence spectroscopy techniques. For this, BSA nanoparticles (size = 62.0 ± 3.5 nm, molecular weight = 11,243 ± 3445 kD) prepared by thermal denaturation method was mixed with DMC in solution and monitored for fluorescence emission of tryptophan (Trp) residue as well as DMC separately. The emission maximum of DMC in nanoparticles form exhibited more blue sift and quenched the excited state of tryptophan (Trp) by six fold higher than in the native form of BSA. By analyzing Trp fluorescence, the mean binding constant (K) estimated for the interaction of DMC with native and nanoparticles forms of BSA was 2.7 ± 0.4 × 10⁴ M^-1 and 1.5 ± 0.5 × 10⁵ M^-1 respectively. Together these results suggested that DMC experienced a more rigid environment in nanoparticles than in native form of BSA. Additionally the above determined K values were in agreement with those reported previously by absorption techniques. Further direct energy transfer was observed between Trp and DMC, using which the distance (r) calculated between them was 28.25 ± 0.27 Ǻ in BSA native. Similar analysis involving BSA nanoparticle and DMC revealed a distance of 24.25 ± 1.05 Ǻ between the hydrophobic core and the ligand. Finally interaction of DMC with BSA was validated through molecular docking studies, which indicated sub-domain IIA as the binding site of DMC. Thus it is concluded that intrinsic fluorescence of protein can be utilized to study the interaction of its different physical forms with any hydrophobic ligand.

Mechanism of Nucleation and Growth of Aβ40 Fibrils from All-Atom and Coarse-Grained Simulations

In this work, we characterize the nucleation and elongation mechanisms of the "diseased" polymorph of the amyloid-β 40 (Aβ40) fibril using an off-lattice coarse-grained (CG) protein model. After determining the nucleation size and subsequent stable protofibrillar structure from the CG model, validated with all-atom simulations, we consider the "lock and dock" and "activated monomer" fibril elongation mechanisms for the protofibril by statistical additions of a monomer drawn from four different ensembles of the free Aβ40 peptide to grow the fibril. Our CG model shows that the dominant mechanism for fibril elongation is the lock and dock mechanism across all monomer ensembles, even when the monomer is in the activated form. Although our CG model finds no thermodynamic difference between the two fibril elongation mechanisms, the activated monomer is found to be kinetically faster by a factor of 2 for the "locking" step compared with all other structured or unstructured monomer ensembles.

The effect of chirality and steric hindrance on intrinsic backbone conformational propensities: tools for protein design

The conformational propensities of amino acids are an amalgamation of sequence effects, environmental effects and underlying intrinsic behavior. Many have attempted to investigate neighboring residue effects to aid in our understanding of protein folding and improve structure prediction efforts, especially with respect to difficult to characterize states, such as disordered or unfolded states. Host-guest peptide series are a useful tool in examining the propensities of the amino acids free from the surrounding protein structure. Here, we compare the distributions of the backbone dihedral angles (φ/ψ) of the 20 proteogenic amino acids in two different sequence contexts using the AAXAA and GGXGG host-guest pentapeptide series. We further examine their intrinsic behaviors across three environmental contexts: water at 298 K, water at 498 K, and 8 M urea at 298 K. The GGXGG systems provide the intrinsic amino acid propensities devoid of any conformational context. The alanine residues in the AAXAA series enforce backbone chirality, thereby providing a model of the intrinsic behavior of amino acids in a protein chain. Our results show modest differences in φ/ψ distributions due to the steric constraints of the Ala side chains, the magnitudes of which are dependent on the denaturing conditions. One of the strongest factors modulating φ/ψ distributions was the protonation of titratable side chains, and the largest differences observed were in the amino acid propensities for the rarely sampled αL region.

Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches

Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a protein’s folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the G_A all-α and G_B α+β folds is extensively characterized; but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between G_A and G_B. In agreement with experiment, we observe conformational switching from G_A to G_B upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp G_A/G_B switch may arise from the orientation dependence of aromatic π-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches.

