Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memory

Generating the polymorph landscapes of amyloid fibrils using AI: RibbonFold

The concept that proteins are selected to fold into a well-defined native state has been effectively addressed within the framework of energy landscapes, underpinning the recent successes of structure prediction tools like AlphaFold. The amyloid fold, however, does not represent a unique minimum for a given single sequence. While the cross-β hydrogen-bonding pattern is common to all amyloids, other aspects of amyloid fiber structures are sensitive not only to the sequence of the aggregating peptides but also to the experimental conditions. This polymorphic nature of amyloid structures challenges structure predictions. In this paper, we use AI to explore the landscape of possible amyloid protofilament structures composed of a single stack of peptides aligned in a parallel, in-register manner. This perspective enables a practical method for predicting protofilament structures of arbitrary sequences: RibbonFold. RibbonFold is adapted from AlphaFold2, incorporating parallel in-register constraints within AlphaFold2's template module, along with an appropriate polymorphism loss function to address the structural diversity of folds. RibbonFold outperforms AlphaFold2/3 on independent test sets, achieving a mean TM-score of 0.5. RibbonFold proves well-suited to study the polymorphic landscapes of widely studied sequences with documented polymorphisms. The resulting landscapes capture these observed polymorphisms effectively. We show that while well-known amyloid-forming sequences exhibit a limited number of plausible polymorphs on their "solubility" landscape, randomly shuffled sequences with the same composition appear to be negatively selected in terms of their relative solubility. RibbonFold is a valuable framework for structurally characterizing amyloid polymorphism landscapes.

Invasive mussels fashion silk-like byssus via mechanical processing of massive horizontally acquired coiled coils

Zebra and quagga mussels (Dreissena spp.) are invasive freshwater biofoulers that perpetrate devastating economic and ecological impact. Their success depends on their ability to anchor onto substrates with protein-based fibers known as byssal threads. Yet, compared to other mussel lineages, little is understood about the proteins comprising their fibers or their evolutionary history. Here, we investigated the hierarchical protein structure of Dreissenid byssal threads and the process by which they are fabricated. Unique among bivalves, we found that threads possess a predominantly β-sheet crystalline structure reminiscent of spider silk. Further analysis revealed unexpectedly that the Dreissenid thread protein precursors are mechanoresponsive α-helical proteins that are mechanically processed into β-crystallites during thread formation. Proteomic analysis of the byssus secretory organ and byssus fibers revealed a family of ultrahigh molecular weight (354 to 467 kDa) asparagine-rich (19 to 20%) protein precursors predicted to form α-helical coiled coils. Moreover, several independent lines of evidence indicate that the ancestral predecessor of these proteins was likely acquired via horizontal gene transfer. This chance evolutionary event that transpired at least 12 Mya has endowed Dreissenids with a distinctive and effective fiber formation mechanism, contributing significantly to their success as invasive species and possibly, inspiring new materials design.

Exploring the structural acrobatics of fold-switching proteins using simplified structure-based models

Metamorphic proteins are a paradigm of the protein folding process, by encoding two or more native states, highly dissimilar in terms of their secondary, tertiary, and even quaternary structure, on a single amino acid sequence. Moreover, these proteins structurally interconvert between these native states in a reversible manner at biologically relevant timescales as a result of different environmental cues. The large-scale rearrangements experienced by these proteins, and their sometimes high mass interacting partners that trigger their metamorphosis, makes the computational and experimental study of their structural interconversion challenging. Here, we present our efforts in studying the refolding landscapes of two quintessential metamorphic proteins, RfaH and KaiB, using simplified dual-basin structure-based models (SBMs), rigorously footed on the energy landscape theory of protein folding and the principle of minimal frustration. By using coarse-grained models in which the native contacts and bonded interactions extracted from the available experimental structures of the two native states of RfaH and KaiB are merged into a single Hamiltonian, dual-basin SBM models can be generated and savvily calibrated to explore their fold-switch in a reversible manner in molecular dynamics simulations. We also describe how some of the insights offered by these simulations have driven the design of experiments and the validation of the conformational ensembles and refolding routes observed using this simple and computationally efficient models.

