Thermodynamics of model prions and its implications for the problem of prion protein folding

Advances in the understanding of protein misfolding and aggregation through molecular dynamics simulation

Aberrant protein folding known as protein misfolding is counted as one of the striking factors of neurodegenerative diseases. The extensive range of pathologies caused by protein misfolding, aggregation and subsequent accumulation are mainly classified into either gain of function diseases or loss of function diseases. In order to seek for novel strategies for treatment and diagnosis of neurodegenerative diseases, insights into the mechanism of misfolding and aggregation is essential. A comprehensive knowledge on the factors influencing misfolding and aggregation is required as well. An extensive experimental study on protein aggregation is somewhat challenging due to the insoluble and noncrystalline nature of amyloid fibrils. Thus there has been a growing use of computational approaches including Monte Carlo simulation, docking simulation, molecular dynamics simulation in the study of protein misfolding and aggregation. The review presents a discussion on molecular dynamics simulation alone as to how it has emerged as a promising tool in the understanding of protein misfolding and aggregation in general, detailing upon three different aspects considering four misfold prone proteins in particular. It is noticeable that all four proteins considered in this review i.e prion, superoxide dismutase1, huntingtin and amyloid β are linked to chronic neurodegenerative diseases with debilitating effects. Initially the review elaborates on the factors influencing the misfolding and aggregation. Next, it addresses our current understanding of the amyloid structures and the associated aggregation mechanisms, finally, summarizing the contribution of this computational tool in the search for therapeutic strategies against the respective protein-deposition diseases.

The Protein Folding Problem: The Role of Theory

The protein folding problem was first articulated as question of how order arose from disorder in proteins: How did the various native structures of proteins arise from interatomic driving forces encoded within their amino acid sequences, and how did they fold so fast? These matters have now been largely resolved by theory and statistical mechanics combined with experiments. There are general principles. Chain randomness is overcome by solvation-based codes. And in the needle-in-a-haystack metaphor, native states are found efficiently because protein haystacks (conformational ensembles) are funnel-shaped. Order-disorder theory has now grown to encompass a large swath of protein physical science across biology.

Sequence-dependent dynamical instability of the human prion protein: a comparative simulation study

The present study aimed to explore the most probable regions of the human prion protein backbone for which the initial steps of conformational transitions as a result of intrinsic and extrinsic perturbing factors on the protein structure can be assigned. A total of 0.3-μs molecular dynamics simulations on several analog structures of the protein have been performed. To mimic the impact of the extrinsic and intrinsic destructive parameters on the dynamical characteristics of the protein, mild acidic conditions and R208H mutation have been simulated. The findings indicated that distribution of conformational flexibilities along the protein chain was almost independent of the induced perturbing factors, and was mostly centralized on certain distinct parts of the structure comprising residues 132-145 and 187-203. Analyses also revealed that the segment comprising residues 187-203 may be considered as a peptide sequence, possessing high potential to start the initial steps of conformational rearrangements due to the induced physicochemical alterations. Sequence alignment and molecular dynamics data also revealed that segment 178-203 prefers to accommodate in extended structures rather than α-helices. Region 178-203 may be considered as a peptide switch capable of initiating the conformational transitions due to the introduced modifications and perturbing parameters.

To What Extent Are the Terminal Stages of Sepsis, Septic Shock, Systemic Inflammatory Response Syndrome, and Multiple Organ Dysfunction Syndrome Actually Driven by a Prion/Amyloid Form of Fibrin?

A well-established development of increasing disease severity leads from sepsis through systemic inflammatory response syndrome, septic shock, multiple organ dysfunction syndrome, and cellular and organismal death. Less commonly discussed are the equally well-established coagulopathies that accompany this. We argue that a lipopolysaccharide-initiated (often disseminated intravascular) coagulation is accompanied by a proteolysis of fibrinogen such that formed fibrin is both inflammatory and resistant to fibrinolysis. In particular, we argue that the form of fibrin generated is amyloid in nature because much of its normal α-helical content is transformed to β-sheets, as occurs with other proteins in established amyloidogenic and prion diseases. We hypothesize that these processes of amyloidogenic clotting and the attendant coagulopathies play a role in the passage along the aforementioned pathways to organismal death, and that their inhibition would be of significant therapeutic value, a claim for which there is considerable emerging evidence.

