Competition between ß-Sheet and Coacervate Domains Yields Diverse Morphologies in Mixtures of Oppositely Charged Homochiral Polypeptides.

Biomolecular assembly processes involving competition between specific intermolecular interactions and thermodynamic phase instability have been implicated in a number of pathological states and technological applications of biomaterials. As a model for such processes, aqueous mixtures of oppositely charged homochiral polypeptides such as poly-l-lysine and poly-l-glutamic acid have been reported to form either ß-sheet-rich solid-like precipitates or liquid-like coacervate droplets depending on competing hydrogen bonding interactions. Herein, we report studies of polypeptide mixtures that reveal unexpectedly diverse morphologies ranging from partially coalescing and aggregated droplets to bulk precipitates, as well as a previously unreported re-entrant liquid-liquid phase separation at high polypeptide concentration and ionic strength. Combining our experimental results with all-atom molecular dynamics simulations of folded polypeptide complexes reveals a concentration dependence of ß-sheet-rich secondary structure, whose relative composition correlates with the observed macroscale morphologies of the mixtures. These results elucidate a crucial balance of interactions that are important for controlling morphology during coacervation in these and potentially similar biologically relevant systems.

A New Transfer Free Energy Based Implicit Solvation Model for the Description of Disordered and Folded Proteins.

Most biological events occur on time scales that are difficult to access using conventional all-atom molecular dynamics simulations in explicit solvent. Implicit solvent techniques offer a promising solution to this problem, alleviating the computational cost associated with the simulation of large systems and accelerating the sampling compared to explicit solvent models. The substitution of water molecules by a mean field, however, introduces simplifications that may penalize accuracy and impede the prediction of certain physical properties. We demonstrate that existing implicit solvent models developed using a transfer free energy approach, while satisfactory at reproducing the folding behavior of globular proteins, fare less well in characterizing the conformational properties of intrinsically disordered proteins. We develop a new implicit solvent model that maximizes the degree of accuracy for both disordered and folded proteins. We show, by comparing the simulation outputs to experimental data, that in combination with the a99SB-disp force field, the implicit solvent model can describe both disordered (aß40, PaaA2, and drkN SH3) and folded ((AAQAA)3, CLN025, Trp-cage, and GTT) peptides. Our implicit solvent model permits a computationally efficient investigation of proteins containing both ordered and disordered regions, as well as the study of the transition between ordered and disordered protein states.

Cosolvent Exclusion Drives Protein Stability in Trimethylamine N-Oxide and Betaine Solutions.

Using a combination of molecular dynamics simulation, dialysis experiments, and electronic circular dichroism measurements, we studied the solvation thermodynamics of proteins in two osmolyte solutions, trimethylamine N-oxide (TMAO) and betaine. We showed that existing force fields are unable to capture the solvation properties of the proteins lysozyme and ribonuclease T1 and that the inaccurate parametrization of protein-osmolyte interactions in these force fields promoted an unphysical strong thermal denaturation of the trpcage protein. We developed a novel force field for betaine (the KBB force field) which reproduces the experimental solution Kirkwood-Buff integrals and density. We further introduced appropriate scaling to protein-osmolyte interactions in both the betaine and TMAO force fields which led to successful reproduction of experimental protein-osmolyte preferential binding coefficients for lysozyme and ribonuclease T1 and prevention of the unphysical denaturation of trpcage in osmolyte solutions. Correct parametrization of protein-TMAO interactions also led to the stabilization of the collapsed conformations of a disordered elastin-like peptide, while the uncorrected parameters destabilized the collapsed structures. Our results establish that the thermodynamic stability of proteins in both betaine and TMAO solutions is governed by osmolyte exclusion from proteins.

Molecular Context of Dopa Influences Adhesion of Mussel-Inspired Peptides.

Improving adhesives for wet surfaces is an ongoing challenge. While the adhesive proteins of marine mussels have inspired many synthetic wet adhesives, the mechanisms of mussel adhesion are still not fully understood. Using surface forces apparatus (SFA) measurements and replica-exchange and umbrella-sampling molecular dynamics simulations, we probed the relationships between the sequence, structure, and adhesion of mussel-inspired peptides. Experimental and computational results reveal that peptides derived from mussel foot protein 3 slow (mfp-3s) containing 3,4-dihydroxyphenylalanine (Dopa), a post-translationally modified variant of tyrosine commonly found in mussel foot proteins, form adhesive monolayers on mica. In contrast, peptides with tyrosine adsorb as weakly adhesive clusters. We further considered simulations of mfp-3s derivatives on a range of hydrophobic and hydrophilic organic and inorganic surfaces (including silica, self-assembled monolayers, and a lipid bilayer) and demonstrated that the chemical character of the target surface and proximity of cationic and hydrophobic residues to Dopa affect peptide adsorption and adhesion. Collectively, our results suggest that conversion of tyrosine to Dopa in hydrophobic, sparsely charged peptides influences peptide self-association and ultimately dictates their adhesive performance.