Finite element modeling of alpha-helices and tropocollagen molecules with reference to the spike of SARS-CoV-2

The newly developed finite element modeling at the atomic scale was used to predict the static and dynamic response of the alpha-helix (AH) and tropocollagen (TC) protein fragments, the main building blocks of the spike of the SARS-CoV-2. The geometry and morphology of the spike's stalk and its connection to the viral envelope were determined from the combination of most recent Molecular Dynamics simulation and images of Cryo-Electron microscope. The stiffness parameters of the covalent bonds in the main chain of the helix were taken from the literature. The AH and TC were modeled using both beam elements (wire model) and shell elements (ribbon model) in finite element analysis to predict their mechanical properties under tension. The asymptotic stiffening features of AH and TC under tensile loading were revealed and compared with a new analytical solution. The mechanical stiffnesses under other loading conditions, including compression, torsion and bending were also predicted numerically and correlated with the results of the existing MD simulations and tests. The mode shapes and natural frequencies of the spike were predicted using the built FE model. The frequencies were shown to be within the safe range of 1-20 MHz routinely used for medical imaging and diagnosis by means of ultrasound. These results provide a solid theoretical basis for using ultrasound to study damaging coronavirus through transient and resonant vibration at large deformations.

A coarse-grained approach to model the dynamics of the actomyosin cortex

Background

The dynamics of the actomyosin machinery is at the core of many important biological processes. Several relevant cellular responses such as the rhythmic compression of the cell cortex are governed, at a mesoscopic level, by the nonlinear interaction between actin monomers, actin crosslinkers, and myosin motors. Coarse-grained models are an optimal tool to study actomyosin systems, since they can include processes that occur at long time and space scales, while maintaining the most relevant features of the molecular interactions.

Results

Here, we present a coarse-grained model of a two-dimensional actomyosin cortex, adjacent to a three-dimensional cytoplasm. Our simplified model incorporates only well-characterized interactions between actin monomers, actin crosslinkers and myosin, and it is able to reproduce many of the most important aspects of actin filament and actomyosin network formation, such as dynamics of polymerization and depolymerization, treadmilling, network formation, and the autonomous oscillatory dynamics of actomyosin.

Conclusions

We believe that the present model can be used to study the in vivo response of actomyosin networks to changes in key parameters of the system, such as alterations in the attachment of actin filaments to the cell cortex.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12915-022-01279-2).

Divergent CPEB prion-like domains reveal different assembly mechanisms for a generic amyloid-like fold

BACKGROUND

Amyloids are ordered, insoluble protein aggregates, characterized by a cross-β sheet quaternary structure in which molecules in a β-strand conformation are stacked along the filament axis via intermolecular interactions. While amyloids are typically associated with pathological conditions, functional amyloids have also been identified and are present in a wide variety of organisms ranging from bacteria to humans. The cytoplasmic polyadenylation element-binding (CPEB) prion-like protein is an mRNA-binding translation regulator, whose neuronal isoforms undergo activity-dependent aggregation, a process that has emerged as a plausible biochemical substrate for memory maintenance. CPEB aggregation is driven by prion-like domains (PLD) that are divergent in sequence across species, and it remains unknown whether such divergent PLDs follow a similar aggregating assembly pathway. Here, we describe the amyloid-like features of the neuronal Aplysia CPEB (ApCPEB) PLD and compare them to those of the Drosophila ortholog, Orb2 PLD.

RESULTS

Using in vitro single-molecule and bulk biophysical methods, we find transient oligomers and mature amyloid-like filaments that suggest similarities in the late stages of the assembly pathway for both ApCPEB and Orb2 PLDs. However, while prior to aggregation the Orb2 PLD monomer remains mainly as a random coil in solution, ApCPEB PLD adopts a diversity of conformations comprising α-helical structures that evolve to coiled-coil species, indicating structural differences at the beginning of their amyloid assembly pathways.

