Conformation Dependence of Diphenylalanine Self-Assembly Structures and Dynamics: Insights from Hybrid-Resolution Simulations

Recent progress in quantitative analysis of self-assembled peptides

Self-assembled peptides have been among the important biomaterials due to its excellent biocompatibility and diverse functions. Over the past decades, substantial progress and breakthroughs have been made in designing self-assembled peptides with multifaceted biomedical applications. The techniques for quantitative analysis, including imaging-based quantitative techniques, chromatographic technique and computational approach (molecular dynamics simulation), are becoming powerful tools for exploring the structure, properties, biomedical applications, and even supramolecular assembly processes of self-assembled peptides. However, a comprehensive review concerning these quantitative techniques remains scarce. In this review, recent progress in techniques for quantitative investigation of biostability, cellular uptake, biodistribution, self-assembly behaviors of self-assembled peptide etc., are summarized. Specific applications and roles of these techniques are highlighted in detail. Finally, challenges and outlook in this field are concluded. It is believed that this review will provide technical guidance for researchers in the field of peptide-based materials and pharmaceuticals, and facilitate related research for newcomers in this field.

Salt-induced Fmoc-tripeptide supramolecular hydrogels: a combined experimental and computational study of the self-assembly

Delving into the mechanism behind the molecular interactions at the atomic level of short-sequence peptides plays a key role in the development of nanomaterials with specific structure-property-function relationships from a bottom-up perspective. Due to their poor water solubility, the self-assembly of Fmoc-bearing peptides is usually induced by dissolution in an organic solvent, followed by a dilution step in water, pH changes, and/or a heating-cooling process. Herein, we report a straightforward methodology for the gelation of Fmoc-FFpY (F: phenylalanine; Y: tyrosine; and p: PO42-), a negatively charged tripeptide, in NaCl solution. The electrostatic interactions between Fmoc-FFpY and Na+ ions give rise to different nanofibrillar hydrogels with rheological properties and nanofiber sizes modulated by the NaCl concentration in pure aqueous media. Initiated by the electrostatic interactions between the peptide phosphate groups and the Na+ ions, the peptide self-assembly is stabilized thanks to hydrogen bonds between the peptide backbones and the π-π stacking of aromatic Fmoc and phenyl units. The hydrogels showed self-healing and thermo-responsive properties for potential biomedical applications. Molecular dynamics simulations from systems devoid of prior training not only confirm the aggregation of peptides at a critical salt concentration and the different interactions involved, but also corroborate the secondary structure of the hydrogels at the microsecond timescale. It is worth highlighting the remarkable achievement of reproducing the morphological behavior of the hydrogels using atomistic simulations. To our knowledge, this study is the first to report such a correspondence.

Enantiomer-Dependent Supramolecular Immunosuppressive Modulation for Tissue Reconstruction

Modulating the properties of biomaterials in terms of the host immune response is critical for tissue repair and regeneration. However, it is unclear how the preference for the cellular microenvironment manipulates the chiral immune responses under physiological or pathological conditions. Here, we reported that in vivo and in vitro oligopeptide immunosuppressive modulation was achieved by manipulation of macrophage polarization using chiral tetrapeptide (Ac-FFFK-OH, marked as FFFK) supramolecular polymers. The results suggested that chiral FFFK nanofibers can serve as a defense mechanism in the restoration of tissue homeostasis by upregulating macrophage M2 polarization via the Src-STAT6 axis. More importantly, transiently acting STAT6, insufficient to induce a sustained polarization program, then passes the baton to EGR2, thereby continuously maintaining the M2 polarization program. It is worth noting that the L-chirality exhibits a more potent effect in inducing macrophage M2 polarization than does the D-chirality, leading to enhanced tissue reconstruction. These findings elucidate the crucial molecular signals that mediate chirality-dependent supramolecular immunosuppression in damaged tissues while also providing an effective chiral supramolecular strategy for regulating macrophage M2 polarization and promoting tissue injury repair based on the self-assembling chiral peptide design.

Three Stages of Dynamic Assembly Process of Dipeptide-Based Supramolecular Gel Revealed by In Situ Infrared Spectroscopy

The exploration of short peptide-based assembly is vital for understanding protein-misfolding-associated diseases and seeking strategies to attenuate aggregate formation. While, the molecular mechanism of their structural evolution remains poorly studied in view of the dynamic and unpredictable assembly process. Herein, infrared (IR) spectroscopy, which serves as an in situ and real-time analytical technique, was intelligently employed to investigate the mechanism of phase transition and aggregate formation during the dynamic assembly process of diphenylalanine. Combined with other spectroscopy and electron microscopy technologies, three stages of gel formation and the main driving forces in different stages were revealed. A variety of stoichiometric methods such as continuous wavelet transform, principal component analysis, and two-dimensional correlation spectroscopy techniques were conducted to analyze the original time-dependent IR spectra to obtain detailed information on the changes in the amide bands and hydration layer. The microenvironment of hydrogen bonding among amide bands was significantly changed with the addition of pyridine derivatives, resulting in great differences in the properties of co-assembled gels. This work not only provides a universal analytical way to reveal the dynamic assembly process of dipeptide-based supramolecular gel but also expands their applications in supramolecular regulation and high-throughput screens in situ.

