Characterizing the shear response of polymer-grafted nanoparticles.

Grafting polymer chains to the surface of nanoparticles overcomes the challenge of nanoparticle dispersion within nanocomposites and establishes high-volume fractions that are found to enable enhanced material mechanical properties. This study utilizes coarse-grained molecular dynamics simulations to quantify how the shear modulus of polymer-grafted nanoparticle (PGN) systems in their glassy state depends on parameters such as strain rate, nanoparticle size, grafting density, and chain length. The results are interpreted through further analysis of the dynamics of chain conformations and volume fraction arguments. The volume fraction of nanoparticles is found to be the most influential variable in deciding the shear modulus of PGN systems. A simple rule of mixture is utilized to express the monotonic dependence of shear modulus on the volume fraction of nanoparticles. Due to the reinforcing effect of nanoparticles, shortening the grafted chains results in a higher shear modulus in PGNs, which is not seen in linear systems. These results offer timely insight into calibrating molecular design parameters for achieving the desired mechanical properties in PGNs.

Bidispersity Improves the Toughness and Impact Resistance of Star-Polymer Thin Films.

Branched polymer architectures are used to tune the mechanical properties of impact-resistant thin films through parameters, such as chain length and grafting density. While chain dispersity affects molecular properties, such as interpenetration and entanglements, structure-property relationships accounting for dispersity are challenging to obtain experimentally and are often neglected in computational models. We employ molecular dynamics simulations to model the high-rate tensile elongation and nanoballistic impact of thin films composed of bidisperse star polymers with varying arm lengths. We find that, at fixed molecular weight, high dispersity can significantly enhance the toughness and impact resistance of the films without decreasing their elastic modulus. Bidisperse stars with fewer longer arms are less entangled, but stretch and interpenetrate for longer times during crazing, leading to increased toughness. These findings highlight controlled dispersity as a design strategy to improve the mechanical properties of polymer composites across Pareto fronts.

B-factor prediction in proteins using a sequence-based deep learning model.

B factors provide critical insight into protein dynamics. Predicting B factors of an atom in new proteins remains challenging as it is impacted by their neighbors in Euclidean space. Previous learning methods developed have resulted in low Pearson correlation coefficients beyond the training set due to their limited ability to capture the effect of neighboring atoms. With the advances in deep learning methods, we develop a sequence-based model that is tested on 2,442 proteins and outperforms the state-of-the-art models by 30%. We find that the model learns that the B factor of a site is prominently affected by atoms within a 12-15 Å radius, which is in excellent agreement with cutoffs from protein network models. The ablation study revealed that the B factor can largely be predicted from the primary sequence alone. Based on the abovementioned points, our model lays a foundation for predicting other properties that are correlated with the B factor.

Increase in Charge and Density Improves the Strength and Toughness of Mussel Foot Protein 5 Inspired Protein Materials.

Mussel foot protein 5 (fp5) found in the adhesive byssal plaque of Mediterranean mussel Mytilus galloprovincialis exhibits exceptional underwater adhesion to diverse surfaces to the extent that adhesion strength typically exceeds the cohesive strength of the plaque. While sequence effects such as presence of charged residues, metal ion coordination, and high catechol content have been identified to govern fp5's interaction with surfaces, molecular contributors to its cohesive strength remain to be fully understood. Addressing this issue is critical for designing mussel-inspired sequences for new adhesives and biomaterials enabled by synthetic biology. Here we carry out all-atom molecular dynamics simulations on hydrated model fp5 biopolymer melts to understand how sequence features such as tyrosine and charge content affect packing density and inter-residue and ionic interaction strengths and consequently influence the cohesive strength and toughness. Systematic serine (S) substitutions for lysine (K), arginine (R) and tyrosine (Y) residues reveal that Y to S substitution surprisingly results in improvement of cohesive strength due to densification of the material by removal of steric hindrances, whereas the removal of charge in K and R to S substitutions has a detrimental impact on strength and toughness as it reduces cohesive interactions facilitated by electrostatic interactions. Additionally, melts formed from split fp5 sequences with only C or N terminal halves show distinct mechanical responses that further illustrate the role of charge. Our findings provide new insights for designing materials that could potentially surpass the performance of existing biomolecular and bioinspired adhesives, specifically by tailoring sequences for balancing charge and excluded volume effects.

Stability of Nanopeptides: Structure and Molecular Exchange of Self-assembled Peptide Fibers.