CONCLUSION

Our results indicate that divergent PLDs of CPEB proteins from different species retain the ability to form a generic amyloid-like fold through different assembly mechanisms.

Dimerization of α-Synuclein Fragments Studied by Isothermal-Isobaric Replica-Permutation Molecular Dynamics Simulation

Aggregates and fibrils of intrinsically disordered α-synuclein are associated with Parkinson's disease. Within a non-amyloid β component (NAC) spanning from the 61st to the 95th residue of α-synuclein, an 11-residue segment called NACore (₆₈GAVVTGVTAVA₇₈) is an essential region for both fibril formation and cytotoxicity. Although NACore peptides alone are known to form aggregates and amyloid fibrils, the mechanisms of aggregation and fibrillation remain unknown. This study investigated the dimerization process of NACore peptides as the initial stage of the aggregation and fibrillation processes. We performed an isothermal-isobaric replica-permutation molecular dynamics simulation, which is one of the efficient sampling methods, for the two NACore peptides in explicit water over 96 μs. The simulation succeeded in sampling a variety of dimer structures. An analysis of secondary structure revealed that most of the NACore dimers form intermolecular β-bridges. In particular, more antiparallel β-bridges were observed than parallel β-bridges. We also found that intramolecular secondary structures such as α-helix and antiparallel β-bridge are stabilized in the pre-dimer state. However, we identified that the intermolecular β-bridges tend to form directly between residues with no specific structure rather than via the intramolecular β-bridges. This is because the NACore peptides still have a low propensity to form the intramolecular secondary structures even though they are stabilized in the pre-dimer state.

Coiled-Coil Motifs of RNA-Binding Proteins: Dynamicity in RNA Regulation

Neuronal granules are biomolecular condensates that concentrate high quantities of RNAs and RNA-related proteins within neurons. These dense packets of information are trafficked from the soma to distal sites rich in polysomes, where local protein synthesis can occur. Movement of neuronal granules to distal sites, and local protein synthesis, play a critical role in synaptic plasticity. The formation of neuronal granules is intriguing; these granules lack a membrane and instead phase separate due to protein and RNA interactions. Low complexity motifs and RNA binding domains are highly prevalent in these proteins. Here, we introduce the role that coiled-coil motifs play in neuronal granule proteins, and investigate the structure-function relationship of coiled-coil proteins in RNA regulation. Interestingly, low complexity domains and coiled-coil motifs are highly dynamic, allowing for increased functional response to environmental influences. Finally, biomolecular condensates have been suggested to drive the formation of toxic, neurodegenerative proteins such as TDP-43 and tau. Here, we review the conversion of coiled-coil motifs to amyloid structures, and speculate a role that neuronal granules play in coiled-coil to amyloid conversions of neurodegenerative proteins.

Exploring the F-actin/CPEB3 interaction and its possible role in the molecular mechanism of long-term memory

Dendritic spines are tiny membranous protrusions on the dendrites of neurons. Dendritic spines change shape in response to input signals, thereby strengthening the connections between neurons. The growth and stabilization of dendritic spines is thought to be essential for maintaining long-term memory. Actin cytoskeleton remodeling in spines is a key element of their formation and growth. More speculatively, the aggregation of CPEB3, a functional prion that binds RNA, has been reported to be involved in the maintenance of long-term memory. Here we study the interaction between actin and CPEB3 and propose a molecular model for the complex structure of CPEB3 and an actin filament (F-actin). The results of our computational modeling, including both energetic and structural analyses, are compared with novel data from peptide array experiments. Our model of the CPEB3/F-actin interaction suggests that F-actin potentially triggers the aggregation-prone structural transition of a short CPEB3 sequence by zipping it into a beta-hairpin form. We also propose that the CPEB3/F-actin interaction might be regulated by the SUMOylation of CPEB3, based on bioinformatic searches for potential SUMOylation sites as well as SUMO interacting motifs in CPEB3. On the basis of these results and the existing literature, we put forward a possible molecular mechanism underlying long-term memory that involves CPEB3's binding to actin, its aggregation, and its regulation by SUMOylation.