Piezoactive Bioorganic Diphenylalanine Films: Mechanism of Phase Formation

Self-organized peptides are unique materials with various applications in biology, medicine, and nanotechnology. Many of these applications require fabrication of homogeneous thin films having high piezoelectric effect and sufficiently low roughness. Recently, a facile method for the controlled deposition of flat solid films of the most studied peptide, diphenylalanine (FF), has been proposed, which is based on the crystallization of FF in the amorphous phase under the action of water vapor. This method is very advantageous compared with crystallization from a liquid phase reported previously. Here, we thoroughly investigate the mechanism of solid-state transformation from the amorphous to crystalline phase. The study revealed that the process proceeds in two distinct stages, maintaining clamped condition of self-assembling building blocks that preserve the films' morphology and high piezoelectric activity. We emphasize the critical role of water diffusion that governs two-dimensional growth of crystalline domains in FF films, merging in very dense, flat, and homogeneous films. These findings open a wide perspective for using this methodology for the direct fabrication of biofilms from the amorphous phase. We thus expect the application of these films to various nanotechnological applications of self-assembled structures.

Enhancing the Biopharmacological Characteristics of Asperosaponin VI: Unveiling Dynamic Self-Assembly Phase Transitions in the Gastrointestinal Environment

Purpose

Asperosaponin VI (ASP VI) as an active ingredient of Dipsacus asperoides, which has a wide range of biological and pharmacological activity. However, its development and application are restricted due to the poor gastrointestinal permeability and oral bioavailability. This investigation aims to reveal the influence of the self-assembled structure by the interaction between ASP VI and endogenous components NaTC and/or DOPC in the gastrointestinal environment on its biopharmaceutical properties, and novelty elucidated the molecular mechanism for the formation of self-assembled nanomicelles.

Methods

This change in phase state in gastrointestinal fluids is characterized by dynamic light scattering (DLS) and transmission electron microscope (TEM). UPLC-Q-TOF-MS was used to analyze the composition of phase components and the exposure of nanomicelles in vivo. Molecular dynamics simulation (MDS) was applied to preliminarily elucidate the self-assembly mechanism of ASP VI in the gastrointestinal environment. Furthermore, theS8 promoting absorption mechanism of nanomicelles were investigated through in vivo pharmacokinetic experiments, parallel artificial membrane permeability assay (PAMPA), quadruple single-pass intestinal perfusion in rats, and Caco-2 cell monolayer model.

Results

We demonstrated that the ASP VI could spontaneously form dynamic self-assembled structures with sodium taurocholate (NaTC) and dipalmitoyl phosphatidylcholine (DOPC) during gastrointestinal solubilization, which promoted the gastrointestinal absorption and permeability of ASP VI and increased its exposure in vivo, thus improving the biopharmacological characteristics of ASP VI. Moreover, ASP VI-NaTC-DOPC-self-assembled nanostructures (ASP VI-NaTC-DOPC-SAN) manifested higher cellular uptake in Caco-2 cells as evidenced by flow cytometry and confocal microscopy, and this study also preliminarily revealed the mechanism of self-assembly formation of ASP VI with endogenous components NaTC and DOPC driven by electrostatic and hydrogen bonding interactions.

Conclusion

This study provides evidence that the dynamic self-assembled phase transition may play a key role in improving the biopharmacological characteristics of insoluble or low permeability active ingredients during the gastrointestinal dissolution of Chinese medicines.

Deep Learning Empowers the Discovery of Self-Assembling Peptides with Over 10 Trillion Sequences

Self-assembling of peptides is essential for a variety of biological and medical applications. However, it is challenging to investigate the self-assembling properties of peptides within the complete sequence space due to the enormous sequence quantities. Here, it is demonstrated that a transformer-based deep learning model is effective in predicting the aggregation propensity (AP) of peptide systems, even for decapeptide and mixed-pentapeptide systems with over 10 trillion sequence quantities. Based on the predicted AP values, not only the aggregation laws for designing self-assembling peptides are derived, but the transferability relation among the APs of pentapeptides, decapeptides, and mixed pentapeptides is also revealed, leading to discoveries of self-assembling peptides by concatenating or mixing, as consolidated by experiments. This deep learning approach enables speedy, accurate, and thorough search and design of self-assembling peptides within the complete sequence space of oligopeptides, advancing peptide science by inspiring new biological and medical applications.

Geometric Transformations Afforded by Rotational Freedom in Aramid Amphiphile Nanostructures

Molecular self-assembly in water leads to nanostructure geometries that can be tuned owing to the highly dynamic nature of amphiphiles. There is growing interest in strongly interacting amphiphiles with suppressed dynamics, as they exhibit ultrastability in extreme environments. However, such amphiphiles tend to assume a limited range of geometries upon self-assembly due to the specific spatial packing induced by their strong intermolecular interactions. To overcome this limitation while maintaining structural robustness, we incorporate rotational freedom into the aramid amphiphile molecular design by introducing a diacetylene moiety between two aramid units, resulting in diacetylene aramid amphiphiles (D-AAs). This design strategy enables rotations along the carbon-carbon sp hybridized bonds of an otherwise fixed aramid domain. We show that varying concentrations and equilibration temperatures of D-AA in water lead to self-assembly into four different nanoribbon geometries: short, extended, helical, and twisted nanoribbons, all while maintaining robust structure with thermodynamic stability. We use advanced microscopy, X-ray scattering, spectroscopic techniques, and two-dimensional (2D) NMR to understand the relationship between conformational freedom within strongly interacting amphiphiles and their self-assembly pathways.