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

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

The proline-rich domain promotes Tau liquid-liquid phase separation in cells.

Tau protein in vitro can undergo liquid-liquid phase separation (LLPS); however, observations of this phase transition in living cells are limited. To investigate protein state transitions in living cells, we attached Cry2 to Tau and studied the contribution of each domain that drives the Tau cluster in living cells. Surprisingly, the proline-rich domain (PRD), not the microtubule binding domain (MTBD), drives LLPS and does so under the control of its phosphorylation state. Readily observable, PRD-derived cytoplasmic condensates underwent fusion and fluorescence recovery after photobleaching consistent with the PRD LLPS in vitro. Simulations demonstrated that the charge properties of the PRD predicted phase separation. Tau PRD formed heterotypic condensates with EB1, a regulator of plus-end microtubule dynamic instability. The specific domain properties of the MTBD and PRD serve distinct but mutually complementary roles that use LLPS in a cellular context to implement emergent functionalities that scale their relationship from binding α-beta tubulin heterodimers to the larger proportions of microtubules.

CORE-MD, a path correlated molecular dynamics simulation method.

We present an enhanced Molecular Dynamics (MD) simulation method, which is free from the requirement of a priori structural information of the system. The technique is capable of folding proteins with very low computational effort and requires only an energy parameter. The path correlated MD (CORE-MD) method uses the autocorrelation of the path integral over the reduced action and propagates the system along the history dependent path correlation. We validate the new technique in simulations of the conformational landscapes of dialanine and the TrpCage mini-peptide. We find that the novel method accelerates the sampling by three orders of magnitude and observe convergence of the conformational sampling in both cases. We conclude that the new method is broadly applicable for the enhanced sampling in MD simulations. The CORE-MD algorithm reaches a high accuracy compared with long time equilibrium MD simulations.

Latent Models of Molecular Dynamics Data: Automatic Order Parameter Generation for Peptide Fibrillization.

Variational autoencoders are artificial neural networks with the capability to reduce highly dimensional sets of data to smaller dimensional, latent representations. In this work, these models are applied to molecular dynamics simulations of the self-assembly of coarse-grained peptides to obtain a singled-valued order parameter for amyloid aggregation. This automatically learned order parameter is constructed by time-averaging the latent parametrizations of internal coordinate representations and compared to the nematic order parameter which is commonly used to study ordering of similar systems in literature. It is found that the latent space value provides more tailored insight into the aggregation mechanism's details, correctly identifying fibril formation in instances where the nematic order parameter fails to do so. A means is provided by which the latent space value can be analyzed so that the major contributing internal coordinates are identified, allowing for a direct interpretation of the latent space order parameter in terms of the behavior of the system. The latent model is found to be an effective and convenient way of representing the data from the dynamic ensemble and provides a means of reducing the dimensionality of a system whose scale exceeds molecular systems so-far considered with similar tools. This bypasses a need for researcher speculation on what elements of a system best contribute to summarizing major transitions and suggests latent models are effective and insightful when applied to large systems with a diversity of complex behaviors.

Terminal Capping of an Amyloidogenic Tau Fragment Modulates Its Fibrillation Propensity.

