Free energy landscapes for amyloidogenic tetrapeptides dimerization

Exploiting Sequence-Dependent Rotamer Information in Global Optimization of Proteins

Rotamers, namely amino acid side chain conformations common to many different peptides, can be compiled into libraries. These rotamer libraries are used in protein modeling, where the limited conformational space occupied by amino acid side chains is exploited. Here, we construct a sequence-dependent rotamer library from simulations of all possible tripeptides, which provides rotameric states dependent on adjacent amino acids. We observe significant sensitivity of rotamer populations to sequence and find that the library is successful in locating side chain conformations present in crystal structures. The library is designed for applications with basin-hopping global optimization, where we use it to propose moves in conformational space. The addition of rotamer moves significantly increases the efficiency of protein structure prediction within this framework, and we determine parameters to optimize efficiency.

Distribution and Structure Analysis of Fibril-Forming Peptides Focusing on Concentration Dependency

We focus on the concentration dependency of fibril-forming peptides, which have the potential of aggregation by themselves. In this study, we performed replica-exchange molecular dynamics simulations of Lys-Phe-Phe-Glu (KFFE) fragments, which are known to form fibrils in experiments under different concentration environments. The analysis by static structure factors suggested that the density fluctuation of the KFFE fragments becomes large as the concentration increases. It was also found that the number of β-structures and oligomers also increases under a high concentration environment. Hence, a high concentration environment of fibril-forming peptides is likely to cause protein aggregation.

Early aggregation mechanism of Aβ16-22 revealed by Markov state models

Aβ_16-22 is believed to have critical role in early aggregation of full length amyloids that are associated with the Alzheimer's disease and can aggregate to form amyloid fibrils. However, the early aggregation mechanism is still unsolved. Here, multiple long-term molecular dynamics simulations combining with Markov state model were used to probe the early oligomerization mechanism of Aβ_16-22 peptides. The identified dimeric form adopted either globular random-coil or extended β-strand like conformations. The observed dimers of these variants shared many overall conformational characteristics but differed in several aspects at detailed level. In all cases, the most common type of secondary structure was intermolecular antiparallel β-sheets. The inter-state transitions were very frequent ranges from few to hundred nanoseconds. More strikingly, those states which contain fraction of β secondary structure and significant amount of extended coiled structures, therefore exposed to the solvent, were majorly participated in aggregation. The assembly of low-energy dimers, in which the peptides form antiparallel β sheets, occurred by multiple pathways with the formation of an obligatory intermediates. We proposed that these states might facilitate the Aβ_16-22 aggregation through a significant component of the conformational selection mechanism, because they might increase the aggregates population by promoting the inter-chain hydrophobic and the hydrogen bond contacts. The formation of early stage antiparallel β sheet structures is critical for oligomerization, and at the same time provided a flat geometry to seed the ordered β-strand packing of the fibrils. Our findings hint at reorganization of this part of the molecule as a potentially critical step in Aβ aggregation and will insight into early oligomerization for large β amyloids.

Protein structure predictions by enhanced conformational sampling methods

In this Special Festschrift Issue for the celebration of Professor Nobuhiro Gō's 80th birthday, we review enhanced conformational sampling methods for protein structure predictions. We present several generalized-ensemble algorithms such as multicanonical algorithm, replica-exchange method, etc. and parallel Monte Carlo or molecular dynamics method with genetic crossover. Examples of the results of these methods applied to the predictions of protein tertiary structures are also presented.

Assembly modes of hexaphenylalanine variants as function of the charge states of their terminal ends

The ability of peptides to self-assemble represents a valuable tool for the development of biomaterials of biotechnological and/or biomedical interest. Diphenylalanine homodimer (FF) and its analogues are among the most promising systems in this field. The longest Phe-based building block hitherto characterized is pentaphenylalanine (F5). We studied the aggregation propensity and the structural/morphological features of assemblies of zwitterionic hexaphenylalanine H+-F6-O- and of three variants characterized by different charged states of the terminal ends (Ac-F6-Amide, H+-F6-Amide and Ac-F6-O-). As previously observed for PEGylated hexaphenylalanine (PEG8-F6), all F6 variants show a strong tendency to form β-rich assemblies in which the structural motif is constituted by antiparallel β-strands in the cross-β framework. Extensive replica exchange molecular dynamics simulations carried out on a pairs of F6 peptides indicate that the antiparallel β-structure of the final assemblies is likely dictated by the preferred association modes of the individual chains in the very early stages of the aggregation process. Our data suggest that even very small F6 peptides are properly pre-organized and prone to the build-up of the final assembly.