Machine Learning-Guided Adaptive Parametrization for Coupling Terms in a Mixed United-Atom/Coarse-Grained Model for Diphenylalanine Self-Assembly in Aqueous Ionic Liquids

Precise regulation of the peptide self-assembly into ordered nanostructures with intriguing properties has attracted intense attention. However, predicting peptide assembly at atomic resolution is a challenge due to both the structural flexibility of peptides and the associated huge computational costs. A machine learning-guided adaptive parametrization method was proposed for developing a mixed atomic and coarse-grained (CG) model through a multiobjective optimization strategy. Our model incorporates the united-atom (UA) model for diphenylalanine (P) and the polarizable electrostatic-variable coarse-grained (VaCG) model for aqueous ionic liquid [BMIM]+[BF4]- solution. In this mixed model, the coupling van der Waals (vdW) interaction is addressed by introducing virtual sites (VS) in the UA model to interact with solvent CG beads. The coupling parameters, including the electrostatic parameter and vdW parameters, are automatically optimized through ML-guided adaptive parametrization. The performance of this model was tested by some microstructural properties, e.g., the average number of P-P intermolecular hydrogen bonds (HBs) and radius distribution functions (RDFs) between P and different fragments of IL, in comparison with all-atom (AA) simulations. The computational cost is significantly reduced using such a parametrization scheme, which could search tens of thousands of force-field parameter sets, while needing only a small fraction of them to be assessed with molecular dynamics (MD) simulations. We used such a mixed resolution model to investigate the self-assembly in IL-water mixtures with variants of IL concentration (X). The long-range-ordered fibril structure is formed in a pure water system (X = 0). With an increase of IL concentrations, the formation of an ordered self-assembly nanostructure is prohibited, instead forming branched fibril at X = 2 mol % or amorphous aggregates when X > 10 mol %, resulting from the interplay between π-stacking and HB interactions between P and IL. The qualitative agreement between the simulated structures and the observed morphologies in experiments indicates the applicability of ML-guided parametrization strategy in the study of complex systems, such as polymers, lipid bilayers, and polysaccharides.

Helical-Like Assembly of Nateglinide as Coating for Oral Delivery of Insulin and Their Synergistic Prevention of Diabetes Mellitus

Oral delivery of antidiabetic active components promises to free millions of people from daily suffering who require routine injections. However, oral insulin (Ins) and other short-acting compounds such as nateglinide (NG) in harsh gastrointestinal tract still face great challenging, including low bioavailability, and rapid elimination. In this study, inspired by the self-assembly of phenylalanine-based peptides in nature, it is showed that NG a small phenylalanine derivative, assembles into left-handed helical nanofibers in the presence of Ca2+ . These helical NG nanofibers functioned as a coating layer on the surface of Ca2+ -linked alginate (Alg) microgels for the effective encapsulation of Ins. As expected, the sustained release and prolonged circulation of Ins and NG from the Ins-loading Alg/NG microgels (Ins@Alg/NG) in the intestinal tract synergistically maintain a relatively normal blood glucose level in streptozotocin-induced diabetic mice after oral administration of Ins@Alg/NG. This further confirms that Ins@Alg/NG ameliorated Ins resistance mainly through activating Insreceptor substrate 1 (IRS1), protein kinase B (AKT), and AMP-activated protein kinase (AMPK), as well as by repressing glycogen synthase kinase-3β (GSK-3β). The strategy of using the assembly of NG as a coating achieves the oral delivery of insulin and showcases a potential for the treatment of diabetes.

Efficient prediction of peptide self-assembly through sequential and graphical encoding

In recent years, there has been an explosion of research on the application of deep learning to the prediction of various peptide properties, due to the significant development and market potential of peptides. Molecular dynamics has enabled the efficient collection of large peptide datasets, providing reliable training data for deep learning. However, the lack of systematic analysis of the peptide encoding, which is essential for artificial intelligence-assisted peptide-related tasks, makes it an urgent problem to be solved for the improvement of prediction accuracy. To address this issue, we first collect a high-quality, colossal simulation dataset of peptide self-assembly containing over 62 000 samples generated by coarse-grained molecular dynamics. Then, we systematically investigate the effect of peptide encoding of amino acids into sequences and molecular graphs using state-of-the-art sequential (i.e. recurrent neural network, long short-term memory and Transformer) and structural deep learning models (i.e. graph convolutional network, graph attention network and GraphSAGE), on the accuracy of peptide self-assembly prediction, an essential physiochemical process prior to any peptide-related applications. Extensive benchmarking studies have proven Transformer to be the most powerful sequence-encoding-based deep learning model, pushing the limit of peptide self-assembly prediction to decapeptides. In summary, this work provides a comprehensive benchmark analysis of peptide encoding with advanced deep learning models, serving as a guide for a wide range of peptide-related predictions such as isoelectric points, hydration free energy, etc.