Aberrant protein folding leading to the formation of characteristic cross-ß-sheet-rich amyloid structures is well known for its association with a variety of debilitating human diseases. Often, depending upon amino acid composition, only a small segment of a large protein participates in amyloid formation and is in fact capable of self-assembling into amyloid, independent of the rest of the protein. Therefore, such peptide fragments serve as useful model systems for understanding the process of amyloid formation. An important factor that has often been overlooked while using peptides to mimic full-length protein is the charge on the termini of these peptides. Here, we show the influence of terminal charges on the aggregation of an amyloidogenic peptide from microtubule-associated protein Tau, implicated in Alzheimer's disease and tauopathies. We found that modification of terminal charges by capping the peptide at one or both of the termini drastically modulates the fibrillation of the hexapeptide sequence paired helical filament 6 (PHF6) from repeat 3 of Tau, both with and without heparin. Without heparin, the PHF6 peptide capped at both termini and PHF6 capped only at the N-terminus self-assembled to form amyloid fibrils. With heparin, all capping variants of PHF6, except for PHF6 with both termini free, formed typical amyloid fibrils. However, the rate and extent of aggregation both with and without heparin as well as the morphology of aggregates were found to be highly dependent on the terminal charges. Our molecular dynamics simulations on PHF6 capping variants corroborated our experiments and provided critical insights into the mechanism of PHF6 self-assembly. Overall, our results emphasize the importance of terminal modifications in fibrillation of small peptide fragments and provide significant insights into the aggregation of a small Tau fragment, which is considered essential for Tau filament assembly.

Distinct and Nonadditive Effects of Urea and Guanidinium Chloride on Peptide Solvation.

Using enhanced-sampling replica exchange fully atomistic molecular dynamics simulations, we show that, individually, urea and guanidinium chloride (GdmCl) denature the Trpcage protein, but remarkably, the helical segment 1NLYIQWL7 of the protein is stabilized in mixed denaturant solutions. GdmCl induces protein denaturation via a combination of direct and indirect effects involving dehydration of the protein and destabilization of stabilizing salt bridges. In contrast, urea denatures the protein through favorable protein-urea preferential interactions, with peptide-specific indirect effects of urea on the water structure around the protein. In the case of the helical segment of Trpcage, urea "oversolvates" the peptide backbone by reorganizing water molecules from the peptide side chains to the peptide backbone. An intricate nonadditive thermodynamic balance between GdmCl-induced dehydration of the peptide and the urea-induced changes in solvation structure triggers partial counteraction to urea denaturation and stabilization of the helix.

The Mitochondrial Peptide Humanin Targets but Does Not Denature Amyloid Oligomers in Type II Diabetes.

Mitochondrially derived peptides (MDPs) such as humanin (HN) have shown a remarkable ability to modulate neurological amyloids and apoptosis-associated proteins in cells and animal models. Recently, we found that humanin-like peptides also inhibit amyloid formation outside of neural environments in islet amyloid polypeptide (IAPP) fibrils and plaques, which are hallmarks of Type II diabetes. However, the biochemical basis for regulating amyloids through endogenous MDPs remains elusive. One hypothesis is that MDPs stabilize intermediate amyloid oligomers and discourage the formation of insoluble fibrils. To test this hypothesis, we carried out simulations and experiments to extract the dominant interactions between the S14G-HN mutant (HNG) and a diverse set of IAPP structures. Replica-exchange molecular dynamics suggests that MDPs cap the growth of amyloid oligomers. Simulations also indicate that HNG-IAPP heterodimers are 10 times more stable than IAPP homodimers, which explains the substoichiometric ability of HNG to inhibit amyloid growth. Despite this strong attraction, HNG does not denature IAPP. Instead, HNG binds IAPP near the disordered NFGAIL motif, wedging itself between amyloidogenic fragments. Shielding of NFGAIL-flanking fragments reduces the formation of parallel IAPP ß-sheets and subsequent nucleation of mature amyloid fibrils. From ThT spectroscopy and electron microscopy, we found that HNG does not deconstruct mature IAPP fibrils and oligomers, consistent with the simulations and our proposed hypothesis. Taken together, this work provides new mechanistic insight into how endogenous MDPs regulate pathological amyloid growth at the molecular level and in highly substoichiometric quantities, which can be exploited through peptidomimetics in diabetes or Alzheimer's disease.

The Classifying Autoencoder: Gaining Insight into Amyloid Assembly of Peptides and Proteins.

Despite the importance of amyloid formation in disease pathology, the understanding of the primary structure?activity relationship for amyloid-forming peptides remains elusive. Here we use a new neural-network based method of analysis: the classifying autoencoder (CAE). This machine learning technique uses specialized architecture of artificial neural networks to provide insight into typically opaque classification processes. The method proves to be robust to noisy and limited data sets, as well as being capable of disentangling relatively complicated rules over data sets. We demonstrate its capabilities by applying the technique to an experimental database (the Waltz database) and demonstrate the CAE?s capability to provide insight into a novel descriptor, dimeric isotropic deviation?an experimental measure of the aggregation properties of the amino acids. We measure this value for all 20 of the common amino acids and find correlation between dimeric isotropic deviation and the failure to form amyloids when hydrophobic effects are not a primary driving force in amyloid formation. These applications show the value of the new method and provide a flexible and general framework to approach problems in biochemistry using artificial neural networks.