Often nanostructures formed by self-assembly of small molecules based on hydrophobic interactions are rather unstable, causing morphological changes or even dissolution when exposed to changes in aqueous media. In contrast, peptides offer precise control of the nanostructure through a range of molecular interactions where physical stability can be engineered in and, to a certain extent, decoupled from size via rational design. Here, we investigate a family of peptides that form beta-sheet nanofibers and demonstrate a remarkable physical stability even after attachment of poly(ethylene glycol). We employed small-angle neutron/X-ray scattering, circular dichroism spectroscopy, and molecular dynamics simulation techniques to investigate the detailed nanostructure, stability, and molecular exchange. The results for the most stable sequence did not reveal any structural alterations or unimer exchange for temperatures up to 85 °C in the biologically relevant pH range. Only under severe mechanical perturbation (i.e., tip sonication) would the fibers break up, which is reflected in a very high activation barrier for unimer exchange of ∼320 kJ/mol extracted from simulations. The results give important insight into the relation between molecular structure and stability of peptide nanostructure that is important for, e.g., biomedical applications.

The buckling-condensation mechanism driving gas vesicle collapse.

Gas vesicles (GVs) are proteinaceous cylindrical shells found within bacteria or archea growing in aqueous environments and are composed primarily of two proteins, gas vesicle protein A and C (GvpA and GvpC). GVs exhibit strong performance as next-generation ultrasound contrast agents due to their gas-filled interior, tunable collapse pressure, stability in vivo and functionalizable exterior. However, the exact mechanism leading to GV collapse remains inconclusive, which leads to difficulty in predicting collapse pressures for different species of GVs and in extending favorable nonlinear response regimes. Here, we propose a two stage mechanism leading to GV loss of echogenicity and rupture under hydrostatic pressure: elastic buckling of the cylindrical shell coupled with condensation driven weakening of the GV membrane. Our goal is to therefore test whether the final fracture of the GV membrane occurs by the interplay of both mechanisms or purely through buckling failure as previously believed. To do so, we (1) compare the theoretical condensation and buckling pressures with that for experimental GV collapse and (2) describe how condensation can lead to plastic buckling failure. GV shell properties that are necessary input to this theoretical description, such as the elastic moduli and wettability of GvpA, are determined using molecular dynamics simulations of a novel structural model of GvpA that better represents the hydrophobic core. For GVs that are not reinforced by GvpC, this analytical framework shows that the experimentally observed pressures resulting in loss of echogenicity coincide with both the elastic buckling and condensation pressure regimes. We also found that the stress strain curve for GvpA wetted on both the interior and exterior exhibits a loss of mechanical stability compared to GvpA only wetted on the exterior by the bulk solution. We identify a pressure vs. vesicle size regime where condensation can occur prior to buckling, which may preclude nonlinear shell buckling responses in contrast imaging.

Hierarchically structured bioinspired nanocomposites.

Next-generation structural materials are expected to be lightweight, high-strength and tough composites with embedded functionalities to sense, adapt, self-repair, morph and restore. This Review highlights recent developments and concepts in bioinspired nanocomposites, emphasizing tailoring of the architecture, interphases and confinement to achieve dynamic and synergetic responses. We highlight cornerstone examples from natural materials with unique mechanical property combinations based on relatively simple building blocks produced in aqueous environments under ambient conditions. A particular focus is on structural hierarchies across multiple length scales to achieve multifunctionality and robustness. We further discuss recent advances, trends and emerging opportunities for combining biological and synthetic components, state-of-the-art characterization and modelling approaches to assess the physical principles underlying nature-inspired design and mechanical responses at multiple length scales. These multidisciplinary approaches promote the synergetic enhancement of individual materials properties and an improved predictive and prescriptive design of the next era of structural materials at multilength scales for a wide range of applications.

A new approach for extracting information from protein dynamics.

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.

The effect of nanoparticle softness on the interfacial dynamics of a model polymer nanocomposite.