Engineering nanoparticle toolkits for mRNA delivery

The concept of using mRNA to produce its own medicine in situ in the body makes it an ideal drug candidate, holding great potential to revolutionize the way we approach medicine. The unique characteristics of mRNA, as well as its customizable biomedical functions, call for the rational design of delivery systems to protect and transport mRNA molecules. In this review, a nanoparticle toolkit is presented for the development of mRNA-based therapeutics from a drug delivery perspective. Nano-delivery systems derived from either natural systems or chemical synthesis, in the nature of organic or inorganic materials, are summarised. Delivery strategies in controlling the tissue targeting and mRNA release, as well as the role of nanoparticles in building and boosting the activity of mRNA drugs, have also been introduced. In the end, our insights into the clinical and translational development of mRNA nano-drugs are presented.

Chiral Supramolecular Assemblies: Controllable Construction and Biological Activity

Chiral supramolecular assemblies with helical structures (e. g., proteins with α-helix, DNA with double helix, collagen with triple-helix) as the central structure motifs in biological systems play a crucial role in various physiological activities of living organisms. Variations in chiral structure can cause many abnormal physiological activities. To gain insight into the construction, structural transition, and related physiological functions of these complex helix in natural systems, it is necessary to fabricate artificial supramolecular assemblies with controllable helix orientation as research platform. This review discusses recent advances in chiral supramolecular assembly, including the precise construction and regulation of assembled chiral nanostructures with tunable chirality. Chiral structure-dependent biological activities, including cell proliferation, cell differentiation, antibacterial activity and tissue regeneration, are also discussed. This review not only contributes to further understanding of the importance of chirality in the physiological environment, but also plays an important role in the development of chiral biomedical materials for the treatment of diseases (e. g., tissue engineering regeneration, stem cell transplantation therapy).

Molecular Dynamics Simulation of Self-Assembly Processes of Diphenylalanine Peptide Nanotubes and Determination of Their Chirality

In this work, we further developed a new approach for modeling the processes of the self-assembly of complex molecular nanostructures using molecular dynamics methods; in particular, using a molecular dynamics manipulator. Previously, this approach was considered using the example of the self-assembly of a phenylalanine helical nanotube. Now, a new application of the algorithm has been developed for implementing a similar molecular dynamic self-assembly into helical structures of peptide nanotubes (PNTs) based on other peptide molecules-namely diphenylalanine (FF) molecules of different chirality L-FF and D-FF. In this work, helical nanotubes were assembled from linear sequences of FF molecules with these initially different chiralities. The chirality of the obtained nanotubes was calculated by various methods, including calculation by dipole moments. In addition, a statistical analysis of the results obtained was performed. A comparative analysis of the structures of nanotubes was also performed using the method of visual differential analysis. It was found that FF PNTs obtained by the MD self-assembly method form helical nanotubes of different chirality. The regimes that form nanotubes of right chirality D from initial L-FF dipeptides and nanotubes of left chirality L from D-FF dipeptides are revealed. This corresponds to the law of changing the sign of the chirality of molecular helical structures as the level of their hierarchical organization becomes more complicated.

Pyrene-Based Self-Assembling Peptide for Ratiometric Detection of Heparin

Heparin is a commonly used anticoagulant in clinical practice; however, excessive heparin can cause serious adverse reactions. Convenient and accurate detection of heparin levels is thus very important. In this research, a pyrene-based self-assembling fluorescent peptide PyFFRRR was designed for simple, selective, and efficient heparin detection. The guanidine groups in the arginine residues of PyFFRRR bind tightly with heparin, which is highly sulfated, through electrostatic interactions. Charge neutralization facilitated the self-assembly of PyFFRRR, resulting in its spectral response changing from deep blue monomer fluorescence to green excimer fluorescence. PyFFRRR exhibited excellent sensitivity and selectivity for ratiometric detection of heparin. The binding mechanism was investigated by using spectral and simulation tools, and structural observation. Finally, PyFFRRR was employed in human serum samples for ratiometric detection of heparin.

Nanotubes and water-channels from self-assembling dipeptides

Dipeptides are attractive building blocks for biomaterials in light of their inherent biocompatibility, biodegradability, and simplicity of preparation. Since the discovery of diphenylalanine (Phe-Phe) self-assembling ability into nanotubes, research efforts have been devoted towards the identification of other dipeptide sequences capable of forming these interesting nanomorphologies, although design rules towards nanotube formation are still elusive. In this review, we analyze the dipeptide sequences reported thus far for their ability to form nanotubes, which often feature water-filled supramolecular channels as revealed by single-crystal X-ray diffraction, as well as their properties, and their potential biological applications, which span from drug delivery and regenerative medicine, to bioelectronics and bioimaging.