A continuous model of physiological prion aggregation suggests a role for Orb2 in gating long-term synaptic information

The regulation of mRNA translation at the level of the synapse is believed to be fundamental in memory and learning at the cellular level. The family of cytoplasmic polyadenylation element binding (CPEB) proteins emerged as an important RNA-binding protein family during development and in adult neurons. Drosophila Orb2 (homologue of mouse CPEB3 protein and of the neural isoform of Aplysia CPEB) has been found to be involved in the translation of plasticity-dependent mRNAs and has been associated with long-term memory. Orb2 protein presents two main isoforms, Orb2A and Orb2B, which form an activity-induced amyloid-like functional aggregate, thought to be the translation-inducing state of the RNA-binding protein. Here we present a first two-states continuous differential model for Orb2A-Orb2B aggregation. This model provides new working hypotheses for studying the role of prion-like CPEB proteins in long-term synaptic plasticity. Moreover, this model can be used as a first step to integrate translation- and protein aggregation-dependent phenomena in synaptic facilitation rules.

Template-Guided Protein Structure Prediction and Refinement Using Optimized Folding Landscape Force Fields

When good structural templates can be identified, template-based modeling is the most reliable way to predict the tertiary structure of proteins. In this study, we combine template-based modeling with a realistic coarse-grained force field, AWSEM, that has been optimized using the principles of energy landscape theory. The Associative memory, Water mediated, Structure and Energy Model (AWSEM) is a coarse-grained force field having both transferable tertiary interactions and knowledge-based local-in-sequence interaction terms. We incorporate template information into AWSEM by introducing soft collective biases to the template structures, resulting in a model that we call AWSEM-Template. Structure prediction tests on eight targets, four of which are in the low sequence identity "twilight zone" of homology modeling, show that AWSEM-Template can achieve high-resolution structure prediction. Our results also confirm that using a combination of AWSEM and a template-guided potential leads to more accurate prediction of protein structures than simply using a template-guided potential alone. Free energy profile analyses demonstrate that the soft collective biases to the template effectively increase funneling toward native-like structures while still allowing significant flexibility so as to allow for correction of discrepancies between the target structure and the template. A further stage of refinement using all-atom molecular dynamics augmented with soft collective biases to the structures predicted by AWSEM-Template leads to a further improvement of both backbone and side-chain accuracy by maintaining sufficient flexibility but at the same time discouraging unproductive unfolding events often seen in unrestrained all-atom refinement simulations. The all-atom refinement simulations also reduce patches of frustration of the initial predictions. Some of the backbones found among the structures produced during the initial coarse-grained prediction step already have CE-RMSD values of less than 3 Å with 90% or more of the residues aligned to the experimentally solved structure for all targets. All-atom structures generated during the following all-atom refinement simulations, which started from coarse-grained structures that were chosen without reference to any knowledge about the native structure, have CE-RMSD values of less than 2.5 Å with 90% or more of the residues aligned for 6 out of 8 targets. Clustering low energy structures generated during the initial coarse-grained annealing picks out reliably structures that are within 1 Å of the best sampled structures in 5 out of 8 cases. After the all-atom refinement, structures that are within 1 Å of the best sampled structures can be selected using a simple algorithm based on energetic features alone in 7 out of 8 cases.