Heparin binding confers prion stability and impairs its aggregation

The conversion of the prion protein (PrP) into scrapie PrP (PrP(Sc)) is a central event in prion diseases. Several molecules work as cofactors in the conversion process, including glycosaminoglycans (GAGs). GAGs exhibit a paradoxical effect, as they convert PrP into protease-resistant PrP (PrP-res) but also exert protective activity. We compared the stability and aggregation propensity of PrP and the heparin-PrP complex through the application of different in vitro aggregation approaches, including real-time quaking-induced conversion (RT-QuIC). Transmissible spongiform encephalopathy-associated forms from mouse and hamster brain homogenates were used to seed RT-QuIC-induced fibrillization. In our study, interaction between heparin and cellular PrP (PrP(C)) increased thermal PrP stability, leading to an 8-fold decrease in temperature-induced aggregation. The interaction of low-molecular-weight heparin (LMWHep) with the PrP N- or C-terminal domain affected not only the extent of PrP fibrillization but also its kinetics, lowering the reaction rate constant from 1.04 to 0.29 s(-1) and increasing the lag phase from 12 to 19 h in RT-QuIC experiments. Our findings explain the protective effect of heparin in different models of prion and prion-like neurodegenerative diseases and establish the groundwork for the development of therapeutic strategies based on GAGs.

Helical ambivalency induced by point mutations

Background

Mutation of amino acid sequences in a protein may have diverse effects on its structure and function. Point mutations of even a single amino acid residue in the helices of the non-redundant database may lead to sequentially identical peptides which adopt different secondary structures in different proteins. However, various physico-chemical factors which govern the formation of these ambivalent helices generated by point mutations of a sequence are not clearly known.

Results

Sequences generated by point mutations of helices are mapped on to their non-helical counterparts in the SCOP database. The results show that short helices are prone to transform into non-helical conformations upon point mutations. Mutation of amino acid residues by helix breakers preferentially yield non-helical conformations, while mutation with residues of intermediate helix propensity display least preferences for non-helical conformations. Differences in the solvent accessibility of the mutating/mutated residues are found to be a major criteria for these sequences to conform to non-helical conformations. Even with minimal differences in the amino acid distributions of the sequences flanking the helical and non-helical conformations, helix-flanking sequences are found be more solvent accessible.

Conclusions

All types of mutations from helical to non-helical conformations are investigated. The primary factors attributing such changes in conformation can be: i) type/propensity of the mutating and mutant residues ii) solvent accessibility of the residue at the mutation site iii) context/environment dependence of the flanking sequences. The results from the present study may be used to design de novo proteins via point mutations.

Exploring the essential collective dynamics of interacting proteins: application to prion protein dimers

Essential collective dynamics is a promising and robust approach for analysing the slow motions of macromolecules from short molecular dynamics trajectories. In this study, an extension of the method to treat a collection of interacting protein molecules is presented. The extension is applied to investigate the effects of dimerization on the collective dynamics of ovine prion protein molecules in two different arrangements. Examination of the structural plasticity shows that aggregation has a restricting effect on the local mobility of the prion protein molecules in the interfacial regions. Domain motions of the two dimeric ovine prion protein conformations are distinctly different and can be related to interatomic correlations at the interface. Correlated motions are among the slow collective modes extensively analysed by considering both main-chain and side-chain atoms. Correlation maps reveal the existence of a vast network of dynamically correlated side groups, which extends beyond individual subunits via interfacial interconnections. The network is formed by a core of hydrophobic side chains surrounded by hydrophilic groups at the periphery. The relevance of these findings are discussed in the context of mutations associated with prion diseases. The binding free energy of the dimeric conformations is evaluated to probe their thermodynamic stability. The descriptions afforded by the analysis of the essential collective dynamics of the prion dimers are consistent with their binding free energies. The agreement validates the extension of the methodology and provides a means of interpreting the collective dynamics in terms of the thermodynamic stability of ovine prion proteins.

Coarse-grained simulations of protein aggregation

Protein aggregation is believed to be responsible for a number of human diseases and limits the yields of pharmaceutical proteins during production. Computer simulations can be used to develop novel experimentally testable hypotheses pertaining to aggregation. While all-atom simulations with explicit solvent are too computationally intensive to address the multitude of relevant time scales, coarse-grained models make it possible to observe the transition of monomers to an equilibrium containing aggregates. Here, we provide the reader with background information and a list of steps for setting up, performing, and analyzing computer simulations of aggregating coarse-grained (CG) proteins.