Recent advances in self-assembling peptide matrices as functional coatings for implantable devices

Nature has evolved numerous supramolecular machineries for modulating various cellular functions. Inspired by the assembly of these sophisticated structures in nature, the controlled assembly of synthetic peptides emerges as a promising approach to therapeutically relevant applications. The self-assembling biomimetic peptides could form well-ordered architectures through non-covalent interactions such as π-π stacking, van der Waals, electrostatic, and hydrogen bonding. In addition, the peptidic building blocks are highly biocompatible and allow facile chemical manipulation with diverse functionalities. For decades, a serious of engineered self-assembling peptides have been extensively studied as functional hydrogels for various applications. Meanwhile, the surface modification strategies based on self-assembling peptide matrices have also raised the attention of biomaterials researchers due to their programmability and 3D porous morphologies. This concise review will cover recent advances in self-assembling peptide matrices as functional coatings for implantable devices. The opportunities and challenges in this field will also be discussed.

Controlled-Alignment Patterns of Dipeptide Micro- and Nanofibers

Ordered assemblies of the peptide diphenylalanine (FF) are produced and deposited on planar substrates. The FF aggregate growth is achieved through precipitation from aqueous ammonia solutions induced by solvent evaporation. The applied dip-coating technique confines the FF assembly growth to a narrow zone near the three-phase contact. The growth was observed online by optical microscopy and was investigated systematically as a function of the process parameters. Depending on the external gas flow (to influence solvent evaporation), the withdrawal speed, the initial FF, and the initial ammonia concentrations, FF forms long, straight, and rigid microfibers and/or shorter, curved nanofibers. Under certain process conditions, the FF fibers can also aggregate into stripes. These can be deposited as large arrays of uniform stripes with regular widths and spacings. Scenarios leading to the various types of fibers and the stripe formation are presented and discussed in view of the experimental findings.

Multiscale Exploration of Concentration-Dependent Amyloid-β(16-21) Amyloid Nucleation

Atomic descriptions of peptide aggregation nucleation remain lacking due to the difficulty of exploring complex configurational spaces on long time scales. To elucidate this process, we develop a multiscale approach combining a metadynamics-based method with cluster statistical mechanics to derive concentration-dependent free energy surfaces of nucleation at near-atomic resolution. A kinetic transition network of nucleation is then constructed and employed to systematically explore nucleation pathways and kinetics through stochastic simulations. This approach is applied to describe Aβ_16-21 amyloid nucleation, revealing a two-step mechanism involving disordered aggregates at millimolar concentration, and an unexpected mechanism at submillimolar concentrations that exhibits kinetics reminiscent of classical nucleation but atypical pathways involving growing clusters with structured cores wrapped by disordered surface. When this atypical mechanism is operative, critical nucleus size can be reflected by the nucleation reaction order. Collectively, our approach paves the way for a more quantitative and detailed understanding of peptide aggregation nucleation.

Development of a Hybrid-Resolution Force Field for Peptide Self-Assembly Simulations: Optimizing Peptide-Peptide and Peptide-Solvent Interactions

Atomic descriptions of peptide self-assembly are crucial to an understanding of disease-related peptide aggregation and the design of peptide-assembled materials. Obtaining these descriptions through computer simulation is challenging because current force fields, which were not designed for this process and are often unable to describe correctly peptide self-assembly behavior and the sequence dependence. Here, we developed a framework using dipeptide aggregation as a model system to improve force fields for simulations of self-assembly. Aggregation-related structural properties were designed and used to guide the optimization of peptide-peptide and peptide-solvent interactions. With this framework, we developed a self-assembly force field, termed PACE-ASM, by reoptimizing a hybrid-resolution force field that was originally developed for folding simulation. With its applicability in folding simulations, the new PACE was used to simulate the self-assembly of two disease-related short peptides, Aβ_16-21 and PHF6, into β-sheet-rich cross-β amyloids. These simulations reproduced the crystal structures of Aβ_16-21 and PHF6 amyloids at near-atomic resolution and captured the difference in packing orientations between the two sequences, a task which is challenging even with all-atom force fields. Apart from cross-β amyloids, the self-assembly of emerging helix-rich cross-α amyloids by another peptide PSMα3 can also be correctly described with the new PACE, manifesting the versatility of the force field. We demonstrated that the ability of the PACE-ASM to model peptide self-assembly is based largely on its improved description of peptide-peptide and peptide-solvent interactions. This was achieved with our optimization framework that can readily identify and address the deficiency in describing these interactions.

Structural Properties of Phenylalanine-Based Dimers Revealed Using IR Action Spectroscopy

Peptide segments with phenylalanine residues are commonly found in proteins that are related to neurodegenerative diseases. However, the self-assembly of phenylalanine-based peptides can be also functional. Peptides containing phenylalanine residues with different side caps, composition, and chemical alteration can form different types of nanostructures that find many applications in technology and medicine. Various studies have been performed in order to explain the remarkable stability of the resulting nanostructures. Here, we study the early stages of self-assembly of two phenylalanine derived peptides in the gas phase using IR action spectroscopy. Our focus lies on the identification of the key intra- and intermolecular interactions that govern the formation of the dimers. The far-IR region allowed us to distinguish between structural families and to assign the 2-(2-amino-2-phenylacetamido)-2-phenylacetic acid (PhgPhg) dimer to a very symmetric structure with two intermolecular hydrogen bonds and its aromatic rings folded away from the backbone. By comparison with the phenylalanine-based peptide cyclic L-phenylalanyl-L-phenylalanine (cyclo-FF), we found that the linear FF dimer likely adopts a less ordered structure. However, when one more phenylalanine residue is added (FFF), a more structurally organized dimer is formed with several intermolecular hydrogen bonds.

