Defining a Physical Basis for Diversity in Protein Self-Assemblies Using a Minimal Model

Bioinspired Flexible Hydrogelation with Programmable Properties for Tactile Sensing

Tactile sensing requires integrated detection platforms with distributed and highly sensitive haptic sensing capabilities along with biocompatibility, aiming to replicate the physiological functions of the human skin and empower industrial robotic and prosthetic wearers to detect tactile information. In this regard, short peptide-based self-assembled hydrogels show promising potential to act as bioinspired supramolecular substrates for developing tactile sensors showing biocompatibility and biodegradability. However, the intrinsic difficulty to modulate the mechanical properties severely restricts their extensive employment. Herein, by controlling the self-assembly of 9-fluorenylmethoxycarbonyl-modifid diphenylalanine (Fmoc-FF) through introduction of polyethylene glycol diacrylate (PEGDA), wider nanoribbons are achieved by untwisting from well-established thinner nanofibers, and the mechanical properties of the supramolecular hydrogels can be enhanced 10-fold, supplying bioinspired supramolecular encapsulating substrate for tactile sensing. Furthermore, by doping with poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) and 9-fluorenylmethoxycarbonyl-modifid 3,4-dihydroxy-l-phenylalanine (Fmoc-DOPA), the Fmoc-FF self-assembled hydrogels can be engineered to be conductive and adhesive, providing bioinspired sensing units and adhesive layer for tactile sensing applications. Therefore, the integration of these modules results in peptide hydrogelation-based tactile sensors, showing high sensitivity and sustainable responses with intrinsic biocompatibility and biodegradability. The findings establish the feasibility of developing programmable peptide self-assembly with adjustable features for tactile sensing applications.

Challenges in studying the liquid-to-solid phase transitions of proteins using computer simulations

"Membraneless organelles," also referred to as biomolecular condensates, perform a variety of cellular functions and their dysregulation is implicated in cancer and neurodegeneration. In the last two decades, liquid-liquid phase separation (LLPS) of intrinsically disordered and multidomain proteins has emerged as a plausible mechanism underlying the formation of various biomolecular condensates. Further, the occurrence of liquid-to-solid transitions within liquid-like condensates may give rise to amyloid structures, implying a biophysical link between phase separation and protein aggregation. Despite significant advances, uncovering the microscopic details of liquid-to-solid phase transitions using experiments remains a considerable challenge and presents an exciting opportunity for the development of computational models which provide valuable, complementary insights into the underlying phenomenon. In this review, we first highlight recent biophysical studies which provide new insights into the molecular mechanisms underlying liquid-to-solid (fibril) phase transitions of folded, disordered and multi-domain proteins. Next, we summarize the range of computational models used to study protein aggregation and phase separation. Finally, we discuss recent computational approaches which attempt to capture the underlying physics of liquid-to-solid transitions along with their merits and shortcomings.

Phosphorylation sites are evolutionary checkpoints against liquid-solid transition in protein condensates

Assemblies of multivalent RNA-binding protein fused in sarcoma (FUS) can exist in the functional liquid-like state as well as less dynamic and potentially toxic amyloid- and hydrogel-like states. How could then cells form liquid-like condensates while avoiding their transformation to amyloids? Here, we show how posttranslational phosphorylation can provide a "handle" that prevents liquid-solid transition of intracellular condensates containing FUS. Using residue-specific coarse-grained simulations, for 85 different mammalian FUS sequences, we show how the number of phosphorylation sites and their spatial arrangement affect intracluster dynamics preventing conversion to amyloids. All atom simulations further confirm that phosphorylation can effectively reduce the β-sheet propensity in amyloid-prone fragments of FUS. A detailed evolutionary analysis shows that mammalian FUS PLDs are enriched in amyloid-prone stretches compared to control neutrally evolved sequences, suggesting that mammalian FUS proteins evolved to self-assemble. However, in stark contrast to proteins that do not phase-separate for their function, mammalian sequences have phosphosites in close proximity to these amyloid-prone regions. These results suggest that evolution uses amyloid-prone sequences in prion-like domains to enhance phase separation of condensate proteins while enriching phosphorylation sites in close proximity to safeguard against liquid-solid transitions.