The Associative Memory, Water Mediated, Structure and Energy Model (AWSEM)-Amylometer: Predicting Amyloid Propensity and Fibril Topology Using an Optimized Folding Landscape Model

Amyloids are fibrillar protein aggregates with simple repeated structural motifs in their cores, usually β-strands but sometimes α-helices. Identifying the amyloid-prone regions within protein sequences is important both for understanding the mechanisms of amyloid-associated diseases and for understanding functional amyloids. Based on the crystal structures of seven cross-β amyloidogenic peptides with different topologies and one recently solved cross-α fiber structure, we have developed a computational approach for identifying amyloidogenic segments in protein sequences using the Associative memory, Water mediated, Structure and Energy Model (AWSEM). The AWSEM-Amylometer performs favorably in comparison with other predictors in predicting aggregation-prone sequences in multiple data sets. The method also predicts well the specific topologies (the relative arrangement of β-strands in the core) of the amyloid fibrils. An important advantage of the AWSEM-Amylometer over other existing methods is its direct connection with an efficient, optimized protein folding simulation model, AWSEM. This connection allows one to combine efficient and accurate search of protein sequences for amyloidogenic segments with the detailed study of the thermodynamic and kinetic roles that these segments play in folding and aggregation in the context of the entire protein sequence. We present new simulation results that highlight the free energy landscapes of peptides that can take on multiple fibril topologies. We also demonstrate how the Amylometer methodology can be straightforwardly extended to the study of functional amyloids that have the recently discovered cross-α fibril architecture.

Trans-acting translational regulatory RNA binding proteins

The canonical molecular machinery required for global mRNA translation and its control has been well defined, with distinct sets of proteins involved in the processes of translation initiation, elongation and termination. Additionally, noncanonical, trans-acting regulatory RNA-binding proteins (RBPs) are necessary to provide mRNA-specific translation, and these interact with 5' and 3' untranslated regions and coding regions of mRNA to regulate ribosome recruitment and transit. Recently it has also been demonstrated that trans-acting ribosomal proteins direct the translation of specific mRNAs. Importantly, it has been shown that subsets of RBPs often work in concert, forming distinct regulatory complexes upon different cellular perturbation, creating an RBP combinatorial code, which through the translation of specific subsets of mRNAs, dictate cell fate. With the development of new methodologies, a plethora of novel RNA binding proteins have recently been identified, although the function of many of these proteins within mRNA translation is unknown. In this review we will discuss these methodologies and their shortcomings when applied to the study of translation, which need to be addressed to enable a better understanding of trans-acting translational regulatory proteins. Moreover, we discuss the protein domains that are responsible for RNA binding as well as the RNA motifs to which they bind, and the role of trans-acting ribosomal proteins in directing the translation of specific mRNAs. This article is categorized under: RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes Translation > Translation Regulation Translation > Translation Mechanisms.

The Wisdom of Networks: A General Adaptation and Learning Mechanism of Complex Systems: The Network Core Triggers Fast Responses to Known Stimuli; Innovations Require the Slow Network Periphery and Are Encoded by Core-Remodeling

I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the weakly connected network periphery. Upon repeated stimulus, peripheral network nodes remodel the network core that encodes the attractor of the new response. This "core-periphery learning" theory reviews and generalizes the heretofore fragmented knowledge on attractor formation by neural networks, periphery-driven innovation, and a number of recent reports on the adaptation of protein, neuronal, and social networks. The core-periphery learning theory may increase our understanding of signaling, memory formation, information encoding and decision-making processes. Moreover, the power of network periphery-related "wisdom of crowds" inventing creative, novel responses indicates that deliberative democracy is a slow yet efficient learning strategy developed as the success of a billion-year evolution. Also see the video abstract here: https://youtu.be/IIjP7zWGjVE.