The biological functions of globular proteins are intimately related to their folded structures and their associated conformational fluctuations. Evolution of new structures is an important avenue to new functions. Although many mutations do not change the folded state, experiments indicate that a single amino acid substitution can lead to a drastic change in the folded structure. The physics of this switch-like behavior remains to be elucidated. Here we develop a computational model for the relevant physical forces, showing that mutations can lead to new folds by passing through intermediate sequences where the old and new folds occur with varying probabilities. Our approach helps provide a general physical account of conformational switching in evolution and mutational effects on conformational dynamics.

Transient β-hairpin formation in α-synuclein monomer revealed by coarse-grained molecular dynamics simulation

Parkinson's disease, originating from the intrinsically disordered peptide α-synuclein, is a common neurodegenerative disorder that affects more than 5% of the population above age 85. It remains unclear how α-synuclein monomers undergo conformational changes leading to aggregation and formation of fibrils characteristic for the disease. In the present study, we perform molecular dynamics simulations (over 180 μs in aggregated time) using a hybrid-resolution model, Proteins with Atomic details in Coarse-grained Environment (PACE), to characterize in atomic detail structural ensembles of wild type and mutant monomeric α-synuclein in aqueous solution. The simulations reproduce structural properties of α-synuclein characterized in experiments, such as secondary structure content, long-range contacts, chemical shifts, and (3)J(HNHCα )-coupling constants. Most notably, the simulations reveal that a short fragment encompassing region 38-53, adjacent to the non-amyloid-β component region, exhibits a high probability of forming a β-hairpin; this fragment, when isolated from the remainder of α-synuclein, fluctuates frequently into its β-hairpin conformation. Two disease-prone mutations, namely, A30P and A53T, significantly accelerate the formation of a β-hairpin in the stated fragment. We conclude that the formation of a β-hairpin in region 38-53 is a key event during α-synuclein aggregation. We predict further that the G47V mutation impedes the formation of a turn in the β-hairpin and slows down β-hairpin formation, thereby retarding α-synuclein aggregation.

Catalase-only nanoparticles prepared by shear alone: Characteristics, activity and stability evaluation

Catalase is a promising therapeutic enzyme; however, it carries risks of inactivation and rapid degradation when it is used in practical bioprocess, such as delivery in vivo. To overcome the issue, we made catalase-only nanoparticles using shear stress alone at a moderate shear rate of 217s(-1) in a coaxial cylinder flow cell. Properties of nanoparticles, including particle size, polydispersity index and zeta potential, were characterized. The conformational changes of pre- and post-sheared catalase were determined using spectroscopy techniques. The results indicated that the conformational changes of catalase and reduction in α-helical content caused by shear alone were less significant than that by desolvation method. Catalase-only nanoparticles prepared by single shear retained over 90% of its initial activity when compared with the native catalase. Catalase nanoparticles lost only 20% of the activity when stored in phosphate buffer solution for 72h at 4°C, whereas native catalase lost 53% under the same condition. Especially, the activity of nanogranulated catalase was decreased only slightly in the simulated intestinal fluid containing α-chymotrypsin during 4h incubation at 37°C, implying that the catalase nanoparticle was more resistant to the degradation of proteases than native catalase molecules. Overall, catalase-only nanoparticles offered a great potential to stabilize enzymes for various pharmaceutical applications.