pH-Induced interfacial properties of Chaplin E from Streptomyces coelicolor

Chaplin E, or Chp E, is a surface active peptide secreted by Streptomyces coelicolor that adopts different structures depending on solution pH but the effect of these structures on the interfacial properties of Chp E is not known. In experiments paired with simulations, Chp E was found to display pH-dependent interfacial assembly and surface activity. At pH 3.0, Chp E formed an ordered non-amyloidal interfacial film with high surface activity; while at pH 10.0, Chp E self-assembled into a heterogeneous film containing randomly arranged fibrils at the interface that was less surface active compared to the film formed at pH 3.0. In simulations at pH 10.0, Chp E molecules showed a higher propensity for dimerization within the solution phase, lower rate of adsorption to the interface and tighter inter-molecular associations at the interface, consistent with the lower surface activity and smaller interfacial area coverage per molecule measured at this pH compared to at pH 3.0. A model is presented for the role of Chp E in the developmental differentiation of Streptomyces coelicolor, where Chp E contributes to changes in surface tension at low pH and the formation of fibrils on the surface of aerial hyphae at high pH. Our data also suggest Chp E could be a promising surface active agent with functional activity that can be controlled by pH.

The pH-dependent assembly of Chaplin E from Streptomyces coelicolor

Chaplin E, is one of five self-assembling peptides secreted by Streptomyces coelicolor that assist aerial growth by lowering the surface tension of water. Although the surface activity of a mixture of chaplin peptides has observed to depend on pH, it is unclear how the solvent environment (i.e. pH) influences the structure, assembly and subsequent functionality of these individual peptides. In this study, the conformation and fibril forming propensity of the Chaplin E peptide was assessed as a function of pH using a combination of experimental measurements and molecular dynamics simulations. At an acidic pH of 3.0, Chaplin E retained a random coil structure, whereas at the isoelectric point of 6.7 or a basic pH of 10.0, Chaplin E rapidly formed amyloid fibrils rich in β-sheet structure with high efficiency (>93%). Molecular dynamics simulations indicate the persistence of greater α-helical content at the N-terminus at high pH; this is likely partly due to the lack of electrostatic repulsion between residues His6 and Lys10. Since fibril formation was observed at high but not at low pH, we propose that the presence of an N-terminal α-helix in the monomeric form of Chaplin E is required for aggregation and conversion to β-amyloid fibrils. The pH sensitivity of Chaplin E peptide structure provides a route to control peptide assembly and may be important for the physiological function of this peptide, as a surface active agent in the transition from vegetative to aerial growth and could assist Streptomyces coelicolor in response to environmental fluctuations in pH.

Using VIPT-jump to distinguish between different folding mechanisms: application to BBL and a Trpzip

Protein folding involves a large number of sequential molecular steps or conformational substates. Thus, experimental characterization of the underlying folding energy landscape for any given protein is difficult. Herein, we present a new method that can be used to determine the major characteristics of the folding energy landscape in question, e.g., to distinguish between activated and barrierless downhill folding scenarios. This method is based on the idea that the conformational relaxation kinetics of different folding mechanisms at a given final condition will show different dependences on the initial condition. We show, using both simulation and experiment, that it is possible to differentiate between disparate kinetic folding models by comparing temperature jump (T-jump) relaxation traces obtained with a fixed final temperature and varied initial temperatures, which effectively varies the initial potential (VIP) of the system of interest. We apply this method (hereafter refer to as VIPT-jump) to two model systems, tryptophan zipper (Trpzip)-2c and BBL, and our results show that BBL exhibits characteristics of barrierless downhill folding, whereas Trpzip-2c folding encounters a free energy barrier. In addition, using the T-jump data of BBL we are able to provide, via Langevin dynamics simulations, a realistic estimate of its conformational diffusion coefficient.

Enhanced sampling algorithms

In biomolecular systems (especially all-atom models) with many degrees of freedom such as proteins and nucleic acids, there exist an astronomically large number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. Enhanced conformational sampling techniques are thus in great demand. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms in biomolecular systems. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present various extensions of these three generalized-ensemble algorithms. The effectiveness of the methods is tested with short peptide and protein systems.