Conformational investigation of the structure-activity relationship of GdFFD and its analogues on an achatin-like neuropeptide receptor of Aplysia californica involved in the feeding circuit.

Proteins and peptides in nature are almost exclusively made from l-amino acids, and this is even more absolute in the metazoan. With the advent of modern bioanalytical techniques, however, previously unappreciated roles for d-amino acids in biological processes have been revealed. Over 30 d-amino acid containing peptides (DAACPs) have been discovered in animals where at least one l-residue has been isomerized to the d-form via an enzyme-catalyzed process. In Aplysia californica, GdFFD and GdYFD (the lower-case letter "d" indicates a d-amino acid residue) modulate the feeding behavior by activating the Aplysia achatin-like neuropeptide receptor (apALNR). However, little is known about how the three-dimensional conformation of DAACPs influences activity at the receptor, and the role that d-residues play in these peptide conformations. Here, we use a combination of computational modeling, drift-tube ion-mobility mass spectrometry, and receptor activation assays to create a simple model that predicts bioactivities for a series of GdFFD analogs. Our results suggest that the active conformations of GdFFD and GdYFD are similar to their lowest energy conformations in solution. Our model helps connect the predicted structures of GdFFD analogs to their activities, and highlights a steric effect on peptide activity at position 1 on the GdFFD receptor apALNR. Overall, these methods allow us to understand ligand-receptor interactions in the absence of high-resolution structural data.

Trimethylamine N-oxide Counteracts Urea Denaturation by Inhibiting Protein-Urea Preferential Interaction.

Osmolytes are small organic molecules that can modulate the stability and function of cellular proteins by altering the chemical environment of the cell. Some of these osmolytes work in conjunction, via mechanisms that are poorly understood. An example is the naturally occurring protein-protective osmolyte trimethylamine N-oxide (TMAO) that stabilizes cellular proteins in marine organisms against the detrimental denaturing effects of another naturally occurring osmolyte, urea. From a computational standpoint, our understanding of this counteraction mechanism is hampered by the fact that existing force fields fail to capture the correct balance of TMAO and urea interactions in ternary solutions. Using molecular dynamics simulations and Kirkwood-Buff theory of solutions, we have developed an optimized force field that reproduces experimental Kirkwood-Buff integrals. We show through the study of two model systems, a 15-residue polyalanine chain and the R2-fragment (273GKVQIINKKLDL284) of the Tau protein, that TMAO can counteract the denaturing effects of urea by inhibiting protein-urea preferential interaction. The extent to which counteraction can occur is seen to depend heavily on the amino acid composition of the peptide.

1,2,3,4,6-penta-O-galloyl-ß-D-glucopyranose Binds to the N-terminal Metal Binding Region to Inhibit Amyloid ß-protein Oligomer and Fibril Formation.

The early oligomerization of amyloid ß-protein (Aß) is a crucial step in the etiology of Alzheimer's disease (AD), in which soluble and highly neurotoxic oligomers are produced and accumulated inside neurons. In search of therapeutic solutions for AD treatment and prevention, potent inhibitors that remodel Aß assembly and prevent neurotoxic oligomer formation offer a promising approach. In particular, several polyphenolic compounds have shown anti-aggregation properties and good efficacy on inhibiting oligomeric amyloid formation. 1,2,3,4,6-penta-O-galloyl-ß-D-glucopyranose is a large polyphenol that has been shown to be effective at inhibiting aggregation of full-length Aß1-40 and Aß1-42, but has the opposite effect on the C-terminal fragment Aß25-35. Here, we use a combination of ion mobility coupled to mass spectrometry (IMS-MS), transmission electron microscopy (TEM) and molecular dynamics (MD) simulations to elucidate the inhibitory effect of PGG on aggregation of full-length Aß1-40 and Aß1-42. We show that PGG interacts strongly with these two peptides, especially in their N-terminal metal binding regions, and suppresses the formation of Aß1-40 tetramer and Aß1-42 dodecamer. By exploring multiple facets of polyphenol-amyloid interactions, we provide a molecular basis for the opposing effects of PGG on full-length Aß and its C-terminal fragments.

Signature of an aggregation-prone conformation of tau.