Surface properties of heat-induced soluble soy protein aggregates of different molecular masses

Suspensions (2% and 5%, w/v) of soy protein isolate (SPI) were heated at 80, 90, or 100 °C for different time periods to produce soluble aggregates of different molecular sizes to investigate the relationship between particle size and surface properties (emulsions and foams). Soluble aggregates generated in these model systems were characterized by gel permeation chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Heat treatment increased surface hydrophobicity, induced SPI aggregation via hydrophobic interaction and disulfide bonds, and formed soluble aggregates of different sizes. Heating of 5% SPI always promoted large-size aggregate (LA; >1000 kDa) formation irrespective of temperature, whereas the aggregate size distribution in 2% SPI was temperature dependent: the LA fraction progressively rose with temperature (80→90→100 °C), corresponding to the attenuation of medium-size aggregates (MA; 670 to 1000 kDa) initially abundant at 80 °C. Heated SPI with abundant LA (>50%) promoted foam stability. LA also exhibited excellent emulsifying activity and stabilized emulsions by promoting the formation of small oil droplets covered with a thick interfacial protein layer. However, despite a similar influence on emulsion stability, MA enhanced foaming capacity but were less capable of stabilizing emulsions than LA. The functionality variation between heated SPI samples is clearly related to the distribution of aggregates that differ in molecular size and surface activity. The findings may encourage further research to develop functional SPI aggregates for various commercial applications.

Evolution of the potential energy landscape with static pulling force for two model proteins

The energy landscape is analyzed for off-lattice bead models of protein L and protein G as a function of a static pulling force. Two different pairs of attachment points (pulling directions) are compared in each case, namely, residues 1/56 and 10/32. For the terminal residue pulling direction 1/56, the distinct global minimum structures are all extended, aside from the compact geometry that correlates with zero force. The helical turns finally disappear at the highest pulling forces considered. For the 10/32 pulling direction, the changes are more complicated, with a variety of competing arrangements for beads outside the region where the force is directly applied. These alternatives produce frustrated energy landscapes, with low-lying minima separated by high barriers. The calculated folding pathways in the absence of force are in good agreement with previous work. The N-terminal hairpin folds first for protein L and the C-terminal hairpin for protein G, which exhibits an intermediate. However, for a relatively low static force, where the global minimum retains its structure, the folding mechanisms change, sometimes dramatically, depending on the protein and the attachment points. The scaling relations predicted by catastrophe theory are found to hold in the limit of short path lengths.

Accurate prediction of protein folding rates from sequence and sequence-derived residue flexibility and solvent accessibility

Protein folding rates vary by several orders of magnitude and they depend on the topology of the fold and the size and composition of the sequence. Although recent works show that the rates can be predicted from the sequence, allowing for high-throughput annotations, they consider only the sequence and its predicted secondary structure. We propose a novel sequence-based predictor, PFR-AF, which utilizes solvent accessibility and residue flexibility predicted from the sequence, to improve predictions and provide insights into the folding process. The predictor includes three linear regressions for proteins with two-state, multistate, and unknown (mixed-state) folding kinetics. PFR-AF on average outperforms current methods when tested on three datasets. The proposed approach provides high-quality predictions in the absence of similarity between the predicted and the training sequences. The PFR-AF's predictions are characterized by high (between 0.71 and 0.95, depending on the dataset) correlation and the lowest (between 0.75 and 0.9) mean absolute errors with respect to the experimental rates, as measured using out-of-sample tests. Our models reveal that for the two-state chains inclusion of solvent-exposed Ala may accelerate the folding, while increased content of Ile may reduce the folding speed. We also demonstrate that increased flexibility of coils facilitates faster folding and that proteins with larger content of solvent-exposed strands may fold at a slower pace. The increased flexibility of the solvent-exposed residues is shown to elongate folding, which also holds, with a lower correlation, for buried residues. Two case studies are included to support our findings.

An implicit solvent coarse-grained lipid model with correct stress profile

We develop a coarse-grained parametrization strategy for lipid membranes that we illustrate for a dipalmitoylphosphatidylcholine bilayer. Our coarse-graining approach eliminates the high cost of explicit solvent but maintains more lipid interaction sites. We use a broad attractive tail-tail potential and extract realistic bonded potentials of mean force from all-atom simulations, resulting in a model with a sharp gel to fluid transition, a correct bending modulus, and overall very reasonable dynamics when compared with experiment. We also determine a quantitative stress profile and correct breakdown of contributions from lipid components when compared with detailed all-atom simulation benchmarks, which has been difficult to achieve for implicit membrane models. Such a coarse-grained lipid model will be necessary for efficiently simulating complex constructs of the membrane, such as protein assembly and lipid raft formation, within these nonaqueous chemical environments.