The introduction of soft organic nanoparticles (NPs) into polymer melts has recently expanded the material design space for polymer nanocomposites, compared to traditional nanocomposites that utilize rigid NPs, such as silica, metallic NPs, and other inorganic NPs. Despite advances in the fabrication and characterization of this new class of materials, the effect of NP stiffness on the polymer structure and dynamics has not been systematically investigated. Here, we use molecular dynamics to investigate the segmental dynamics of the polymer interfacial region of isolated NPs of variable stiffness in a polymer matrix. When the NP-polymer interactions are stronger than the polymer-polymer interactions, we find that the slowing of segmental dynamics in the interfacial region is more pronounced for stiff NPs. In contrast, when the NP-polymer interaction strength is smaller than the matrix interaction, the NP stiffness has relatively little impact on the changes in the polymer interfacial dynamics. We also find that the segmental relaxation time τα of segments in the NP interfacial region changes from values lower than to higher than the bulk material when the NP-polymer interaction strength is increased beyond a "critical" strength, reminiscent of a binding-unbinding transition. Both the NP stiffness and the polymer-surface interaction strength can thus greatly influence the relative segmental relaxation and interfacial mobility in comparison to the bulk material.

A new approach for extracting information from protein dynamics.

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.

Systematic Coarse-graining of Epoxy Resins with Machine Learning-Informed Energy Renormalization.

A persistent challenge in predictive molecular modeling of thermoset polymers is to capture the effects of chemical composition and degree of crosslinking (DC) on dynamical and mechanical properties with high computational efficiency. We established a new coarse-graining (CG) approach that combines the energy renormalization method with Gaussian process surrogate models of the molecular dynamics simulations. This allows a machine-learning informed functional calibration of DC-dependent CG force field parameters. Taking versatile epoxy resins consisting of Bisphenol A diglycidyl ether combined with curing agent of either 4,4-Diaminodicyclohexylmethane or polyoxypropylene diamines, we demonstrated excellent agreement between all-atom and CG predictions for density, Debye-Waller factor, Young's modulus and yield stress at any DC. We further introduce a surrogate model enabled simplification of the functional forms of 14 non-bonded calibration parameters by quantifying the uncertainty of a candidate set of high-dimensional/flexible calibration functions. The framework established provides an efficient methodology for chemistry-specific, large-scale investigations of the dynamics and mechanics of epoxy resins.

Hygromechanical mechanisms of wood cell wall revealed by molecular modeling and mixture rule analysis.

Despite the thousands of years of wood utilization, the mechanisms of wood hygromechanics remain barely elucidated, owing to the nanoscopic system size and highly coupled physics. This study uses molecular dynamics simulations to systematically characterize wood polymers, their mixtures, interface, and composites, yielding an unprecedented micromechanical dataset including swelling, mechanical weakening, and hydrogen bonding, over the full hydration range. The rich data reveal the mechanism of wood cell wall hygromechanics: Cellulose fiber dominates the mechanics of cell wall along the longitudinal direction. Hemicellulose glues lignin and cellulose fiber together defining the cell wall mechanics along the transverse direction, and water severely disturbs the hemicellulose-related hydrogen bonds. In contrast, lignin is rather hydration independent and serves mainly as a space filler. The moisture-induced highly anisotropic swelling and weakening of wood cell wall is governed by the interplay of cellulose reinforcement, mechanical degradation of matrix, and fiber-matrix interface.

Microbial production of megadalton titin yields fibers with advantageous mechanical properties.

Manmade high-performance polymers are typically non-biodegradable and derived from petroleum feedstock through energy intensive processes involving toxic solvents and byproducts. While engineered microbes have been used for renewable production of many small molecules, direct microbial synthesis of high-performance polymeric materials remains a major challenge. Here we engineer microbial production of megadalton muscle titin polymers yielding high-performance fibers that not only recapture highly desirable properties of natural titin (i.e., high damping capacity and mechanical recovery) but also exhibit high strength, toughness, and damping energy - outperforming many synthetic and natural polymers. Structural analyses and molecular modeling suggest these properties derive from unique inter-chain crystallization of folded immunoglobulin-like domains that resists inter-chain slippage while permitting intra-chain unfolding. These fibers have potential applications in areas from biomedicine to textiles, and the developed approach, coupled with the structure-function insights, promises to accelerate further innovation in microbial production of high-performance materials.

Mesoscopic and multiscale modelling in materials.

The concept of multiscale modelling has emerged over the last few decades to describe procedures that seek to simulate continuum-scale behaviour using information gleaned from computational models of finer scales in the system, rather than resorting to empirical constitutive models. A large number of such methods have been developed, taking a range of approaches to bridging across multiple length and time scales. Here we introduce some of the key concepts of multiscale modelling and present a sampling of methods from across several categories of models, including techniques developed in recent years that integrate new fields such as machine learning and material design.