Dynamic Transition from α-Helices to β-Sheets in Polypeptide Coiled-Coil Motifs

We carried out dynamic force manipulations in silico on a variety of coiled-coil protein fragments from myosin, chemotaxis receptor, vimentin, fibrin, and phenylalanine zippers that vary in size and topology of their α-helical packing. When stretched along the superhelical axis, all superhelices show elastic, plastic, and inelastic elongation regimes and undergo a dynamic transition from the α-helices to the β-sheets, which marks the onset of plastic deformation. Using the Abeyaratne-Knowles formulation of phase transitions, we developed a new theoretical methodology to model mechanical and kinetic properties of protein coiled-coils under mechanical nonequilibrium conditions and to map out their energy landscapes. The theory was successfully validated by comparing the simulated and theoretical force-strain spectra. We derived the scaling laws for the elastic force and the force for α-to-β transition, which can be used to understand natural proteins' properties as well as to rationally design novel biomaterials of required mechanical strength with desired balance between stiffness and plasticity.

Aggregation landscapes of Huntingtin exon 1 protein fragments and the critical repeat length for the onset of Huntington's disease

Huntington's disease (HD) is a neurodegenerative disease caused by an abnormal expansion in the polyglutamine (polyQ) track of the Huntingtin (HTT) protein. The severity of the disease depends on the polyQ repeat length, arising only in patients with proteins having 36 repeats or more. Previous studies have shown that the aggregation of N-terminal fragments (encoded by HTT exon 1) underlies the disease pathology in mouse models and that the HTT exon 1 gene product can self-assemble into amyloid structures. Here, we provide detailed structural mechanisms for aggregation of several protein fragments encoded by HTT exon 1 by using the associative memory, water-mediated, structure and energy model (AWSEM) to construct their free energy landscapes. We find that the addition of the N-terminal 17-residue sequence ([Formula: see text]) facilitates polyQ aggregation by encouraging the formation of prefibrillar oligomers, whereas adding the C-terminal polyproline sequence ([Formula: see text]) inhibits aggregation. The combination of both terminal additions in HTT exon 1 fragment leads to a complex aggregation mechanism with a basic core that resembles that found for the aggregation of pure polyQ repeats using AWSEM. At the extrapolated physiological concentration, although the grand canonical free energy profiles are uphill for HTT exon 1 fragments having 20 or 30 glutamines, the aggregation landscape for fragments with 40 repeats has become downhill. This computational prediction agrees with the critical length found for the onset of HD and suggests potential therapies based on blocking early binding events involving the terminal additions to the polyQ repeats.

Evolving Notch polyQ tracts reveal possible solenoid interference elements

Polyglutamine (polyQ) tracts in regulatory proteins are extremely polymorphic. As functional elements under selection for length, triplet repeats are prone to DNA replication slippage and indel mutations. Many polyQ tracts are also embedded within intrinsically disordered domains, which are less constrained, fast evolving, and difficult to characterize. To identify structural principles underlying polyQ tracts in disordered regulatory domains, here I analyze deep evolution of metazoan Notch polyQ tracts, which can generate alleles causing developmental and neurogenic defects. I show that Notch features polyQ tract turnover that is restricted to a discrete number of conserved “polyQ insertion slots”. Notch polyQ insertion slots are: (i) identifiable by an amphipathic “slot leader” motif; (ii) conserved as an intact C-terminal array in a 1-to-1 relationship with the N-terminal solenoid-forming ankyrin repeats (ARs); and (iii) enriched in carboxamide residues (Q/N), whose sidechains feature dual hydrogen bond donor and acceptor atoms. Correspondingly, the terminal loop and β-strand of each AR feature conserved carboxamide residues, which would be susceptible to folding interference by hydrogen bonding with residues outside the ARs. I thus suggest that Notch polyQ insertion slots constitute an array of AR interference elements (ARIEs). Notch ARIEs would dynamically compete with the delicate serial folding induced by adjacent ARs. Huntingtin, which harbors solenoid-forming HEAT repeats, also possesses a similar number of polyQ insertion slots. These results suggest that intrinsically disordered interference arrays featuring carboxamide and polyQ enrichment may constitute coupled proteodynamic modulators of solenoids.