Insights Into Crowding Effects on Protein Stability From a Coarse-Grained Model

Proteins aggregate and precipitate from high concentration solutions in a wide variety of problems of natural and technological interest. Consequently, there is a broad interest in developing new ways to model the thermodynamic and kinetic aspects of protein stability in these crowded cellular or solution environments. We use a coarse-grained modeling approach to study the effects of different crowding agents on the conformational equilibria of proteins and the thermodynamic phase behavior of their solutions. At low to moderate protein concentrations, we find that crowding species can either stabilize or destabilize the native state, depending on the strength of their attractive interaction with the proteins. At high protein concentrations, crowders tend to stabilize the native state due to excluded volume effects, irrespective of the strength of the crowder-protein attraction. Crowding agents reduce the tendency of protein solutions to undergo a liquid-liquid phase separation driven by strong protein-protein attractions. The aforementioned equilibrium trends represent, to our knowledge, the first simulation predictions for how the properties of crowding species impact the global thermodynamic stability of proteins and their solutions.

Contrasting disease and nondisease protein aggregation by molecular simulation

[Figurre: see text]. Protein aggregation can be defined as the sacrifice of stabilizing intrachain contacts of the functional state that are replaced with interchain contacts to form non-functional states. The resulting aggregate morphologies range from amorphous structures without long-range order typical of nondisease proteins involved in inclusion bodies to highly structured fibril assemblies typical of amyloid disease proteins. In this Account, we describe the development and application of computational models for the investigation of nondisease and disease protein aggregation as illustrated for the proteins L and G and the Alzheimer's Abeta systems. In each case, we validate the models against relevant experimental observables and then expand on the experimental window to better elucidate the link between molecular properties and aggregation outcomes. Our studies show that each class of protein exhibits distinct aggregation mechanisms that are dependent on protein sequence, protein concentration, and solution conditions. Nondisease proteins can have native structural elements in the denatured state ensemble or rapidly form early folding intermediates, which offers avenues of protection against aggregation even at relatively high concentrations. The possibility that early folding intermediates may be evolutionarily selected for their protective role against unwanted aggregation could be a useful strategy for reengineering sequences to slow aggregation and increase folding yield in industrial protein production. The observed oligomeric aggregates that we see for nondisease proteins L and G may represent the nuclei for larger aggregates, not just for large amorphous inclusion bodies, but potentially as the seeds of ordered fibrillar aggregates, since most nondisease proteins can form amyloid fibrils under conditions that destabilize the native state. By contrast, amyloidogenic protein sequences such as Abeta 1-40,42 and the familial Alzheimer's disease (FAD) mutants favor aggregation into ordered fibrils once the free-energy barrier for forming a critical nucleus is crossed. However, the structural characteristics and oligomer size of the soluble nucleation species have yet to be determined experimentally for any disease peptide sequence, and the molecular mechanism of polymerization that eventually delineates a mature fibril is unknown. This is in part due to the limited experimental access to very low peptide concentrations that are required to characterize these early aggregation events, providing an opportunity for theoretical studies to bridge the gap between the monomer and fibril end points and to develop testable hypotheses. Our model shows that Abeta 1-40 requires as few as 6-10 monomer chains (depending on sequence) to begin manifesting the cross-beta order that is a signature of formation of amyloid filaments or fibrils assessed in dye-binding kinetic assays. The richness of the oligomeric structures and viable filament and fibril polymorphs that we observe may offer structural clues to disease virulence variations that are seen for the WT and hereditary mutants.