Stereostructure Dependence Phenomenon on the Self-Assembly of Ala-Ala-Ala Lipotripeptides

A series of lipotripeptide stereoisomers based on alanine were synthesized, and their self-assembling behaviors were studied by means of circular dichroism spectra, ATR-IR, temperature-dependent ¹H NMR, and X-ray diffraction patterns. In the mixed solvent of hexafluoroisopropanol/H₂O (1/9, v/v), eight lipotripeptides were able to self-assembled into nanoflakes or nanoribbons driven by the hydrophobic association of alkyl chains, intermolecular hydrogen bonding among carboxyl groups at C-terminal and amide groups of alanine moieties in the peptide segment. It was found that the stacking chirality of carbonyl groups was determined by the chirality of alanine residue at C-terminal (i.e., "C-terminal determination" rule). Moreover, our research also highlighted the intermolecular hydrogen bonding on amide groups of each alanine residue, terminal carboxyl as well as the molecular packing structures can be subtly manipulated by changing the stereochemical sequence of peptide segment.

Self-assembly of an in silico designed dipeptide derivative to obtain photo-responsive vesicles

Photo-responsive vesicles self-assembled from in silico designed peptide derivatives were investigated using coarse-grained molecular dynamics simulations.

Dipeptide Nanostructure Assembly and Dynamics via in Situ Liquid-Phase Electron Microscopy

In this paper, we report the in situ growth of FF nanotubes examined via liquid-cell transmission electron microscopy (LCTEM). This direct, high spatial, and temporal resolution imaging approach allowed us to observe the growth of peptide-based nanofibrillar structures through directional elongation. Furthermore, the radial growth profile of FF nanotubes through the addition of monomers perpendicular to the tube axis has been observed in real-time with sufficient resolution to directly observe the increase in diameter. Our study demonstrates that the kinetics, dynamics, structure formation, and assembly mechanism of these supramolecular assemblies can be directly monitored using LCTEM. The performance of the peptides and the assemblies they form can be verified and evaluated using post-mortem techniques including time-of-flight secondary ion mass spectrometry (ToF-SIMS).

Computational Tools to Rationalize and Predict the Self-Assembly Behavior of Supramolecular Gels

Supramolecular gels form a class of soft materials that has been heavily explored by the chemical community in the past 20 years. While a multitude of experimental techniques has demonstrated its usefulness when characterizing these materials, the potential value of computational techniques has received much less attention. This review aims to provide a complete overview of studies that employ computational tools to obtain a better fundamental understanding of the self-assembly behavior of supramolecular gels or to accelerate their development by means of prediction. As such, we hope to stimulate researchers to consider using computational tools when investigating these intriguing materials. In the concluding remarks, we address future challenges faced by the field and formulate our vision on how computational methods could help overcoming them.

Molecular design of stapled pentapeptides as building blocks of self-assembled coiled coil-like fibers

Peptide self-assembly inspired by natural superhelical coiled coils has been actively pursued but remains challenging due to limited helicity of short peptides. Side chain stapling can strengthen short helices but is unexplored in design of self-assembled helical nanofibers as it is unknown how staples could be adapted to coiled coil architecture. Here, we demonstrate the feasibility of this design for pentapeptides using a computational method capable of predicting helicity and fiber-forming tendency of stapled peptides containing noncoded amino acids. Experiments showed that the best candidates, which carried an aromatically substituted staple and phenylalanine analogs, displayed exceptional helicity and assembled into nanofibers via specific head-to-tail hydrogen bonding and packing between staple and noncoded side chains. The fibers exhibited sheet-of-helix structures resembling the recently found collapsed coiled coils whose formation was sensitive to side chain flexibility. This study expands the chemical space of coiled coil assemblies and provides guidance for their design.