Backbone Engineering within a Latent β-Hairpin Structure to Design Inhibitors of Polyglutamine Amyloid Formation

Candidates for the toxic molecular species in the expanded polyglutamine (polyQ) repeat diseases range from various types of aggregates to "misfolded" monomers. One way to vet these candidates is to develop mutants that restrict conformational landscapes. Previously, we inserted two self-complementary β-hairpin enhancing motifs into a short polyQ sequence to generate a mutant, here called "βHP," that exhibits greatly improved amyloid nucleation without measurably enhancing β-structure in the monomer ensemble. We extend these studies here by introducing single-backbone H-bond impairing modifications ^αN-methyl Gln or l-Pro at key positions within βHP. Modifications predicted to allow formation of a fully H-bonded β-hairpin at the fibril edge while interfering with H-bonding to the next incoming monomer exhibit poor amyloid formation and act as potent inhibitors in trans of simple polyQ peptide aggregation. In contrast, a modification that disrupts intra-β-hairpin H-bonding within βHP, while also aggregating poorly, is ineffective at inhibiting amyloid formation in trans. The inhibitors constitute a dynamic version of the edge-protection negative design strategy used in protein evolution to limit unwanted protein aggregation. Our data support a model in which polyQ peptides containing strong β-hairpin encouraging motifs only rarely form β-hairpin conformations in the monomer ensemble, but nonetheless take on such conformations at key steps during amyloid formation. The results provide insights into polyQ solution structure and fibril formation while also suggesting an approach to the design of inhibitors of polyQ amyloid growth that focuses on conformational requirements for fibril and nucleus elongation.

Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for α/β Proteins

The atomistic associative memory, water mediated, structure and energy model (AAWSEM) is an efficient coarse-grained force field with transferable tertiary interactions that incorporates local in sequence energetic biases using structural information derived from all-atom simulations of long segments of the protein. For α helical proteins, the accuracy of structure prediction using AAWSEM has been established previously. In this article, we examine the capability of AAWSEM to predict the structure of α/β proteins. We also elaborate on an iterative approach that uses the structures from a first round of AAWSEM simulation as fragment memories. This iterative scheme improves the quality of the structure prediction and makes the free energy profile more funneled toward native configurations. We explore the use of clustering analyses as a way of evaluating the confidence in various structure prediction models. Clustering using a local relative order parameter (mutual Q) of the predicted structural ensemble turns out to be optimal. The tightest cluster according to mutual Q generally has the most correctly folded structure. Since there is no bioinformatic input, AAWSEM amounts to an ab initio protein structure prediction method that combines the efficiency of coarse-grained simulations with the local structural accuracy that can be achieved from all-atom simulations.

The Aggregation Free Energy Landscapes of Polyglutamine Repeats

Aggregates of proteins containing polyglutamine (polyQ) repeats are strongly associated with several neurodegenerative diseases. The length of the repeats correlates with the severity of the disease. Previous studies have shown that pure polyQ peptides aggregate by nucleated growth polymerization and that the size of the critical nucleus (n*) decreases from tetrameric to dimeric and monomeric as length increases from Q₁₈ to Q₂₆. Why the critical nucleus size changes with repeat-length has been unclear. Using the associative memory, water-mediated, structure and energy model, we construct the aggregation free energy landscapes for polyQ peptides of different repeat-lengths. These studies show that the monomer of the shorter repeat-length (Q₂₀) prefers an extended conformation and that its aggregation indeed has a trimeric nucleus (n* ∼ 3), while a longer repeat-length monomer (Q₃₀) prefers a β-hairpin conformation which then aggregates in a downhill fashion at 0.1 mM. For an intermediate length peptide (Q₂₆), there is an equal preference for hairpin and extended forms in the monomer which leads to a mixed inhomogeneous nucleation mechanism for fibrils. The predicted changes of monomeric structure and nucleation mechanism are confirmed by studying the aggregation free energy profile for a polyglutamine repeat with site-specific PG mutations that favor the hairpin form, giving results in harmony with experiments on this system.