Accounting for protein-solvent contacts facilitates design of nonaggregating lattice proteins

The folding specificity of proteins can be simulated using simplified structural models and knowledge-based pair-potentials. However, when the same models are used to simulate systems that contain many proteins, large aggregates tend to form. In other words, these models cannot account for the fact that folded, globular proteins are soluble. Here we show that knowledge-based pair-potentials, which include explicitly calculated energy terms between the solvent and each amino acid, enable the simulation of proteins that are much less aggregation-prone in the folded state. Our analysis clarifies why including a solvent term improves the foldability. The aggregation for potentials without water is due to the unrealistically attractive interactions between polar residues, causing artificial clustering. When a water-based potential is used instead, polar residues prefer to interact with water; this leads to designed protein surfaces rich in polar residues and well-defined hydrophobic cores, as observed in real protein structures. We developed a simple knowledge-based method to calculate interactions between the solvent and amino acids. The method provides a starting point for modeling the folding and aggregation of soluble proteins. Analysis of our simple model suggests that inclusion of these solvent terms may also improve off-lattice potentials for protein simulation, design, and structure prediction.

Generation of prions in vitro and the protein-only hypothesis

Prions are self-propagating proteinaceous infectious agents capable of transmitting disease in the absence of nucleic acids. The nature of the infectious agent in prion diseases has been at the center of passionate debate for the past 30 years. However, recent reports on the in vitro generation of prions have settled all doubts that the misfolded prion protein (PrP(Sc)) is the key component in propagating infectivity. However, we still do not understand completely the mechanism of prion replication and whether or not other cellular factors besides PrP(Sc) are required for infectivity. In this article, we discuss these recent reports under the context of the protein-only hypothesis and their implications.

A minimal sequence code for switching protein structure and function

We present here a structural and mechanistic description of how a protein changes its fold and function, mutation by mutation. Our approach was to create 2 proteins that (i) are stably folded into 2 different folds, (ii) have 2 different functions, and (iii) are very similar in sequence. In this simplified sequence space we explore the mutational path from one fold to another. We show that an IgG-binding, 4beta+alpha fold can be transformed into an albumin-binding, 3-alpha fold via a mutational pathway in which neither function nor native structure is completely lost. The stabilities of all mutants along the pathway are evaluated, key high-resolution structures are determined by NMR, and an explanation of the switching mechanism is provided. We show that the conformational switch from 4beta+alpha to 3-alpha structure can occur via a single amino acid substitution. On one side of the switch point, the 4beta+alpha fold is >90% populated (pH 7.2, 20 degrees C). A single mutation switches the conformation to the 3-alpha fold, which is >90% populated (pH 7.2, 20 degrees C). We further show that a bifunctional protein exists at the switch point with affinity for both IgG and albumin.

Design of therapeutic proteins with enhanced stability

Therapeutic proteins such as antibodies constitute the most rapidly growing class of pharmaceuticals for use in diverse clinical settings including cancer, chronic inflammatory diseases, kidney transplantation, cardiovascular medicine, and infectious diseases. Unfortunately, they tend to aggregate when stored under the concentrated conditions required in their usage. Aggregation leads to a decrease in antibody activity and could elicit an immunological response. Using full antibody atomistic molecular dynamics simulations, we identify the antibody regions prone to aggregation by using a technology that we developed called spatial aggregation propensity (SAP). SAP identifies the location and size of these aggregation prone regions, and allows us to perform target mutations of those regions to engineer antibodies for stability. We apply this method to therapeutic antibodies and demonstrate the significantly enhanced stability of our mutants compared with the wild type. The technology described here could be used to incorporate developability in a rational way during the screening of antibodies in the discovery phase for several diseases.

Versatile approach to access the low temperature thermodynamics of lattice polymers and proteins

We show that Wang-Landau sampling, combined with suitable Monte Carlo trial moves, provides a powerful method for both the ground state search and the determination of the density of states for the hydrophobic-polar (HP) protein model and the interacting self-avoiding walk (ISAW) model for homopolymers. We obtain accurate estimates of thermodynamic quantities for HP sequences with >100 monomers and for ISAWs up to >500 monomers. Our procedure possesses an intrinsic simplicity and overcomes the limitations inherent in more tailored approaches making it interesting for a broad range of protein and polymer models.

Effects of macromolecular crowding on biochemical reaction equilibria: a molecular thermodynamic perspective

A molecular thermodynamic model is developed to investigate the effects of macromolecular crowding on biochemical reactions. Three types of reactions, representing protein folding/conformational isomerization, coagulation/coalescence, and polymerization/association, are considered. The reactants, products, and crowders are modeled as coarse-grained spherical particles or as polymer chains, interacting through hard-sphere interactions with or without nonbonded square-well interactions, and the effects of crowder size and chain length as well as product size are examined. The results predicted by this model are consistent with experimentally observed crowding effects based on preferential binding or preferential exclusion of the crowders. Although simple hard-core excluded-volume arguments do in general predict the qualitative aspects of the crowding effects, the results show that other intermolecular interactions can substantially alter the extent of enhancement or reduction of the equilibrium and can even change the direction of the shift. An advantage of the approach presented here is that competing reactions can be incorporated within the model.