Effects of intramolecular distance between amyloidogenic domains on amyloid aggregation

Peptide/protein aggregation is implicated in many amyloid diseases. Some amyloidogenic peptides/proteins, such as those implicated in Alzheimer’s and Parkinson’s diseases, contain multiple amyloidogenic domains connected by “linker” sequences displaying high propensities to form turn structures. Recent studies have demonstrated the importance of physicochemical properties of each amino acid contained in the polypeptide sequences in amyloid aggregation. However, effects on aggregation related to the intramolecular distance between amyloidogenic domains, which may be determined by a linker length, have yet to be examined. In the study presented here, we created peptides containing two copies of KFFE, a simple four-residue amyloidogenic domain, connected by GS-rich linker sequences with different lengths yet similar physicochemical properties. Our experimental results indicate that aggregation occurred most rapidly when KFFE domains were connected by a linker of an intermediate length. Our experimental findings were consistent with estimated entropic contribution of a linker length toward formation of (partially) structured intermediates on the aggregation pathway. Moreover, inclusion of a relatively short linker was found to inhibit formation of aggregates with mature fibril morphology. When the results are assimilated, our study demonstrates that intramolecular distance between amyloidogenic domains is an important yet overlooked factor affecting amyloid aggregation.

Nanomaterials design and tests for neural tissue engineering

Nanostructured scaffolds recently showed great promise in tissue engineering: nanomaterials can be tailored at the molecular level and scaffold morphology may more closely resemble features of extracellular matrix components in terms of porosity, framing and biofunctionalities. As a consequence, both biomechanical properties of scaffold microenvironments and biomaterial-protein interactions can be tuned, allowing for improved transplanted cell engraftment and better controlled diffusion of drugs. Easier said than done, a nanotech-based regenerative approach encompasses different fields of know-how, ranging from in silico simulations, nanomaterial synthesis and characterization at the nano-, micro- and mesoscales to random library screening methods (e.g. phage display), in vitro cellular-based experiments and validation in animal models of the target injury. All of these steps of the "assembly line" of nanostructured scaffolds are tightly interconnected both in their standard analysis techniques and in their most recent breakthroughs: indeed their efforts have to jointly provide the deepest possible analyses of the diverse facets of the challenging field of neural tissue engineering. The purpose of this review is therefore to provide a critical overview of the recent advances in and drawbacks and potential of each mentioned field, contributing to the realization of effective nanotech-based therapies for the regeneration of peripheral nerve transections, spinal cord injuries and brain traumatic injuries. Far from being the ultimate overview of such a number of topics, the reader will acknowledge the intrinsic complexity of the goal of nanotech tissue engineering for a conscious approach to the development of a regenerative therapy and, by deciphering the thread connecting all steps of the research, will gain the necessary view of its tremendous potential if each piece of stone is correctly placed to work synergically in this impressive mosaic.

Scanning tunneling microscopy reveals single-molecule insights into the self-assembly of amyloid fibrils

Many severe diseases are associated with amyloid fibril deposits in the body caused by protein misfolding. Structural information on amyloid fibrils is accumulating rapidly, but little is known about the assembly of peptides into fibrils at the level of individual molecules. Here we investigate self-assembly of the fibril-forming tetrapeptides KFFE and KVVE on a gold surface under ultraclean vacuum conditions using scanning tunneling microscopy. Combined with restrained molecular dynamics modeling, we identify peptide arrangements with interesting similarities to fibril structures. By resolving individual peptide residues and revealing conformational heterogeneities and dynamics, we demonstrate how conformational correlations may be involved in cooperative fibril growth. Most interestingly, intermolecular interactions prevail over intramolecular interactions, and assembly of the phenyl-rich KFFE peptide appears not to be dominated by π-π interactions. This study offers interesting perspectives for obtaining fundamental single-molecule insights into fibril formation using a surface science approach to study idealized model systems.