Inhibition of Amyloid Nucleation by Steric Hindrance

Despite recent experiments and simulations suggesting that small-molecule inhibitors and some post-translational modifications (e.g., glycosylation and ubiquitination) can suppress the pathogenic aggregation of proteins due to steric hindrance, the effect of steric hindrance on amyloid formation has not been systematically studied. Based on Monte Carlo simulations using a coarse-grained model for amyloidogenic proteins and a hard sphere acting as steric hindrance, we investigated how steric hindrance on proteins could affect amyloid formation, particularly two steps of primary nucleation, namely, oligomerization and conformational conversion into a β-sheet-enriched nucleus. We found that steric spheres played an inhibitory role in oligomerization with the effect proportional to the sphere radius R_S, which we attributed to the decline in the nonspecific attractions between proteins. During the second step, small steric spheres facilitated the conformational conversion of proteins while large ones suppressed the conversion. The overall steric effect on amyloid nucleation was inhibitory regardless of R_S. As R_S increased, oligomeric assemblies changed from amorphous into sheet-like, structurally ordered species, reminiscent of the structure of amyloid fibrils. The oligomers with large R_S were off-pathway with their ordered structures induced by the competition between steric hindrance and nonspecific attractions of soluble proteins. Interestingly, the equimolar mixture of proteins with and without steric hindrance amplified the sterically inhibitory effect by increasing the energy barrier of protein's conformational conversion. The physical mechanisms and biological implications of the above results are discussed. Our findings improve the current understanding of how nature regulates protein aggregation and amyloid formation by steric hindrance.

Side Chain Geometry Determines the Fibrillation Propensity of a Minimal Two-Beads-per-Residue Peptide Model

The molecular mechanism of fibrillation is an important issue for understanding peptide aggregation. In our previous work, we demonstrated that the interchain attraction and intrachain bending stiffness control the aggregation kinetics and transient aggregate morphologies of a one-bead-per-residue implicit solvent peptide model. However, that model did not lead to fibrillation. In this work, we study the molecular origin of fibril formation using a two-beads-per-residue model, where one bead represents the backbone residue atoms and the other the side chain atoms. We show that the side chain geometry determines the fibrillation propensity that is further modulated by the modified terminal beads. This allows us to bring out the effects of side chain geometry and terminal capping on the fibrillation propensity. Our model does not assume a secondary structure and is, perhaps, the simplest bead-based chain model leading to fibrillation.

The physics of liquid-to-solid transitions in multi-domain protein condensates

Many RNA-binding proteins (RBPs) that assemble into membraneless organelles have a common architecture including disordered prion-like domain (PLD) and folded RNA-binding domain (RBD). An enrichment of PLD within the condensed phase gives rise to formation, on longer time scales, of amyloid-like fibrils (aging). In this study, we employ coarse-grained Langevin dynamics simulations to explore the physical basis for the structural diversity in condensed phases of multi-domain RBPs. We discovered a highly cooperative first-order transition between disordered structures and an ordered phase whereby chains of PLD organize in fibrils with high nematic orientational order. An interplay between homodomain (PLD-PLD) and heterodomain (PLD-RBD) interactions results in variety of structures with distinct spatial architectures. Interestingly, the different structural phases also exhibit vastly different intracluster dynamics of proteins, with diffusion coefficients 5 times (disordered structures) to 50 times (ordered structures) lower than that of the dilute phase. Cooperativity of this liquid-solid transition makes fibril formation highly malleable to mutations or post-translational modifications. Our results provide a mechanistic understanding of how multi-domain RBPs could form assemblies with distinct structural and material properties.

Role of non-specific interactions in the phase-separation and maturation of macromolecules

Phase separation of biomolecules could be mediated by both specific and non-specific interactions. How the interplay between non-specific and specific interactions along with polymer entropy influences phase separation is an open question. We address this question by simulating self-associating molecules as polymer chains with a short core stretch that forms the specifically interacting functional interface and longer non-core regions that participate in non-specific/promiscuous interactions. Our results show that the interplay of specific (strength, ϵsp) and non-specific interactions (strength, ϵns) could result in phase separation of polymers and its transition to solid-like aggregates (mature state). In the absence of ϵns, the polymer chains do not dwell long enough in the vicinity of each other to undergo phase separation and transition into a mature state. On the other hand, in the limit of strong ϵns, the assemblies cannot transition into the mature state and form a non-specific assembly, suggesting an optimal range of interactions favoring mature multimers. In the scenario where only a fraction (Nfrac) of the non-core regions participate in attractive interactions, we find that slight modifications to either ϵns or Nfrac can result in dramatically altered self-assembled states. Using a combination of heterogeneous and homogeneous mix of polymers, we establish how this interplay between interaction energies dictates the propensity of biomolecules to find the correct binding partner at dilute concentrations in crowded environments.

Contact-Based Analysis of Aggregation of Intrinsically Disordered Proteins

We review the contact-based description of aggregation of intrinsically disordered proteins in coarse-grained and all-atom models. We consider polyglutamines and polyalanines at various concentrations of the peptides. We also study associations of two chains of α-synuclein and up to 20 chains of a 12-residue-long segment of protein tau. We demonstrate that the total number of two-chain association events (in an aggregate that comprises at least two chains) provides a useful measure of the propensity to aggregate. This measure is consistent, for instance, with the previously reported mass spectroscopy data. The distribution of the number of association events is given essentially by a power law as a function of the duration of these events. The corresponding exponent depends on the protein and the temperature but not on the concentration of the proteins.