Heterochirality and Halogenation Control Phe-Phe Hierarchical Assembly

Diphenylalanine is an amyloidogenic building block that can form a versatile array of supramolecular materials. Its shortcomings, however, include the uncontrolled hierarchical assembly into microtubes of heterogeneous size distribution and well-known cytotoxicity. This study rationalized heterochirality as a successful strategy to address both of these pitfalls and it provided an unprotected heterochiral dipeptide that self-organized into a homogeneous and optically clear hydrogel with excellent ability to sustain fibroblast cell proliferation and viability. Substitution of one l-amino acid with its d-enantiomer preserved the ability of the dipeptide to self-organize into nanotubes, as shown by single-crystal XRD analysis, whereby the pattern of electrostatic and hydrogen bonding interactions of the backbone was unaltered. The effect of heterochirality was manifested in subtle changes in the positioning of the aromatic side chains, which resulted in weaker intermolecular interactions between nanotubes. As a result, d-Phe-l-Phe self-organized into homogeneous nanofibrils with a diameter of 4 nm, corresponding to two layers of peptides around a water channel, and yielded a transparent hydrogel. In contrast with homochiral Phe-Phe stereoisomer, it formed stable hydrogels thermoreversibly. d-Phe-l-Phe displayed no amyloid toxicity in cell cultures with fibroblast cells proliferating in high numbers and viability on this biomaterial, marking it as a preferred substrate over tissue-culture plastic. Halogenation also enabled the tailoring of d-Phe-l-Phe self-organization. Fluorination allowed analogous supramolecular packing as confirmed by XRD, thus nanotube formation, and gave intermediate levels of bundling. In contrast, iodination was the most effective strategy to augment the stability of the resulting hydrogel, although at the expense of optical transparency and biocompatibility. Interestingly, iodine presence hindered the supramolecular packing into nanotubes, resulting instead into amphipathic layers of stacked peptides without the occurrence of halogen bonding. By unravelling fine details to control these materials at the meso- and macro-scale, this study significantly advanced our understanding of these systems.

Low molecular weight self-assembling peptide-based materials for cell culture, antimicrobial, anti-inflammatory, wound healing, anticancer, drug delivery, bioimaging and 3D bioprinting applications

In this review, we have focused on the design and development of low molecular weight self-assembling peptide-based materials for various applications including cell proliferation, tissue engineering, antibacterial, antifungal, anti-inflammatory, anticancer, wound healing, drug delivery, bioimaging and 3D bioprinting. The first part of the review describes about stimuli and various noncovalent interactions, which are the key components of various self-assembly processes for the construction of organized structures. Subsequently, the chemical functionalization of the peptides has been discussed, which is required for the designing of self-assembling peptide-based soft materials. Various low molecular weight self-assembling peptides have been discussed to explain the important structural features for the construction of defined functional nanostructures. Finally, we have discussed various examples of low molecular weight self-assembling peptide-based materials for cell culture, antimicrobial, anti-inflammatory, anticancer, wound healing, drug delivery, bioimaging and 3D bioprinting applications.

Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence–structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended β-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.

Structural conversion of human islet amyloid polypeptide aggregates under an electric field

Electric fields (EFs) in biological systems are well known, and their presence implies the activity of protein ion channels and pumps in various cells. The aggregation of islet amyloid polypeptides (IAPP) was recently found in human brain tissue, and this was related to the electrical activity of neurons and caused neuronal loss. However, the association between amyloid formation and the electric field is still unknown. Herein a direct method to stimulate the formation of the hIAPP peptide under an EF is reported.

Constitutionally Isomeric Aromatic Tripeptides: Self-Assembly and Metal-Ion-Modulated Transformations

Self-assembling peptides based on aromatic amino acids can adopt diverse nanostructures which primarily depend on their molecular structures. Therefore, to understand the nature of self-assembly on the molecular level we rationally designed two constitutional isomers of short aromatic peptides. The first isomer consists of a tyrosine moiety at the N-terminus and the second isomer consists of a tyrosine moiety at the C-terminus of the FF peptide, a core recognition motif of Amyloid β peptides. Therefore, it can be considered that both the designed tripeptides are the analogues of the FFF peptide with only atomic(-H) level replacement by -OH functional group on the first and last phenyl ring, respectively. The first isomer self-assembled into 2D porous nanosheets ("Nanowebs"), however the second isomers produced toroidal shapes with central spheres ("Nano-Saturn" like assemblies). Interestingly, the presence of the transition-metal ions (copper, zinc and iron) triggered the self-assembly of both the peptides into fibrous circular discs, nanomats and nanoplates like assembly.

Root of the Tree: The Significance, Evolution, and Origins of the Ribosome

The ribosome is an ancient molecular fossil that provides a telescope to the origins of life. Made from RNA and protein, the ribosome translates mRNA to coded protein in all living systems. Universality, economy, centrality and antiquity are ingrained in translation. The translation machinery dominates the set of genes that are shared as orthologues across the tree of life. The lineage of the translation system defines the universal tree of life. The function of a ribosome is to build ribosomes; to accomplish this task, ribosomes make ribosomal proteins, polymerases, enzymes, and signaling proteins. Every coded protein ever produced by life on Earth has passed through the exit tunnel, which is the birth canal of biology. During the root phase of the tree of life, before the last common ancestor of life (LUCA), exit tunnel evolution is dominant and unremitting. Protein folding coevolved with evolution of the exit tunnel. The ribosome shows that protein folding initiated with intrinsic disorder, supported through a short, primitive exit tunnel. Folding progressed to thermodynamically stable β-structures and then to kinetically trapped α-structures. The latter were enabled by a long, mature exit tunnel that partially offset the general thermodynamic tendency of all polypeptides to form β-sheets. RNA chaperoned the evolution of protein folding from the very beginning. The universal common core of the ribosome, with a mass of nearly 2 million Daltons, was finalized by LUCA. The ribosome entered stasis after LUCA and remained in that state for billions of years. Bacterial ribosomes never left stasis. Archaeal ribosomes have remained near stasis, except for the superphylum Asgard, which has accreted rRNA post LUCA. Eukaryotic ribosomes in some lineages appear to be logarithmically accreting rRNA over the last billion years. Ribosomal expansion in Asgard and Eukarya has been incremental and iterative, without substantial remodeling of pre-existing basal structures. The ribosome preserves information on its history.