The assembly of individual chaplin peptides from Streptomyces coelicolor into functional amyloid fibrils

The self-association of proteins into amyloid fibrils offers an alternative to the natively folded state of many polypeptides. Although commonly associated with disease, amyloid fibrils represent the natural functional state of some proteins, such as the chaplins from the soil-dwelling bacterium Streptomyces coelicolor, which coat the aerial mycelium and spores rendering them hydrophobic. We have undertaken a biophysical characterisation of the five short chaplin peptides ChpD-H to probe the mechanism by which these peptides self-assemble in solution to form fibrils. Each of the five chaplin peptides produced synthetically or isolated from the cell wall is individually surface-active and capable of forming fibrils under a range of solution conditions in vitro. These fibrils contain a highly similar cross-β core structure and a secondary structure that resembles fibrils formed in vivo on the spore and mycelium surface. They can also restore the growth of aerial hyphae to a chaplin mutant strain. We show that cysteine residues are not required for fibril formation in vitro and propose a role for the cysteine residues conserved in four of the five short chaplin peptides.

Principles governing oligomer formation in amyloidogenic peptides

Identifying the principles that describe the formation of protein oligomers and fibrils with distinct morphologies is a daunting problem. Here we summarize general principles of oligomer formation gleaned from molecular dynamics simulations of Abeta-peptides. The spectra of high free energy structures sampled by the monomer provide insights into the plausible fibril structures, providing a rationale for the 'strain phenomenon.' Heterogeneous growth dynamics of small oligomers of Abeta(16-22), whose lowest free energy structures are like nematic droplets, can be broadly described using a two-stage dock-lock mechanism. In the growth process, water is found to play various roles depending on the oligomer size, and peptide length, and sequence. Water may be an explicit element of fibril structure linked to various fibril morphologies.

Demixing transition of the aqueous solution of amyloidogenic peptides: a REMD simulation study

The aggregation of amyloidogenic peptides in liquid water is studied at various temperatures by replica exchange molecular dynamics (REMD) simulations. The formation of a peptide aggregate upon decreasing the temperature reveals features typical for a first-order demixing phase transition, which is smeared out due to the finite size of the simulation box. Various properties of the ensemble of peptides were used to describe the temperature-induced demixing phase transition, which was found to occur at about 375 K. The hydrational and volumetric properties of the peptides and their aggregates are analyzed.

Assembly dynamics of two-beta sheets revealed by molecular dynamics simulations

The assembly dynamics of two beta sheets with different initial separation distances are explored by multiple all-atom molecular dynamics simulations with the presence of explicit water solvent. The beta sheet is composed of seven identical peptides in an antiparallel fashion. The peptide sequence is the 20-29 segment of human Islet amyloid polypeptide. Our simulations show that the assembly occurs not only in the lateral direction but also along the longitudinal direction, which provides a new insight into the assembly pathway at the early stage of fibril elongation. Based on Poisson-Boltzmann free energy analysis and quasiharmonic configuration entropy estimation, the entropic contribution is found to play an important role in the longitudinal assembly. Moreover, a possible oligomeric state with cyclic form is suggested based on one assembly model found in the simulations, illustrating the polymorphic nature of aggregation of the amyloidogenic peptide.

Computational approaches for the design of peptides with anti-breast cancer properties

Background: Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Methodology: Recently, a computational approach was used to successfully design peptides that are new lead compounds against breast cancer. We used replica exchange molecular dynamics to predict the structure and dynamics of active peptides, leading to the discovery of smaller bioactive peptides. Conclusions: These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used along with the experimental information that led to the successful completion of this research.

What determines the structure and stability of KFFE monomers, dimers, and protofibrils?

The self-assembly of the KFFE peptide was studied using replica exchange molecular dynamics simulations with a fully atomic description of the peptide and explicit solvent. The relative roles of the aromatic residues and oppositely charged end groups in stabilizing the earliest oligomers and the end-products of aggregation were investigated. beta and non-beta-peptide conformations compete in the monomeric state as a result of a balancing between the high beta-sheet propensity of the phenylalanine residues and charge-charge interactions that favor non-beta-conformations. Dimers are present in beta- and non-beta-sheet conformations and are stabilized primarily by direct and water-mediated charge-charge interactions between oppositely charged side chains and between oppositely charged termini, with forces between aromatic residues playing a minor role. Dimerization to a beta-sheet, fibril-competent state, is seen to be a cooperative process, with the association process inducing beta-structure in otherwise non-beta-monomers. We propose a model for the KFFE fibril, with mixed interface and antiparallel sheet and strand arrangements, which is consistent with experimental electron microscopy measurements. Both aromatic and charge-charge interactions contribute to the fibril stability, although the dominant contribution arises from electrostatic interactions.