The self-assembly of the microtubule associated tau protein into fibrillar cell inclusions is linked to a number of devastating neurodegenerative disorders collectively known as tauopathies. The mechanism by which tau self-assembles into pathological entities is a matter of much debate, largely due to the lack of direct experimental insights into the earliest stages of aggregation. We present pulsed double electron-electron resonance measurements of two key fibril-forming regions of tau, PHF6 and PHF6*, in transient as aggregation happens. By monitoring the end-to-end distance distribution of these segments as a function of aggregation time, we show that the PHF6(*) regions dramatically extend to distances commensurate with extended ß-strand structures within the earliest stages of aggregation, well before fibril formation. Combined with simulations, our experiments show that the extended ß-strand conformational state of PHF6(*) is readily populated under aggregating conditions, constituting a defining signature of aggregation-prone tau, and as such, a possible target for therapeutic interventions.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different ß-stranded peptides: the C-terminal ß-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

Surface force measurements and simulations of mussel-derived peptide adhesives on wet organic surfaces.

Translating sticky biological molecules-such as mussel foot proteins (MFPs)-into synthetic, cost-effective underwater adhesives with adjustable nano- and macroscale characteristics requires an intimate understanding of the glue's molecular interactions. To help facilitate the next generation of aqueous adhesives, we performed a combination of surface forces apparatus (SFA) measurements and replica-exchange molecular dynamics (REMD) simulations on a synthetic, easy to prepare, Dopa-containing peptide (MFP-3s peptide), which adheres to organic surfaces just as effectively as its wild-type protein analog. Experiments and simulations both show significant differences in peptide adsorption on CH3-terminated (hydrophobic) and OH-terminated (hydrophilic) self-assembled monolayers (SAMs), where adsorption is strongest on hydrophobic SAMs because of orientationally specific interactions with Dopa. Additional umbrella-sampling simulations yield free-energy profiles that quantitatively agree with SFA measurements and are used to extract the adhesive properties of individual amino acids within the context of MFP-3s peptide adhesion, revealing a delicate balance between van der Waals, hydrophobic, and electrostatic forces.

Aggregation of Chameleon Peptides: Implications of α-Helicity in Fibril Formation.

We investigate the relationship between the inherent secondary structure and aggregation propensity of peptides containing chameleon sequences (i.e., sequences that can adopt either α or ß structure depending on context) using a combination of replica exchange molecular dynamics simulations, ion-mobility mass spectrometry, circular dichroism, and transmission electron microscopy. We focus on an eight-residue long chameleon sequence that can adopt an α-helical structure in the context of the iron-binding protein from Bacillus anthracis (PDB id 1JIG ) and a ß-strand in the context of the baculovirus P35 protein (PDB id 1P35 ). We show that the isolated chameleon sequence is intrinsically disordered, interconverting between α-helical and ß-rich conformations. The inherent conformational plasticity of the sequence can be constrained by addition of flanking residues with a given secondary structure propensity. Intriguingly, we show that the chameleon sequence with helical flanking residues aggregates rapidly into fibrils, whereas the chameleon sequence with flanking residues that favor ß-conformations has weak aggregation propensity. This work sheds new insights into the possible role of α-helical intermediates in fibril formation.

Human Islet Amyloid Polypeptide N-Terminus Fragment Self-Assembly: Effect of Conserved Disulfide Bond on Aggregation Propensity.

Amyloid formation by human islet amyloid polypeptide (hIAPP) has long been implicated in the pathogeny of type 2 diabetes mellitus (T2DM) and failure of islet transplants, but the mechanism of IAPP self-assembly is still unclear. Numerous fragments of hIAPP are capable of self-association into oligomeric aggregates, both amyloid and non-amyloid in structure. The N-terminal region of IAPP contains a conserved disulfide bond between cysteines at position 2 and 7, which is important to hIAPP's in vivo function and may play a role in in vitro aggregation. The importance of the disulfide bond in this region was probed using a combination of ion mobility-based mass spectrometry experiments, molecular dynamics simulations, and high-resolution atomic force microscopy imaging on the wildtype 1-8 hIAPP fragment, a reduced fragment with no disulfide bond, and a fragment with both cysteines at positions 2 and 7 mutated to serine. The results indicate the wildtype fragment aggregates by a different pathway than either comparison peptide and that the intact disulfide bond may be protective against aggregation due to a reduction of inter-peptide hydrogen bonding. Graphical Abstract ᅟ.