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.

Thermodynamics of folding and association of lattice-model proteins

Closely related to the "protein folding problem" is the issue of protein misfolding and aggregation. Protein aggregation has been associated with the pathologies of nearly 20 human diseases and presents serious difficulties during the manufacture of pharmaceutical proteins. Computational studies of multiprotein systems have recently emerged as a powerful complement to experimental efforts aimed at understanding the mechanisms of protein aggregation. We describe the thermodynamics of systems containing two lattice-model 64-mers. A parallel tempering algorithm abates problems associated with glassy systems and the weighted histogram analysis method improves statistical quality. The presence of a second chain has a substantial effect on single-chain conformational preferences. The melting temperature is substantially reduced, and the increase in the population of unfolded states is correlated with an increase in interactions between chains. The transition from two native chains to a non-native aggregate is entropically favorable. Non-native aggregates receive approximately 25% of their stabilizing energy from intraprotein contacts not found in the lowest-energy structure. Contact maps show that for non-native dimers, nearly 50% of the most probable interprotein contacts involve pairs of residues that form native contacts, suggesting that a domain-swapping mechanism is involved in self-association.

Contact-induced structure transformation in transmembrane prion propagation

Based on recent experimental evidences of the transmission of prion diseases due to a particular transmembrane form (termed (Ctm)PrP), we propose a theoretical model for the molecular mechanism of such conformational diseases, in which a misfolded (Ctm)PrP induces a similar misfolding of another (Ctm)PrP. Computer simulations are performed to investigate the correlation between folding time and the concentration of misfolded PrP in various processes, including dimerization, trimerization, and cooperative dimerization. By comparing with the experimental correlation curve between incubation time and injected dose of scrapie prions, we conclude that cooperative dimerization may play an important role in the pathological mechanism of prion diseases.

Interpreting the Aggregation Kinetics of Amyloid Peptides

Amyloid fibrils are insoluble mainly beta-sheet aggregates of proteins or peptides. The multi-step process of amyloid aggregation is one of the major research topics in structural biology and biophysics because of its relevance in protein misfolding diseases like Alzheimer's, Parkinson's, Creutzfeld-Jacob's, and type II diabetes. Yet, the detailed mechanism of oligomer formation and the influence of protein stability on the aggregation kinetics are still matters of debate. Here a coarse-grained model of an amphipathic polypeptide, characterized by a free energy profile with distinct amyloid-competent (i.e. beta-prone) and amyloid-protected states, is used to investigate the kinetics of aggregation and the pathways of fibril formation. The simulation results suggest that by simply increasing the relative stability of the beta-prone state of the polypeptide, disordered aggregation changes into fibrillogenesis with the presence of oligomeric on-pathway intermediates, and finally without intermediates in the case of a very stable beta-prone state. The minimal-size aggregate able to form a fibril is generated by collisions of oligomers or monomers for polypeptides with unstable or stable beta-prone state, respectively. The simulation results provide a basis for understanding the wide range of amyloid-aggregation mechanisms observed in peptides and proteins. Moreover, they allow us to interpret at a molecular level the much faster kinetics of assembly of a recently discovered functional amyloid with respect to the very slow pathological aggregation.

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.

Spontaneous fibril formation by polyalanines; discontinuous molecular dynamics simulations

Fibrillary protein aggregates rich in beta-sheet structure have been implicated in the pathology of several neurodegenerative diseases. In this work, we investigate the formation of fibrils by performing discontinuous molecular dynamics simulations on systems containing 12 to 96 model Ac-KA(14)K-NH(2) peptides using our newly developed off-lattice, implicit-solvent, intermediate-resolution model, PRIME. We find that, at a low concentration, random-coil peptides assemble into alpha-helices at low temperatures. At intermediate concentrations, random-coil peptides assemble into alpha-helices at low temperatures and large beta-sheet structures at high temperatures. At high concentrations, the system forms beta-sheets over a wide range of temperatures. These assemble into fibrils above a critical temperature which decreases with concentration and exceeds the isolated peptide's folding temperature. At very high temperatures and all concentrations, the system is in a random-coil state. All of these results are in good qualitative agreement with those by Blondelle and co-workers on Ac-KA(14)K-NH(2) peptides. The fibrils observed in our simulations mimic the structural characteristics observed in experiments in terms of the number of sheets formed, the values of the intra- and intersheet separations, and the parallel peptide arrangement within each beta-sheet. Finally, we find that when the strength of the hydrophobic interaction between nonpolar side chains is high compared to the strength of hydrogen bonding, amorphous aggregates, rather than fibrillar aggregates, are formed.