Simple continuous and discrete models for simulating replica exchange simulations of protein folding

The efficiency of temperature replica exchange (RE) simulations hinge on their ability to enhance conformational sampling at physiological temperatures by taking advantage of more rapid conformational interconversions at higher temperatures. While temperature RE is a parallel simulation technique that is relatively straightforward to implement, kinetics in the RE ensemble is complicated, and there is much to learn about how best to employ RE simulations in computational biophysics. Protein folding rates often slow down above a certain temperature due to entropic bottlenecks. This "anti-Arrhenius" behavior represents a challenge for RE. However, it is far from straightforward to systematically explore the impact of this on RE by brute force molecular simulations, since RE simulations of protein folding are very difficult to converge. To understand some of the basic mechanisms that determine the efficiency of RE, it is useful to study simplified low dimensionality systems that share some of the key characteristics of molecular systems. Results are presented concerning the efficiency of temperature RE on a continuous two-dimensional potential that contains an entropic bottleneck. Optimal efficiency was obtained when the temperatures of the replicas did not exceed the temperature at which the harmonic mean of the folding and unfolding rates is maximized. This confirms a result we previously obtained using a discrete network model of RE. Comparison of the efficiencies obtained using the continuous and discrete models makes it possible to identify non-Markovian effects, which slow down equilibration of the RE ensemble on the more complex continuous potential. In particular, the rate of temperature diffusion and also the efficiency of RE is limited by the time scale of conformational rearrangements within free energy basins.

Computational study on the structural diversity of amyloid Beta Peptide (abeta(10-35)) oligomers

We studied the oligomerization of Alzheimer amyloid beta peptide (Abeta) using a replica exchange molecular dynamics (REMD) simulation. The simulation was performed with Abeta(10-35) dimers, trimers, and tetramers. Extensive REMD simulations illustrated several possible oligomer conformations. As the size of the oligomer increased from a dimer to a tetramer, the number of possible configurations was reduced. We identified all the possible conformations for each oligomer and characterized their temperature dependence. It was found that the detailed structures of the oligomers, which may act as folding intermediates, are highly sensitive to the parameters of the simulation environment such as temperature and concentration. Structural diversities of Abeta oligomers suggest multiple pathways of the aggregation process.

Modeling amyloid fibril formation: a free-energy approach

Amyloid fibrils are structures consisting of many proteins with a well-defined conformation. The formation of these fibrils has been the subject of intense research, largely due to their connection to several diseases. We focus here on the computational studies and discuss these from a free-energy point of view. The fibrillogenic properties of many proteins can be predicted and understood by taking the relevant free energies into account in an appropriate way. This is because both the equilibrium and the kinetic properties of the protein system depend on its free-energy landscape. Advanced simulation techniques can be used to understand the relationship between the free-energy landscape of a protein and its three-dimensional structure and propensity to form amyloid fibrils. We give an overview of existing simulation techniques that operate at a molecular level of detail and that are capable of generating relevant free-energy values. The free energies obtained with these methods can be inserted into a statistical-mechanical or kinetic framework to predict mean fibril properties on length scales and time scales that are inaccessible by molecular-scale simulation methods.

Thermodynamics and kinetics of aggregation for the GNNQQNY peptide

The energy landscape of the monomer and dimer are explored for the amyloidogenic heptapeptide GNNQQNY from the N-terminal prion-determining domain of the yeast protein Sup35. The peptide is modeled by a united-atom potential and an implicit solvent representation. Replica exchange molecular dynamics is used to explore the conformational space, and discrete path sampling is employed to investigate the pathways that interconvert the most populated minima on the free energy surfaces. For the monomer, we find a rapid fluctuation between four different conformations, where a geometry intermediate between compact and extended structures is the most thermodynamically favorable. The GNNQQNY dimer forms three stable sheet structures, namely in-register parallel, off-register parallel, and antiparallel. The antiparallel dimer is stabilized by strong electrostatic interactions resulting from interpeptide hydrogen bonds, which restrict its conformational flexibility. The in-register parallel dimer, which is close to the amyloid beta-sheet structure, has fewer interpeptide hydrogen bonds, making hydrophobic interactions more important and increasing the conformational entropy compared to the antiparallel sheet. The estimated two-state rate constants indicate that the formation of dimers from monomers is fast and that the dimers are kinetically stable against dissociation at room temperature. Interconversions between the different dimers are feasible processes and are more likely than dissociation.