Prebiotic Peptides: Molecular Hubs in the Origin of Life

The fundamental roles that peptides and proteins play in today's biology makes it almost indisputable that peptides were key players in the origin of life. Insofar as it is appropriate to extrapolate back from extant biology to the prebiotic world, one must acknowledge the critical importance that interconnected molecular networks, likely with peptides as key components, would have played in life's origin. In this review, we summarize chemical processes involving peptides that could have contributed to early chemical evolution, with an emphasis on molecular interactions between peptides and other classes of organic molecules. We first summarize mechanisms by which amino acids and similar building blocks could have been produced and elaborated into proto-peptides. Next, non-covalent interactions of peptides with other peptides as well as with nucleic acids, lipids, carbohydrates, metal ions, and aromatic molecules are discussed in relation to the possible roles of such interactions in chemical evolution of structure and function. Finally, we describe research involving structural alternatives to peptides and covalent adducts between amino acids/peptides and other classes of molecules. We propose that ample future breakthroughs in origin-of-life chemistry will stem from investigations of interconnected chemical systems in which synergistic interactions between different classes of molecules emerge.

Expanding the structural diversity of peptide assemblies by coassembling dipeptides with diphenylalanine

Molecular self-assembly is a bottom-up approach to fabricate novel supramolecular structures. While the structural diversity obtained by the use of a single type of building block is limited, coassembly of different peptides has recently evolved as an extended strategy to expand the diversity of peptide nanoarchitectures. Here we systematically investigate the coassembly of diphenylalanine (FF) with each one of the 399 non-FF dipeptides by micro-second molecular dynamics simulations. Our simulations show that dipeptides, by coassembling with FF, display a greatly enhanced aggregation propensity and a significantly expanded structural diversity. Regular-shaped vesicles, single- or multi-cavity assemblies, and planar sheets are formed by coassembly of FF with different types of non-FF dipeptides, which are rarely observed in self-assemblies of non-FF dipeptides. Interaction analyses reveal that the formation of these varied structures is attributed to a delicate balance between aromatic stacking, hydrophobic, and electrostatic repulsion interactions. This study provides structural and mechanistic insights into the coassembly of FF and non-FF dipeptides, thus offering a possible way to achieve a controllable design of bionanomaterials through FF-involved dipeptide coassembly.

Sulfur-Grafted Hollow Carbon Spheres for Potassium-Ion Battery Anodes

Sulfur-rich carbons are minimally explored for potassium-ion batteries (KIBs). Here, a large amount of S (38 wt%) is chemically incorporated into a carbon host, creating sulfur-grafted hollow carbon spheres (SHCS) for KIB anodes. The SHCS architecture provides a combination of nanoscale (≈40 nm) diffusion distances and CS chemical bonding to minimize cycling capacity decay and Coulombic efficiency (CE) loss. The SHCS exhibit a reversible capacity of 581 mAh g^-1 (at 0.025 A g^-1 ), which is the highest reversible capacity reported for any carbon-based KIB anode. Electrochemical analysis of S-free carbon spheres baseline demonstrates that both the carbon matrix and the sulfur species are highly electrochemically active. SHCS also show excellent rate capability, achieving 202, 160, and 110 mAh g^-1 at 1.5, 3, and 5 A g^-1 , respectively. The electrode maintains 93% of the capacity from the 5th to 1000th cycle at 3 A g^-1 , with steady-state CE being near 100%. Raman analysis indicates reversible breakage of CS and SS bonds upon potassiation to 0.01 V versus K/K⁺ . The galvanostatic intermittent titration technique (GITT) analysis provides voltage-dependent K⁺ diffusion coefficients that range from 10^-10 to 10^-12 cm² s^-1 upon potassiation and depotassiation, with approximately five times higher coefficient for the former.

Protein nanotubes as state-of-the-art nanocarriers: Synthesis methods, simulation and applications

Application of food proteins as a tool to form nanostructures (especially nanotubular shapes) has been an interesting topic for both the food and pharmaceutical sectors. Organic and protein nanostructures have better biocompatibility and biodegradability compared to inorganic counterparts like carbon nanotubes; in addition, they can undergo surface modifications. Several organic nanotubes have been developed, meanwhile, the engineered protein nanotubes in the food science have been prepared from α-lactalbumin, ovalbumin, cyclic peptide nanotubes, collagen, bovine serum albumin, lysozyme and hydrophobins which are of great interest to be applied in the food industry considering their outstanding properties. This revision underlines the production of protein nanotubular structures and their applications as well as introducing the in silico studies which is a novel field in predicting the interactions of proteins with different molecules before running experimental tests and finally exploring the safety of protein nanotubes. Protein nanotubes have several advantages over other morphologies, such as the functionalizing ability of both the outer and inner layers, enabling an efficient delivery and controlled release and their ability as gelling agents. Also, regarding their natural source in foods, they are promising alternatives to carbon nanotubes.