Entropy capacity determines protein folding

Search and study of the general principles that govern kinetics and thermodynamics of protein folding generate a new insight into the factors controlling this process. Here, based on the known experimental data and using theoretical modeling of protein folding, we demonstrate that there exists an optimal relationship between the average conformational entropy and the average energy of contacts per residue-that is, an entropy capacity-for fast protein folding. Statistical analysis of conformational entropy and number of contacts per residue for 5829 protein structures from four general structural classes (all-alpha, all-beta, alpha/beta, alpha+beta) demonstrates that each class of proteins has its own class-specific average number of contacts (class alpha/beta has the largest number of contacts) and average conformational entropy per residue (class all-alpha has the largest number of rotatable angles phi, psi, and chi per residue). These class-specific features determine the folding rates: alpha proteins are the fastest folding proteins, then follow beta and alpha+beta proteins, and finally alpha/beta proteins are the slowest ones. Our result is in agreement with the experimental folding rates for 60 proteins. This suggests that structural and sequence properties are important determinants of protein folding rates.

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.

Model study of prionlike folding behavior in aggregated proteins

We investigate the folding behavior of protein sequences by numerically studying all sequences with a maximally compact lattice model through exhaustive enumeration. We get the prionlike behavior of protein folding. Individual proteins remaining stable in the isolated native state may change their conformations when they aggregate. We observe the folding properties as the interfacial interaction strength changes and find that the strength must be strong enough before the propagation of the most stable structures happens.

The competition between protein folding and aggregation: off-lattice minimalist model studies

Protein aggregation has been associated with a number of human diseases, and is a serious problem in the manufacture of recombinant proteins. Of particular interest to the biotechnology industry is deleterious aggregation that occurs during the refolding of proteins from inclusion bodies. As a complement to experimental efforts, computer simulations of multi-chain systems have emerged as a powerful tool to investigate the competition between folding and aggregation. Here we report results from Langevin dynamics simulations of minimalist model proteins. Order parameters are developed to follow both folding and aggregation. By mapping natural units to real units, the simulations are shown to be carried out under experimentally relevant conditions. Data pertaining to the contacts formed during the association process show that multiple mechanisms for aggregation exist, but certain pathways are statistically preferred. Kinetic data show that there are multiple time scales for aggregation, although most association events take place at times much shorter than those required for folding. Last, we discuss results presented here as a basis for future work aimed at rational design of mutations to reduce aggregation propensity, as well as for development of small-molecular weight refolding enhancers.

Solvent effects on the conformational transition of a model polyalanine peptide

We have investigated the folding of polyalanine by combining discontinuous molecular dynamics simulation with our newly developed off-lattice intermediate-resolution protein model. The thermodynamics of a system containing a single Ac-KA(14)K-NH(2) molecule has been explored by using the replica exchange simulation method to map out the conformational transitions as a function of temperature. We have also explored the influence of solvent type on the folding process by varying the relative strength of the side-chain's hydrophobic interactions and backbone hydrogen bonding interactions. The peptide in our simulations tends to mimic real polyalanine in that it can exist in three distinct structural states: alpha-helix, beta-structures (including beta-hairpin and beta-sheet-like structures), and random coil, depending upon the solvent conditions. At low values of the hydrophobic interaction strength between nonpolar side-chains, the polyalanine peptide undergoes a relatively sharp transition between an alpha-helical conformation at low temperatures and a random-coil conformation at high temperatures. As the hydrophobic interaction strength increases, this transition shifts to higher temperatures. Increasing the hydrophobic interaction strength even further induces a second transition to a beta-hairpin, resulting in an alpha-helical conformation at low temperatures, a beta-hairpin at intermediate temperatures, and a random coil at high temperatures. At very high values of the hydrophobic interaction strength, polyalanines become beta-hairpins and beta-sheet-like structures at low temperatures and random coils at high temperatures. This study of the folding of a single polyalanine-based peptide sets the stage for a study of polyalanine aggregation in a forthcoming paper.