Simulating replica exchange simulations of protein folding with a kinetic network model

Replica exchange (RE) is a generalized ensemble simulation method for accelerating the exploration of free-energy landscapes, which define many challenging problems in computational biophysics, including protein folding and binding. Although temperature RE (T-RE) is a parallel simulation technique whose implementation is relatively straightforward, kinetics and the approach to equilibrium in the T-RE ensemble are very complicated; there is much to learn about how to best employ T-RE to protein folding and binding problems. We have constructed a kinetic network model for RE studies of protein folding and used this reduced model to carry out "simulations of simulations" to analyze how the underlying temperature dependence of the conformational kinetics and the basic parameters of RE (e.g., the number of replicas, the RE rate, and the temperature spacing) all interact to affect the number of folding transitions observed. When protein folding follows anti-Arrhenius kinetics, we observe a speed limit for the number of folding transitions observed at the low temperature of interest, which depends on the maximum of the harmonic mean of the folding and unfolding transition rates at high temperature. The results shown here for the network RE model suggest ways to improve atomic-level RE simulations such as the use of "training" simulations to explore some aspects of the temperature dependence for folding of the atomic-level models before performing RE studies.

Self-assembly of β-sheet forming peptides into chiral fibrillar aggregates

The authors introduce a novel mid-resolution off-lattice coarse-grained model to investigate the self-assembly of beta-sheet forming peptides. The model retains most of the peptide backbone degrees of freedom as well as one interaction center describing the side chains. The peptide consists of a core of alternating hydrophobic and hydrophilic residues, capped by two oppositely charged residues. Nonbonded interactions are described by Lennard-Jones and Coulombic terms. The influence of different levels of "hydrophobic" and "steric" forces between the side chains of the peptides on the thermodynamics and kinetics of aggregation was investigated using Langevin dynamics. The model is simple enough to allow the simulation of systems consisting of hundreds of peptides, while remaining realistic enough to successfully lead to the formation of chiral, ordered beta tapes, ribbons, as well as higher order fibrillar aggregates.

Computational design and experimental discovery of an antiestrogenic peptide derived from alpha-fetoprotein

Breast cancer is the most common cancer among women, and tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment. Many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Consequently, there is an ongoing need for breast cancer drugs that have different molecular targets. Previous work has shown that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat models, interacting with an unsolved receptor, while peptides smaller than eight amino acids did not. We show that the use of replica exchange molecular dynamics predicts the structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. Simulations identified smaller peptide analogues with the same conserved reverse turn demonstrated in the larger peptides. These analogues were synthesized and shown to inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition.

Molecular dynamics simulations on the oligomer-formation process of the GNNQQNY peptide from yeast prion protein Sup35

Oligomeric intermediates are possible cytotoxic species in diseases associated with amyloid deposits. Understanding the early steps of fibril formation at atomic details may provide useful information for the rational therapeutic design. In this study, using the heptapeptide GNNQQNY from the yeast prion-like protein Sup35 as a model system, for which a detailed atomic structure of the fibril formed has been determined by x-ray microcrystallography, we investigated its oligomer-formation process from monomer to tetramer at the atomistic level by means of a molecular dynamics simulation with explicit water. Although the number of simulations was limited, the qualitative statistical data gave some interesting results, which indicated that the oligomer formation might start from antiparallel beta-sheet-like dimers. When a new single peptide strand was added to the preformed dimers to form trimers and then tetramers, the transition time from disorder aggregates to regular ones for the parallel alignment was found to be obviously much less than for the antiparallel one. Moreover, the parallel pattern also statistically stayed longer, providing more chances for oligomer extending, although the number of parallel stack events was almost equal to antiparallel ones. Therefore, our simulations showed that new strands might prefer to extend in a parallel arrangement to form oligomers, which agrees with the microcrystal structure of the amyloid fibril formed by this peptide. In addition, analysis of the pi-pi stacking of aromatic residues showed that this type of interaction did not play an important role in giving directionality for beta-strand alignment but played a great influence on stabilizing the structures formed in the oligomer-formation process.