Atomistic Modeling of Peptide Aggregation and ß-Sheet Structuring in Corn Zein for Viscoelasticity.

The structure-function relationships of plant-based proteins that give rise to desirable texture attributes in order to mimic meat products are generally unknown. In particular, it is not clear how to engineer viscoelasticity to impart cohesiveness and proper mouthfeel; however, it is known that intermolecular ß-sheet structures have the potential to enhance the viscoelastic property. Here, we investigated the propensity of selected peptide segments within common corn α-zein variants to maintain stable aggregates and ß-sheet structures. Simulations on dimer systems showed that stability was influenced by the initial orientation and the presence of contiguous small hydrophobic residues. Simulations using eight-peptide ß-sheet oligomers revealed that peptide sequences without proline had higher levels of ß-sheet structuring. Additionally, we identified that sequences with a dimer hydrogen-bonding density of >22% tended to have a larger percent ß-sheet conformation. These results contribute to understanding how the viscoelasticity of zein can be increased for use in plant-based meat analogues.

Hydrogen bonds dominated frictional stick-slip of cellulose nanocrystals.

Crystalline cellulose, the most abundant natural polymer on earth, features exceptional physical and mechanical properties. Using atomistic simulation, this study reports the mechanical behavior of cellulose-cellulose nanocrystal hydrophilic interface and systematically examines the impact of loading direction, interfacial moisture, misalignment and surface types. The density, orientation or distribution of interfacial hydrogen bonds are shown to explain the series of findings presented here, including stick-slip behavior, stiffness recovery after an irreversible slip, direction-dependent behavior and weakening induced by hydration or misalignment. Correlation analysis shows that, regardless of the various loading conditions, the interfacial stress, shear velocity and interaction energy are strongly correlated with the density of interfacial hydrogen bonds, which quantitatively supports the central role of hydrogen bonding. Based on this correlation, the friction force rendered by a single hydrogen bond is inferred to be fHB ∼1.3 E-10 N under a shearing speed of 1 m s-1.

Self-strengthening biphasic nanoparticle assemblies with intrinsic catch bonds.

Protein-ligand complexes with catch bonds exhibit prolonged lifetimes when subject to tensile force, which is a desirable yet elusive attribute for man-made nanoparticle interfaces and assemblies. Most designs proposed so far rely on macromolecular linkers with complicated folds rather than particles exhibiting simple dynamic shapes. Here, we establish a scissor-type X-shaped particle design for achieving intrinsic catch bonding ability with tunable force-enhanced lifetimes under thermal excitations. Molecular dynamics simulations are carried out to illustrate equilibrium self-assembly and force-enhanced bond lifetime of dimers and fibers facilitated by secondary interactions that form under tensile force. The non-monotonic force dependence of the fiber breaking kinetics is well-estimated by an analytical model. Our design concepts for shape-changing particles illuminates a path towards novel nanoparticle or colloidal assemblies that have the passive ability to tune the strength of their interfaces with applied force, setting the stage for self-assembling materials with novel mechanical functions and rheological properties.

Conformational stability of the bacterial adhesin, FimH, with an inactivating mutation.

Allostery governing two conformational states is one of the proposed mechanisms for catch-bond behavior in adhesive proteins. In FimH, a catch-bond protein expressed by pathogenic bacteria, separation of two domains disrupts inhibition by the pilin domain. Thus, tensile force can induce a conformational change in the lectin domain, from an inactive state to an active state with high affinity. To better understand allosteric inhibition in two-domain FimH (H2 inactive), we use molecular dynamics simulations to study the lectin domain alone, which has high affinity (HL active), and also the lectin domain stabilized in the low-affinity conformation by an Arg-60-Pro mutation (HL mutant). Because ligand-binding induces an allostery-like conformational change in HL mutant, this more experimentally tractable version has been proposed as a "minimal model" for FimH. We find that HL mutant has larger backbone fluctuations than both H2 inactive and HL active, at the binding pocket and allosteric interdomain region. We use an internal coordinate system of dihedral angles to identify protein regions with differences in backbone and side chain dynamics beyond the putative allosteric pathway sites. By characterizing HL mutant dynamics for the first time, we provide additional insight into the transmission of allosteric information across the lectin domain and build upon structural and thermodynamic data in the literature to further support the use of HL mutant as a "minimal model." Understanding how to alter protein dynamics to prevent the allosteric conformational change may guide drug development to prevent infection by blocking FimH adhesion.