Protein misfolding and amyloid formation for the peptide GNNQQNY from yeast prion protein Sup35: simulation by reaction path annealing

We study the early steps of amyloid formation of the seven residue peptide GNNQQNY from yeast prion-like protein Sup35 by simulating the random coil to beta-sheet and alpha-helix to beta-sheet transition both in the absence and presence of a cross-beta amyloid nucleus. The simulation method at atomic resolution employs a new implementation of a Langevin dynamics "reaction path annealing" algorithm. The results indicate that the presence of amyloid-like cross-beta-sheet strands both facilitates the transition into the cross-beta conformation and substantially lowers the free energy barrier for this transition. This model systems allows us to investigate the energetic and kinetic details of this transition, which is consistent with an auto-catalyzed, nucleation-like mechanism for the formation of beta-amyloid. In particular, we find that electrostatic interactions of peptide backbone dipoles contribute significantly to the stability of the beta-amyloid state. Furthermore, we find water exclusion and interactions of polar side-chains to be driving forces of amyloid formation: the cross-beta conformation is stabilized by burial of polar side-chains and inter-residue hydrogen bonds in the presence of an amyloid-like "seed". These findings are in support of a "dry, polar zipper model" of amyloid formation.

Self-assembly of the ionic peptide EAK16: the effect of charge distributions on self-assembly

Amphiphilic peptides suspended in aqueous solution display a rich set of aggregation behavior. Molecular-level studies of relatively simple amphiphilic molecules under controlled conditions are an essential step toward a better understanding of self-assembly phenomena of naturally occurring peptides/proteins. Here, we study the influence of molecular architecture and interactions on the self-assembly of model peptides (EAK16s), using both experimental and theoretical approaches. Three different types of EAK16 were studied: EAK16-I, -II, and -IV, which have the same amino acid composition but different amino acid sequences. Atomic force microscopy confirms that EAK16-I and -II form fibrillar assemblies, whereas EAK16-IV forms globular structures. The Fourier transform infrared spectrum of EAK16-IV indicates the possible formation of a beta-turn structure, which is not found in EAK16-I and -II. Our theoretical and numerical studies suggest the underlying mechanism behind these observations. We show that the hairpin structure is energetically stable for EAK16-IV, whereas the chain entropy of EAK16-I and -II favors relatively stretched conformations. Our combined experimental and theoretical approaches provide a clear picture of the interplay between single-chain properties, as determined by peptide sequences (or charge distributions), and the emerging structure at the nano (or more coarse-grained) level.

Protein aggregation determinants from a simplified model: cooperative folders resist aggregation

Two-chain aggregation simulations using minimalist models of proteins G, L, and mutants were used to investigate the fundamentals of protein aggregation. Mutations were selected to break up repeats of hydrophobic beads in the sequence while maintaining native topology and folding ability. Data are collected under conditions in which all chain types have similar folded populations and after equilibrating the separated chains to minimize competition between folding and aggregation. Folding cooperativity stands out as the best single-chain determinant under these conditions and for these simple models. It can be experimentally measured by the width of the unfolding transition during thermal denaturation and loosely related to population of intermediate-like states during folding. Additional measures of cooperativity and other properties such as radius of gyration fluctuations and patterning of hydrophobic residues are also examined. Initial contact system states with transition-state characteristics can be identified and are more expanded than average initial contact states. Two-chain minimalist model aggregates are considerably less structured than their native states and have minimal domain-swapping features.

Kinetics of fibril formation by polyalanine peptides

Ordered beta-sheet complexes, termed amyloid fibrils, are the underlying structural components of the intra- and extracellular fibrillar protein deposits that are associated with a variety of human diseases, including Alzheimer's, Parkinson's, and the prion diseases. In this work, we investigated the kinetics of fibril formation using our newly developed off-lattice intermediate resolution model, PRIME. The model is simple enough to allow the treatment of large multichain systems while maintaining a fairly realistic description of protein dynamics without built-in bias toward any conformation when used in conjunction with constant temperature discontinuous molecular dynamics, a fast alternative to conventional molecular dynamics. Simulations were performed on systems containing 48-96 model Ac-KA14K-NH2 peptides. We found that fibril formation for polyalanines incorporate features that are characteristic of three models, the templated assembly, nucleated polymerization, and nucleated conformational conversion models, but that none of them gave a completely satisfactory description of the simulation kinetics. Fibril formation was nucleation-dependent, occurring after a lag time that decreased with increasing peptide concentration and increased with increasing temperature. Fibril formation appeared to be a conformational conversion process in which small amorphous aggregates --> beta-sheets --> ordered nucleus --> subsequent rapid growth of a small stable fibril or protofilament. Fibril growth in our simulations involved both beta-sheet elongation, in which the fibril grew by adding individual peptides to the end of each beta-sheet, and lateral addition, in which the fibril grew by adding already formed beta-sheets to its side. The initial rate of fibril formation increased with increasing concentration and decreased with increasing temperature.