A coarse-grained alpha-carbon protein model with anisotropic hydrogen-bonding

We develop a sequence based alpha-carbon model to incorporate a mean field estimate of the orientation dependence of the polypeptide chain that gives rise to specific hydrogen bond pairing to stabilize alpha-helices and beta-sheets. We illustrate the success of the new protein model in capturing thermodynamic measures and folding mechanism of proteins L and G. Compared to our previous coarse-grained model, the new model shows greater folding cooperativity and improvements in designability of protein sequences, as well as predicting correct trends for kinetic rates and mechanism for proteins L and G. We believe the model is broadly applicable to other protein folding and protein-protein co-assembly processes, and does not require experimental input beyond the topology description of the native state. Even without tertiary topology information, it can also serve as a mid-resolution protein model for more exhaustive conformational search strategies that can bridge back down to atomic descriptions of the polypeptide chain.

Protofibril assemblies of the arctic, Dutch, and Flemish mutants of the Alzheimer's Abeta1-40 peptide

Using a coarse-grained model of the Abeta peptide, we analyze the Arctic (E22G), Dutch (E22Q), and Flemish (A21G) familial Alzheimer's disease (FAD) mutants for any changes in the stability of amyloid assemblies with respect to the wild-type (WT) sequence. Based on a structural reference state of two protofilaments aligned to create the "agitated" protofibril as determined by solid-state NMR, we determine free energy trends for Abeta assemblies for the WT and FAD familial sequences. We find that the structural characteristics and oligomer size of the critical nucleus vary dramatically among the hereditary mutants. The Arctic mutant's disorder in the turn region introduces new stabilizing interactions that better align the two protofilaments, yielding a well-defined protofibril axis at relatively small oligomer sizes with respect to WT. By contrast, the critical nucleus for the Flemish mutant is beyond the 20 chains characterized in this study, thereby showing a strong shift in the equilibrium toward monomers with respect to larger protofibril assemblies. The Dutch mutant forms more ordered protofilaments than WT, but exhibits greater disorder in protofibril structure that includes an alternative polymorph of the WT fibril. An important conclusion of this work is that the Dutch mutant does not support the agitated protofibril assembly. We discuss the implications of the structural ensembles and free energy profiles for the FAD mutants in regards to interpretation of the kinetics of fibril assembly using chromatography and dye-binding experiments.

From coarse-grain to all-atom: Toward multiscale analysis of protein landscapes

Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biologically relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolutions. We present a method that efficiently generates realistic all-atom protein structures starting from the C(alpha) atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calculated using the coarse-grain structures versus the all-atom structures shows good correspondence and little distortion in the protein folding landscape.

Structural and Pathway Complexity of β-Strand Reorganization within Aggregates of Human Transthyretin(105−115) Peptide

Interstrand conformational rearrangements of human transthyretin peptide (TTR(105-115)) within dimeric aggregates were simulated by means of molecular dynamics (MD) with implicit solvation model for a total length of 48 micros. The conformations sampled in the MD simulations were clustered to identify free energy minima without any projections of free energy surface. A connected graph was constructed with nodes (=clusters) and edges corresponding to free energy minima and transitions between nodes, respectively. This connected graph which reflects the complexity of the free energy surface was used to extract the transition disconnectivity graph, which reflects the overall free energy barriers between pairs of free energy minima but does not contain information on transition paths. The routes of transitions between important free energy minima were obtained by further processing the original graph and the MD data. We have found that both parallel and antiparallel aggregates are populated. The parallel aggregates with different alignment patterns are separated by nonnegligible free energy barriers. Multiroutes exist in the interstrand conformational reorganization. Most visited routes do not dominant the kinetics, while less visited routes contribute a little each but they are numerous and their total contributions are actually dominant. There are various kinds of reptation motions, including those through a beta-bulge, side-chain aided reptation, and flipping or rotation of a hairpin formed by one strand.