Diverse Aggregation Kinetics Predicted by a Coarse-Grained Peptide Model

Protein and peptide aggregation is a ubiquitous phenomenon with implications in medicine, pharmaceutical industry, and materials science. An important issue in peptide aggregation is the molecular mechanism of aggregate nucleation and growth. In many experimental studies, sigmoidal kinetics curves show a clear lag phase ascribed to nucleation; however, experimental studies also show downhill kinetics curves, where the monomers decay continuously and no lag phase can be seen. In this work, we study peptide aggregation kinetics using a coarse-grained implicit solvent model introduced in our previous work. Our simulations explore the hypothesis that the interplay between interchain attraction and intrachain bending stiffness controls the aggregation kinetics and transient aggregate morphologies. Indeed, our model reproduces the aggregation modes seen in experiment: no observed aggregation, nucleated aggregation, and rapid downhill aggregation. We find that the interaction strength is the primary parameter determining the aggregation mode, whereas the stiffness is a secondary parameter modulating the transient morphologies and aggregation rates: more attractive and stiff chains aggregate more rapidly and the transient morphologies are more ordered. We also explore the effects of the initial monomer concentration and the chain length. As the concentration decreases, the aggregation mode shifts from downhill to nucleated and no-aggregation. This concentration effect is in line with an experimental observation that the transition between downhill and nucleated kinetics is concentration-dependent. We find that longer peptides can aggregate at conditions where short peptides do not aggregate at all. It supports an experimental observation that the elongation of a homopeptide, e.g., polyglutamine, can increase the aggregation propensity.

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 (Aβ, 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.

Chiral structure fluctuations predicted by a coarse-grained model of peptide aggregation

This work reports on the chiral structure fluctuations of peptide clusters at the early stages of aggregation in a coarse-grained peptide model. Our model reproduces a variety of aggregate structures, from disordered to crystal-like, that are observed experimentally. Unexpectedly, our molecular dynamics simulations showed that the small peptide cluster undergoes chiral structure fluctuations although the underlying implicit solvent model does not assume the chirality of peptides. The chiral fluctuations are quantified through a cluster twist parameter. A simple model is presented where the twist parameter undergoes a stochastic diffusion on a 1D potential surface. The shape of the potential surface changes with the cluster size. The model shows semi-quantitative agreement with the simulations. We hypothesize that the chiral fluctuations at the early stages of peptide aggregation can contribute to the selection of the final fibril structures.

Chain stiffness bridges conventional polymer and bio-molecular phases

Chain molecules play important roles in industry and in living cells. Our focus here is on distinct ways of modeling the stiffness inherent in a chain molecule. We consider three types of stiffnesses-one yielding an energy penalty for local bends (energetic stiffness) and the other two forbidding certain classes of chain conformations (entropic stiffness). Using detailed Wang-Landau microcanonical Monte Carlo simulations, we study the interplay between the nature of the stiffness and the ground state conformation of a self-attracting chain. We find a wide range of ground state conformations, including a coil, a globule, a toroid, rods, helices, and zig-zag strands resembling β-sheets, as well as knotted conformations allowing us to bridge conventional polymer phases and biomolecular phases. An analytical mapping is derived between the persistence lengths stemming from energetic and entropic stiffness. Our study shows unambiguously that different stiffnesses play different physical roles and have very distinct effects on the nature of the ground state of the conformation of a chain, even if they lead to identical persistence lengths.

Elucidating Self-Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein-Peptide Structural Characterization

Self-assembling and molecular folding are ubiquitous in Nature: they drive the organization of systems ranging from living creatures to DNA molecules. Elucidating the complex dynamics underlying these phenomena is of crucial importance. However, a tool for the analysis of the various phenomena involved in protein/peptide aggregation is still missing. Here, an innovative software is developed and validated for the identification and visualization of b-structuring and b-sheet formation in both simulated systems and crystal structures of proteins and peptides. The novel software suite, dubbed Morphoscanner, is designed to identify and intuitively represent b-structuring and b-sheet formation during molecular dynamics trajectories, paying attention to temporary strand-strand alignment, suboligomer formation and evolution of local order. Self-assembling peptides (SAPs) constitute a promising class of biomaterials and an interesting model to study the spontaneous assembly of molecular systems in vitro. With the help of coarse-grained molecular dynamics the self-assembling of diverse SAPs is simulated into molten aggregates. When applied to these systems, Morphoscanner highlights different b-structuring schemes and kinetics related to SAP sequences. It is demonstrated that Morphoscanner is a novel versatile tool designed to probe the aggregation dynamics of self-assembling systems, adaptable to the analysis of differently coarsened simulations of a variety of biomolecules.