Replica exchange molecular dynamics simulations of amyloid peptide aggregation

The replica exchange molecular dynamics (REMD) approach is applied to four oligomeric peptide systems. At physiologically relevant temperature values REMD samples conformation space and aggregation transitions more efficiently than constant temperature molecular dynamics (CTMD). During the aggregation process the energetic and structural properties are essentially the same in REMD and CTMD. A condensation stage toward disordered aggregates precedes the beta-sheet formation. Two order parameters, borrowed from anisotropic fluid analysis, are used to monitor the aggregation process. The order parameters do not depend on the peptide sequence and length and therefore allow to compare the amyloidogenic propensity of different peptides

Phase diagrams describing fibrillization by polyalanine peptides

Amyloid fibrils are the structural components underlying the intra- and extracellular protein deposits that are associated with a variety of human diseases, including Alzheimer's, Parkinson's, and the prion diseases. In this work, we examine the thermodynamics of fibril formation using our newly-developed off-lattice intermediate-resolution protein model, PRIME. The model is simple enough to allow the treatment of large multichain systems while maintaining a fairly realistic description of protein dynamics when used in conjunction with constant-temperature discontinuous molecular dynamics, a fast alternative to conventional molecular dynamics. We conduct equilibrium simulations on systems containing 96 Ac-KA14K-NH2 peptides over a wide range of temperatures and peptide concentrations using the replica-exchange method. Based on measured values of the heat capacity, radius of gyration, and percentage of peptides that form the various structures, a phase diagram in the temperature-concentration plane is constructed delineating the regions where each structure is stable. There are four distinct single-phase regions: alpha-helices, fibrils, nonfibrillar beta-sheets, and random coils; and four two-phase regions: random coils/nonfibrillar beta-sheets, random coils/fibrils, fibrils/nonfibrillar beta-sheets, and alpha-helices/nonfibrillar beta-sheets. The alpha-helical region is at low temperature and low concentration. The nonfibrillar beta-sheet region is at intermediate temperatures and low concentrations and expands to higher temperatures as concentration is increased. The fibril region occurs at intermediate temperatures and intermediate concentrations and expands to lower as the peptide concentration is increased. The random-coil region is at high temperatures and all concentrations; this region shifts to higher temperatures as the concentration is increased.

Solvent-amino acid interaction energies in three-dimensional-lattice Monte Carlo simulations of a model 27-mer protein: Folding thermodynamics and kinetics

Amino acid residue-solvent interactions are required for lattice Monte Carlo simulations of model proteins in water. In this study, we propose an interaction-energy scale that is based on the interaction scale by Miyazawa and Jernigan. It permits systematic variation of the amino acid-solvent interactions by introducing a contrast parameter for the hydrophobicity, C(s), and a mean attraction parameter for the amino acids, omega. Changes in the interaction energies strongly affect many protein properties. We present an optimized energy parameter set for best representing realistic behavior typical for many proteins (fast folding and high cooperativity for single chains). Our optimal parameters feature a much weaker hydrophobicity contrast and mean attraction than does the original interaction scale. The proposed interaction scale is designed for calculating the behavior of proteins in bulk and at interfaces as a function of solvent characteristics, as well as protein size and sequence.

A structural model of polyglutamine determined from a host-guest method combining experiments and landscape theory

Modeling the structure of natively disordered peptides has proved difficult due to the lack of structural information on these peptides. In this work, we use a novel application of the host-guest method, combining folding theory with experiments, to model the structure of natively disordered polyglutamine peptides. Initially, a minimalist molecular model (C(alpha)C(beta)) of CI2 is developed with a structurally based potential and captures many of the folding properties of CI2 determined from experiments. Next, polyglutamine "guest" inserts of increasing length are introduced into the CI2 "host" model and the polyglutamine is modeled to match the resultant change in CI2 thermodynamic stability between simulations and experiments. The polyglutamine model that best mimics the experimental changes in CI2 thermodynamic stability has 1), a beta-strand dihedral preference and 2), an attractive energy between polyglutamine atoms 0.75-times the attractive energy between the CI2 host Go-contacts. When free-energy differences in the CI2 host-guest system are correctly modeled at varying lengths of polyglutamine guest inserts, the kinetic folding rates and structural perturbation of these CI2 insert mutants are also correctly captured in simulations without any additional parameter adjustment. In agreement with experiments, the residues showing structural perturbation are located in the immediate vicinity of the loop insert. The simulated polyglutamine loop insert predominantly adopts extended random coil conformations, a structural model consistent with low resolution experimental methods. The agreement between simulation and experimental CI2 folding rates, CI2 structural perturbation, and polyglutamine insert structure show that this host-guest method can select a physically realistic model for inserted polyglutamine. If other amyloid peptides can be inserted into stable protein hosts and the stabilities of these host-guest mutants determined, this novel host-guest method may prove useful to determine structural preferences of these intractable but biologically relevant protein fragments.

