Deformation and failure of protein materials in physiologically extreme conditions and disease

Compositional, Structural, and Biomechanical Properties of Three Different Soft Tissue-Hard Tissue Insertions: A Comparative Review

Connective tissue attaches to bone across an insertion with spatial gradients in components, microstructure, and biomechanics. Due to regional stress concentrations between two mechanically dissimilar materials, the insertion is vulnerable to mechanical damage during joint movements and difficult to repair completely, which remains a significant clinical challenge. Despite interface stress concentrations, the native insertion physiologically functions as the effective load-transfer device between soft tissue and bone. This review summarizes tendon, ligament, and meniscus insertions cross-sectionally, which is novel in this field. Herein, the similarities and differences between the three kinds of insertions in terms of components, microstructure, and biomechanics are compared in great detail. This review begins with describing the basic components existing in the four zones (original soft tissue, uncalcified fibrocartilage, calcified fibrocartilage, and bone) of each kind of insertion, respectively. It then discusses the microstructure constructed from collagen, glycosaminoglycans (GAGs), minerals and others, which provides key support for the biomechanical properties and affects its physiological functions. Finally, the review continues by describing variations in mechanical properties at the millimeter, micrometer, and nanometer scale, which minimize stress concentrations and control stretch at the insertion. In summary, investigating the contrasts between the three has enlightening significance for future directions of repair strategies of insertion diseases and for bioinspired approaches to effective soft-hard interfaces and other tough and robust materials in medicine and engineering.

Review paper: The importance of consideration of collagen cross-links in computational models of collagen-based tissues

Collagen as the main protein in Extra Cellular Matrix (ECM) is the main load-bearing component of fibrous tissues. Nanostructure and architecture of collagen fibrils play an important role in mechanical behavior of these tissues. Extensive experimental and theoretical studies have so far been performed to capture these properties, but none of the current models realistically represent the complexity of network mechanics because still less is known about the collagen's inner structure and its effect on the mechanical properties of tissues. The goal of this review article is to emphasize the significance of cross-links in computational modeling of different collagen-based tissues, and to reveal the need for continuum models to consider cross-links properties to better reflect the mechanical behavior observed in experiments. In addition, this study outlines the limitations of current investigations and provides potential suggestions for the future work.

A synergistic investigation of azo-thiazole derivatives incorporating thiazole moieties: a comprehensive exploration of their synthesis, characterization, computational insights, solvatochromism, and multimodal biological activity assessment

In the present study, a novel series of azo-thiazole derivatives (3a-c) containing a thiazole moiety was successfully synthesized. The structure of these derivatives was examined by spectroscopic techniques, including 1H NMR, 13C NMR, FT-IR, and HRMS. Further, the novel synthesized compounds were evaluated for their in vitro biological activities, such as antibacterial and anti-inflammatory activities, and an in silico study was performed. The antibacterial results demonstrated that compounds 3a and 3c (MIC = 10 μg mL-1) have a notable potency against Staphylococcus aureus compared to azithromycin (MIC = 40 μg mL-1). Alternatively, compound 3b displayed a four-fold higher potency (24 recovery days, 1.83 mg day-1) than Hamazine (28 recovery days, 4.14 mg day-1) in promoting burn wound healing, and it also exhibited a comparable inhibitory activity against screened bacterial pathogens compared to the reference drug. Docking on 1KZN, considering the excellent impact of compounds on the crystal structure of E. coli1KZN, a 24 kDa domain, in complex with clorobiocin, indicated the close binding of compounds 3a-c with the active site of the 1KZN protein, which is consistent with their observed biological activity. Additionally, we conducted molecular dynamics simulations on the docked complexes of compounds 3a-c with 1KZN retrieved from the PDB to assess their stability and molecular interactions. Furthermore, we assessed their electrochemical characteristics via DFT calculations. Employing PASS and pkCSM platforms, we gained insights into controlling the bioactivity and physicochemical features of these compounds, highlighting their potential as new active agents.

Building block aspect ratio controls assembly, architecture, and mechanics of synthetic and natural protein networks

Fibrous networks constructed from high aspect ratio protein building blocks are ubiquitous in nature. Despite this ubiquity, the functional advantage of such building blocks over globular proteins is not understood. To answer this question, we engineered hydrogel network building blocks with varying numbers of protein L domains to control the aspect ratio. The mechanical and structural properties of photochemically crosslinked protein L networks were then characterised using shear rheology and small angle neutron scattering. We show that aspect ratio is a crucial property that defines network architecture and mechanics, by shifting the formation from translationally diffusion dominated to rotationally diffusion dominated. Additionally, we demonstrate that a similar transition is observed in the model living system: fibrin blood clot networks. The functional advantages of this transition are increased mechanical strength and the rapid assembly of homogenous networks above a critical protein concentration, crucial for in vivo biological processes such as blood clotting. In addition, manipulating aspect ratio also provides a parameter in the design of future bio-mimetic and bio-inspired materials.