Protein aggregation in silico

Protein aggregation is a challenge to the successful manufacture of protein therapeutics; it can impose severe limitations on purification yields and compromise formulation stability. Advances in computer power, and the wealth of computational studies pertaining to protein folding, have facilitated the development of molecular simulation as a tool to investigate protein misfolding and aggregation. Here, we highlight the successes of protein aggregation studies carried out in silico, with a particular emphasis on studies related to biotechnology. To conclude, we discuss future prospects for the field, and identify several biotechnology-related problems that would benefit from molecular simulation.

A lattice protein with an amyloidogenic latent state: stability and folding kinetics

We have designed a model lattice protein that has two stable folded states, the lower free energy native state and a latent state of somewhat higher energy. The two states have a sizable part of their structures in common (two "alpha-helices") and differ in the content of "alpha-helices" and "beta-strands" in the rest of their structures; i.e. for the native state, this part is alpha-helical, and for the latent state it is composed of beta-strands. Thus, the lattice protein free energy surface mimics that of amyloidogenic proteins that form well organized fibrils under appropriate conditions. A Go-like potential was used and the folding process was simulated with a Monte Carlo method. To gain insight into the equilibrium free energy surface and the folding kinetics, we have combined standard approaches (reduced free energy surfaces, contact maps, time-dependent populations of the characteristic states, and folding time distributions) with a new approach. The latter is based on a principal coordinate analysis of the entire set of contacts, which makes possible the introduction of unbiased reaction coordinates and the construction of a kinetic network for the folding process. The system is found to have four characteristic basins, namely a semicompact globule, an on-pathway intermediate (the bifurcation basin), and the native and latent states. The bifurcation basin is shallow and consists of the structure common to the native and latent states, with the rest disorganized. On the basis of the simulation results, a simple kinetic model describing the transitions between the characteristic states was developed, and the rate constants for the essential transitions were estimated. During the folding process the system dwells in the bifurcation basin for a relatively short time before it proceeds to the native or latent state. We suggest that such a bifurcation may occur generally for proteins in which native and latent states have a sizable part of their structures in common. Moreover, there is the possibility of introducing changes in the system (e.g., mutations), which guide the system toward the native or misfolded state.

Structure and dynamics of parallel beta-sheets, hydrophobic core, and loops in Alzheimer's A beta fibrils

We explore the relative contributions of different structural elements to the stability of Abeta fibrils by molecular-dynamics simulations performed over a broad range of temperatures (298 K to 398 K). Our fibril structures are based on solid-state nuclear magnetic resonance experiments of Abeta(1-40) peptides, with sheets of parallel beta-strands connected by loops and stabilized by interior salt bridges. We consider models with different interpeptide interfaces, and different staggering of the N- and C-terminal beta-strands along the fibril axis. Multiple 10-20 ns molecular-dynamics simulations show that fibril segments with 12 peptides are stable at ambient temperature. The different models converge toward an interdigitated side-chain packing, and present water channels solvating the interior D23/K28 salt bridges. At elevated temperatures, we observe the early phases of fibril dissociation as a loss of order in the hydrophilic loops connecting the two beta-strands, and in the solvent-exposed N-terminal beta-sheets. As the most dramatic structural change, we observe collective sliding of the N- and C-terminal beta-sheets on top of each other. The interior C-terminal beta-sheets in the hydrophobic core remain largely intact, indicating that their formation and stability is crucial to the dissociation/elongation and stability of Abeta fibrils.