Comparison of solvation-effect methods for the simulation of peptide interactions with a hydrophobic surface

In this study we investigated the interaction behavior between thirteen different small peptides and a hydrophobic surface using three progressively more complex methods of representing solvation effects: a united-atom implicit solvation method [CHARMM 19 force field (C19) with Analytical Continuum Electrostatics (ACE)], an all-atom implicit solvation method (C22 with GBMV), and an all-atom explicit solvation method (C22 with TIP3P). The adsorption behavior of each peptide was characterized by the calculation of the potential of mean force as a function of peptide-surface separation distance. The results from the C22/TIP3P model suggest that hydrophobic peptides exhibit relatively strong adsorption behavior, polar and positively-charged peptides exhibit negligible to relatively weak favorable interactions with the surface, and negatively-charged peptides strongly resist adsorption. Compared to the TIP3P model, the ACE and GBMV implicit solvent models predict much stronger attractions for the hydrophobic peptides as well as stronger repulsions for the negatively-charged peptides on the CH(3)-SAM surface. These comparisons provide a basis from which each of these implicit solvation methods may be reparameterized to provide closer agreement with explicitly represented solvation in simulations of peptide and protein adsorption to functionalized surfaces.

Consensus features in amyloid fibrils: sheet–sheet recognition via a (polar or nonpolar) zipper structure

Amyloid fibrils characterized as highly intractable thread-like species are associated with many neurodegenerative diseases. Although neither the mechanism of amyloid formation nor the origin of amyloid toxicity is currently completely understood, the detailed three-dimensional atomic structures of the yeast protein Sup35 and Abeta amyloid protein determined by recent experiments provide the first and important step towards the comprehension of the pathogenesis and aggregation mechanisms of amyloid diseases. By analyzing these two amyloid peptides which have available crystal structures and other amyloid sequences with proposed structures using computational simulations, we delineate three common features in amyloid organizations and amyloid structures. These could contribute to an improved understanding of the molecular mechanism of amyloid formation, the nature of the aggregation driving forces that stabilize these structures and the development of potential therapeutic agents against amyloid diseases.

Folding Landscapes of the Alzheimer Amyloid-β(12-28) Peptide

The energy landscape for folding of the 12-28 fragment of the Alzheimer amyloid beta (Abeta) peptide is characterized using replica-exchange molecular dynamics simulations with an all-atom peptide model and explicit solvent. At physiological temperatures, the peptide exists mostly as a collapsed random coil, populating a small fraction (less than 10%) of hairpins with a beta-turn at position V18F19, with another 10% of hairpin-like conformations possessing a bend rather than a turn in the central VFFA positions. A small fraction of the populated states, approximately 14%, adopt polyproline II (PPII) conformations. Folding of the structured hairpin states proceeds through the assembly of two locally stable segments, VFFAE and EDVGS. The interactions stabilizing these locally folded structural motifs are in conflict with those stabilizing the global fold of A12-28, a signature of underlying residual frustration in this peptide. At increased temperature, the population of both beta-strand and PPII conformations diminishes in favor of beta-turn and random-coil states. On the basis of the conformational preferences of Abeta 12-28 monomers, two models for the molecular structure of amyloid fibrils formed by this peptide are proposed.

Effects of solvent on the structure of the Alzheimer amyloid-beta(25-35) peptide

The free energy landscape for folding of the Alzheimer's amyloid-beta(25-35) peptide is explored using replica exchange molecular dynamics in both pure water and in HFIP/water cosolvent. This amphiphilic peptide is a natural by-product of the Alzheimer's amyloid-beta(1-40) peptide and retains the toxicity of its full-length counterpart as well as the ability to aggregate into beta-sheet-rich fibrils. Our simulations reveal that the peptide preferentially populates a helical structure in apolar organic solvent, while in pure water, the peptide adopts collapsed coil conformations and to a lesser extent beta-hairpin conformations. The beta-hairpin is characterized by a type II' beta-turn involving residues G29 and A30 and two short beta-strands involving residues N27, K28, I31, and I32. The hairpin is stabilized by backbone hydrogen-bonding interactions between residues K28 and I31; S26 and G33; and by side-chain-to-side-chain interactions between N27 and I32. Implications regarding the mechanism of aggregation of this peptide into fibrils and the role of the environment in modulating secondary structure are discussed.

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.