Branched peptides integrate into self-assembled nanostructures and enhance biomechanics of peptidic hydrogels

Self-assembling peptides (SAP) have drawn an increasing interest in the tissue engineering community. They display unquestionable biomimetic properties, tailorability and promising biocompatibility. However their use has been hampered by poor mechanical properties making them fragile soft scaffolds. To increase SAP hydrogel stiffness we introduced a novel strategy based on multiple ramifications of (LDLK)₃, a well-known linear SAP, connected with one or multiple "lysine knots". Differently branched SAPs were tested by increasing the number of (LDLK)₃-like branches and by adding the neuro-regenerative functional motif BMHP1 as a single branch. While pure branched peptides did not have appealing self-assembling propensity, when mixed with the corresponding linear SAP they increased the stiffness of the overall hydrogel of multiple times. Notably, optimal results (or peak) were obtained 1) at similar molar ratio (between linear and branched peptides) for all tested sequences and 2) for the branched SAPs featuring the highest number of branches made of (LDLK)₃. The functional motif BMHP1, as expected, seemed not to contribute to the increase of the storage modulus as efficiently as (LDLK)₃. Interestingly, branched SAPs improved the β-sheet self-arrangement of (LDLK)₃ and allowed for the formation of assembled nanofibers. Indeed in coarse-grained molecular dynamics we showed they readily integrate in the assembled aggregates providing "molecular connections" among otherwise weakly paired β-structures. Lastly, branched SAPs did not affect the usual response of human neural stem cells cultured on (LDLK)₃-like scaffolds in vitro. Hence, branched SAPs may be a valuable new tool to enhance mechanical properties of self-assembling peptide biomaterials harmlessly; as neither chemical nor enzymatic cross-linking reactions are involved. As a consequence, branched SAPs may enlarge the field of application of SAPs in tissue engineering and beyond.

STATEMENT OF SIGNIFICANCE

Self-assembling peptides stand at the forefront of regenerative medicine because they feature biomimetic nano-architectures that mimic the complexity of natural peptide-based extracellular matrices of living tissues. Their superior biocompatibility and ease of scale-up production are hampered by weak mechanical properties due to transient non-covalent interactions among and within the self-assembled peptide chains, thus limiting their potential applications. We introduced new branched self-assembling peptides to be used as "molecular connectors" among self-assembled nanostructures made of linear SAPs. Branched SAPs could be mixed with linear SAPs before self-assembling in order to have them intermingled with different β-sheets of linear SAPs after gelation. This strategy caused a manifold increase of the stiffness of the assembled hydrogels (proportional to the number of self-assembling branches), did not affect SAP propensity to form β-sheet but, instead, further stimulated their secondary structure rearrangements. It is now possible to modularly improve SAP scaffold mechanical properties without using harmful chemical reactions. Therefore, branched SAPs represent an additional tool to be adopted for efficient and harmless SAP scaffold customization in tissue engineering.

Self-assembly of model proteins into virus capsids

We consider self-assembly of proteins into a virus capsid by the methods of molecular dynamics. The capsid corresponds either to SPMV or CCMV and is studied with and without the RNA molecule inside. The proteins are flexible and described by the structure-based coarse-grained model augmented by electrostatic interactions. Previous studies of the capsid self-assembly involved solid objects of a supramolecular scale, e.g. corresponding to capsomeres, with engineered couplings and stochastic movements. In our approach, a single capsid is dissociated by an application of a high temperature for a variable period and then the system is cooled down to allow for self-assembly. The restoration of the capsid proceeds to various extent, depending on the nature of the dissociated state, but is rarely complete because some proteins depart too far unless the process takes place in a confined space.

Kinetics-Controlled Amphiphile Self-Assembly Processes

Amphiphile self-assembly is an essential bottom-up approach of fabricating advanced functional materials. Self-assembled materials with desired structures are often obtained through thermodynamic control. Here, we demonstrate that the selection of kinetic pathways can lead to drastically different self-assembled structures, underlining the significance of kinetic control in self-assembly. By constructing kinetic network models from large-scale molecular dynamics simulations, we show that two largely similar amphiphiles, 1-[11-oxo-11-(pyren-1-ylmethoxy)-undecyl]pyridinium bromide (PYR) and 1-(11-((5a1,8a-dihydropyren-1-yl)methylamino)-11-oxoundecyl)pyridinium bromide (PYN), prefer distinct kinetic assembly pathways. While PYR prefers an incremental growth mechanism and forms a nanotube, PYN favors a hopping growth pathway leading to a vesicle. Such preference was found to originate from the subtle difference in the distributions of hydrophobic and hydrophilic groups in their chemical structures, which leads to different rates of the adhesion process among the aggregating micelles. Our results are in good agreement with experimental results, and accentuate the role of kinetics in the rational design of amphiphile self-assembly.