Determining the critical nucleus and mechanism of fibril elongation of the Alzheimer's Abeta(1-40) peptide

We use a coarse-grained protein model to characterize the critical nucleus, structural stability, and fibril elongation propensity of Abeta(1-40) oligomers for the C(2x) and C(2z) quaternary forms proposed by solid-state NMR. By estimating equilibrium populations of structurally stable and unstable protofibrils, we determine the shift in the dominant population from free monomer to ordered fibril at a critical nucleus of ten chains for the C(2x) and C(2z) forms. We find that a minimum assembly of 16 monomer chains is necessary to mimic a mature fibril, and show that its structural stability correlates with a plateau in the hydrophobic residue density and a decrease in the likelihood of losing hydrophobic interactions by rotating the fibril subunits. While Abeta(1-40) protofibrils show similar structural stability for both C(2x) and C(2z) quaternary structures, we find that the fibril elongation propensity is greater for the C(2z) form relative to the C(2x) form. We attribute the increased propensity for elongation of the C(2z) form as being due to a stagger in the interdigitation of the N-terminal and C-terminal beta-strands, resulting in structural asymmetry in the presented fibril ends that decreases the amount of incorrect addition to the N terminus on one end. We show that because different combinations of stagger and quaternary structure affect the structural symmetry of the fibril end, we propose that differences in quaternary structures will affect directional growth patterns and possibly different morphologies in the mature fiber.

Kinetic studies of protein L aggregation and disaggregation

We have investigated the aggregation of protein L in 25% (vol/vol) TFE and 10 mM HCl. Under both conditions, aggregates adopt a fibrillar structure and bind dyes Congo Red and Thioflavin T consistent with the presence of amyloid fibrils. The kinetics of aggregation in 25% TFE suggest a linear-elongation mechanism with critical nucleus size of either two or three monomers. Aggregation kinetics in 10 mM HCl show a prolonged lag phase prior to a rapid increase in aggregation. The lag phase is time-dependent, but the time dependence can be eliminated by the addition of pre-formed seeds. Disaggregation studies show that for aggregates formed in TFE, aggregate stability is a strong function of aggregate age. For example, after 200 min of aggregation, 40% of the aggregation reaction is irreversible, while after 3 days over 60% is irreversible. When the final concentration of the denaturant, TFE, is reduced from 5% to 0, the amount of reversible aggregation doubles. Disaggregation studies of aggregates formed in TFE and 10 mM HCl reveal a complicated effect of pH on aggregate stability.

Effect of single-point sequence alterations on the aggregation propensity of a model protein

Sequences of contemporary proteins are believed to have evolved through a process that optimized their overall fitness, including their resistance to deleterious aggregation. Biotechnological processing may expose therapeutic proteins to conditions that are much more conducive to aggregation than those encountered in a cellular environment. An important task of protein engineering is to identify alternative sequences that would protect proteins when processed at high concentrations without altering their native structure associated with specific biological function. Our computational studies exploit parallel tempering simulations of coarse-grained model proteins to demonstrate that isolated amino acid residue substitutions can result in significant changes in the aggregation resistance of the protein in a crowded environment while retaining protein structure in isolation. A thermodynamic analysis of protein clusters subject to competing processes of folding and association shows that moderate mutations can produce effects similar to those caused by changes in system conditions, including temperature, concentration, and solvent composition, that affect the aggregation propensity. The range of conditions where a protein can resist aggregation can therefore be tuned by sequence alterations, although the protein generally may retain its generic ability for aggregation.

Coarse-grained strategy for modeling protein stability in concentrated solutions. II: phase behavior

We use highly efficient transition-matrix Monte Carlo simulations to determine equilibrium unfolding curves and fluid phase boundaries for solutions of coarse-grained globular proteins. The model we analyze derives the intrinsic stability of the native state and protein-protein interactions from basic information about protein sequence using heteropolymer collapse theory. It predicts that solutions of low hydrophobicity proteins generally exhibit a single liquid phase near their midpoint temperatures for unfolding, while solutions of proteins with high sequence hydrophobicity display the type of temperature-inverted, liquid-liquid transition associated with aggregation processes of proteins and other amphiphilic molecules. The phase transition occurring in solutions of the most hydrophobic protein we study extends below the unfolding curve, creating an immiscibility gap between a dilute, mostly native phase and a concentrated, mostly denatured phase. The results are qualitatively consistent with the solution behavior of hemoglobin (HbA) and its sickle variant (HbS), and they suggest that a liquid-liquid transition resulting in significant protein denaturation should generally be expected on the phase diagram of high-hydrophobicity protein solutions. The concentration fluctuations associated with this transition could be a driving force for the nonnative aggregation that can occur below the midpoint temperature.