Coupled folding–binding versus docking: A lattice model study

Using a simple hydrophobic/polar protein model, we perform a Monte Carlo study of the thermodynamics and kinetics of binding to a target structure for two closely related sequences, one of which has a unique folded state while the other is unstructured. We obtain significant differences in their binding behavior. The stable sequence has rigid docking as its preferred binding mode, while the unstructured chain tends to first attach to the target and then fold. The free-energy profiles associated with these two binding modes are compared.

Assembly and kinetic folding pathways of a tetrameric beta-sheet complex: molecular dynamics simulations on simplified off-lattice protein models

We have performed discontinuous molecular dynamic simulations of the assembly and folding kinetics of a tetrameric beta-sheet complex that contains four identical four-stranded antiparallel beta-sheet peptides. The potential used in the simulation is a hybrid Go-type potential characterized by the bias gap parameter g, an artificial measure of a model protein's preference for its native state, and the intermolecular contact parameter eta, which measures the ratio of intermolecular to intramolecular native attractions. The formation of the beta-sheet complex and its equilibrium properties strongly depend on the size of the intermolecular contact parameter eta. The ordered beta-sheet complex in the folded state and nonaligned beta-sheets or tangled chains in the misfolded state are distinguished by measuring the squared radius of gyration Rg2 and the fraction of native contacts Q. The folding yield for the folded state is high at intermediate values of eta, but is low at both small and large values of eta. The folded state at small eta is liquid-like, but is solid-like at both intermediate and large eta. The misfolded state at small eta contains nonaligned beta-sheets and tangled chains with poor secondary structure at large eta. Various folding pathways via dimeric and trimeric intermediates are observed, depending on eta. Comparison with experimental results on protein aggregation indicates that intermediate eta values are most appropriate for modeling fibril formation and small eta values are most appropriate for modeling the formation of amorphous aggregates.

Thermodynamics and stability of a beta-sheet complex: molecular dynamics simulations on simplified off-lattice protein models

We have performed discontinuous molecular dynamics simulations of the thermodynamics and stability of a tetrameric beta-sheet complex that contains four identical four-stranded antiparallel beta-sheet peptides. The potential used in the simulation is a hybrid Go-type potential characterized by the bias gap parameter g, an artificial measure of the preference of a model protein for its native state, and the intermolecular contact parameter eta, which measures the ratio of intermolecular to intramolecular native attractions. Despite the simplicity of the model, a complex set of thermodynamic transitions for the beta-sheet complex is revealed that shows there are three distinct oligomer (partially ordered, ordered, and highly ordered beta-sheet complex) states and four noninteracting monomers phases. The thermodynamic properties of the three oligomer states strongly depend on both the size of the intermolecular contact parameter eta and the temperature. The partially ordered beta-sheet complex is made up of four ordered globules and is observed at intermediate to large eta at high temperatures. The ordered beta-sheet complex contains four native beta-sheets and is located at small to intermediate eta at low temperatures in the phase diagram. The highly ordered beta-sheet complex has fully-stiff beta-sheet strands, the same as the global energy minimum structure, and is observed for all eta at low temperatures.

The role of side-chain interactions in the early steps of aggregation: Molecular dynamics simulations of an amyloid-forming peptide from the yeast prion Sup35

Understanding the early steps of aggregation at atomic detail might be crucial for the rational design of therapeutics preventing diseases associated with amyloid deposits. In this paper, aggregation of the heptapeptide GNNQQNY, from the N-terminal prion-determining domain of the yeast protein Sup35, was studied by 20 molecular dynamics runs for a total simulation time of 20 micros. The simulations generate in-register parallel packing of GNNQQNY beta-strands that is consistent with x-ray diffraction and Fourier transform infrared data. The statistically preferred aggregation pathway does not correspond to a purely downhill profile of the energy surface because of the presence of enthalpic barriers that originate from out-of-register interactions. The parallel beta-sheet arrangement is favored over the antiparallel because of side-chain contacts; in particular, stacking interactions of the tyrosine rings and hydrogen bonds between amide groups. No ordered aggregation was found in control simulations with the mutant sequence SQNGNQQRG in accord with experimental data and the strong sequence dependence of aggregation.