Molecular simulation of protein aggregation

Computer simulation offers unique possibilities for investigating molecular-level phenomena difficult to probe experimentally. Drawing from a wealth of studies concerning protein folding, computational studies of protein aggregation are emerging. These studies have been successful in capturing aspects of aggregation known from experiment and are being used to refine experimental methods aimed at abating aggregation. Here we review molecular-simulation studies of protein aggregation conducted in our laboratory. Specific attention is devoted to issues with implications for biotechnology.

Protein folding by distributed computing and the denatured state ensemble

The distributed computing (DC) paradigm in conjunction with the folding@home (FH) client server has been used to study the folding kinetics of small peptides and proteins, giving excellent agreement with experimentally measured folding rates, although pathways sampled in these simulations are not always consistent with the folding mechanism. In this study, we use a coarse-grain model of protein L, whose two-state kinetics have been characterized in detail by using long-time equilibrium simulations, to rigorously test a FH protocol using approximately 10,000 short-time, uncoupled folding simulations starting from an extended state of the protein. We show that the FH results give non-Poisson distributions and early folding events that are unphysical, whereas longer folding events experience a correct barrier to folding but are not representative of the equilibrium folding ensemble. Using short-time, uncoupled folding simulations started from an equilibrated denatured state ensemble (DSE), we also do not get agreement with the equilibrium two-state kinetics because of overrepresented folding events arising from higher energy subpopulations in the DSE. The DC approach using uncoupled short trajectories can make contact with traditionally measured experimental rates and folding mechanism when starting from an equilibrated DSE, when the simulation time is long enough to sample the lowest energy states of the unfolded basin and the simulated free-energy surface is correct. However, the DC paradigm, together with faster time-resolved and single-molecule experiments, can also reveal the breakdown in the two-state approximation due to observation of folding events from higher energy subpopulations in the DSE.

Effects of frustration, confinement, and surface interactions on the dimerization of an off-lattice β-barrel protein

We study the effects of confinement, sequence frustration, and surface interactions on the thermodynamics of dimerization of an off-lattice minimalist beta-barrel protein using replica exchange molecular dynamics. We vary the degree of frustration of the protein by tuning the specificity of the hydrophobic interactions and investigate dimerization in confining spheres of different radii. We also investigate surface effects by tethering the first residue of one of the proteins to a uniformly repulsive surface. We find that increasing the confinement and frustration stabilize the dimer, while adding a repulsive surface decreases its stability. Different ensembles of structures, including properly dimerized and various partially dimerized states, are observed at the association transition temperature T(a), depending on the amount of frustration and whether a surface is present. The presence of a surface is predicted to alter the morphology of larger aggregates formed from partially unfolded dimeric conformations.

Protein-folding landscapes in multichain systems

Computational studies of proteins have significantly improved our understanding of protein folding. These studies are normally carried out by using chains in isolation. However, in many systems of practical interest, proteins fold in the presence of other molecules. To obtain insight into folding in such situations, we compare the thermodynamics of folding for a Miyazawa-Jernigan model 64-mer in isolation to results obtained in the presence of additional chains. The melting temperature falls as the chain concentration increases. In multichain systems, free-energy landscapes for folding show an increased preference for misfolded states. Misfolding is accompanied by an increase in interprotein interactions; however, near the folding temperature, the transition from folded chains to misfolded and associated chains is entropically driven. A majority of the most probable interprotein contacts are also native contacts, suggesting that native topology plays a role in early stages of aggregation.