Alteration of extracellular matrix proteins in atrophic periodontal ligament of hypofunctional rat molars

OBJECTIVES

The aim of this study was to investigate the effect of mechanical force on possible dynamic changes of the matrix proteins deposition in the PDL upon in vitro mechanical and in vivo occlusal forces in a rat model with hypofunctional conditions.

MATERIALS AND METHODS

Intermittent compressive force (ICF) and shear force (SF) were applied to human periodontal ligament stem cells (PDLSCs). Protein expression of collagen I and POSTN was analyzed by western blot technique. To establish an in vivo model, rat maxillary molars were extracted to facilitate hypofunction of the periodontal ligament (PDL) tissue of the opposing mandibular molar. The mandibles were collected after 4-, 8-, and 12-weeks post-extraction and used for micro-CT and immunohistochemical analysis.

RESULTS

ICF and SF increased the synthesis of POSTN by human PDLSCs. Histological changes in the hypofunctional teeth revealed a narrowing of the PDL space, along with a decreased amount of collagen I, POSTN, and laminin in perivascular structures compared to the functional contralateral molars.

CONCLUSION

Our results revealed that loss of occlusal force disrupts deposition of some major matrix proteins in the PDL, underscoring the relevance of mechanical forces in maintaining periodontal tissue homeostasis by modulating ECM composition.

Generative design of de novo proteins based on secondary structure constraints using an attention-based diffusion model

We report two generative deep learning models that predict amino acid sequences and 3D protein structures based on secondary structure design objectives via either overall content or per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity as they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in conditional generative design of various biological or engineering systems. Future work may include additional conditioning, and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.

Mineralization of Bone Extracellular Matrix-like Scaffolds Fabricated as Silk Sericin-Functionalized Dense Collagen–Fibrin Hybrid Hydrogels

The design of hydrogels that combine both the biochemical cues needed to direct seeded cellular functions and mineralization to provide the structural and mechanical properties approaching those of mineralized native bone extracellular matrix (ECM) represents a significant challenge in bone tissue engineering. While fibrous hydrogels constituting of collagen or fibrin (and their hybrids) can be considered as scaffolds that mimic to some degree native bone ECM, their insufficient mechanical properties limit their application. In the present study, an automated gel aspiration–ejection (automated GAE) method was used to generate collagen–fibrin hybrid gel scaffolds with micro-architectures and mechanical properties approaching those of native bone ECM. Moreover, the functionalization of these hybrid scaffolds with negatively charged silk sericin accelerated their mineralization under acellular conditions in simulated body fluid and modulated the proliferation and osteoblastic differentiation of seeded MC3T3-E1 pre-osteoblastic cells. In the latter case, alkaline phosphatase activity measurements indicated that the hybrid gel scaffolds with seeded cells showed accelerated osteoblastic differentiation, which in turn led to increased matrix mineralization. In summary, the design of dense collagen–fibrin hybrid gels through an automated GAE process can provide a route to tailoring specific biochemical and mechanical properties to different types of bone ECM-like scaffolds, and can provide a model to better understand cell–matrix interactions in vitro for bioengineering purposes.

Nano-biofertilizers as bio-emerging strategies for sustainable agriculture development: Potentiality and their limitations

Nanotechnology is a burgeoning revolutionary technology in the 21st century. Climate emergencies caused by natural or anthropogenic activities have tragically consequential repercussions on agricultural output worldwide. Modern cropping systems profoundly rely on synthetic fertilizers to deliver necessary nutrients, yet their prolonged and persistent administration is hazardous to the environment, soil fertility, and nutritional dynamics of the rhizospheric microbiome. By addressing the drawback of physico-chemically synthesized nano-dimensioned fertilizer, this review emphasizes on integrating nanoparticles and biofertilizers conjointly as nano-biofertilizers (NBF) which can safeguard global food security, in light of the population surge. Inoculation with nanoparticles and biofertilizers strengthens plant growth and stress tolerance. However, combined together (NBF), they have emerged as a more economically and environmentally sustainable, highly versatile, and long-lasting agriculture tool. Microbe-based green synthesis using the encapsulation of inorganic nanoparticles of Si, Zn, Cu, Fe, Ni, Ti, and Ag as well as organic materials, including chitosan, cellulose, and starch, to formulate NBFs can eliminate the constraints of conventional fertilizer contamination. The application of NBFs is in its infancy in agriculture, yet it has promising potential for transforming traditional farming techniques into smart agriculture, compared to any of the existing strategies. From this perspective, this review is an attempt to provide a comprehensive understanding of the formulations, fabrication, and characterization of NBFs while unraveling the underlying mechanisms of plant-NBF interactions along with their contribution to climate change-induced biotic and abiotic stress tolerance. We substantially summarize the latest advancements of field applications of NBFs for precision farming. Moreover, we critically revised their applications in agro-ecosystems according to the current literature, while also discussing the bottlenecks and future trends for developing potent NBFs.

Poroviscoelasto-plasticity of agarose-based hydrogels

Agarose gels are excellent candidates for tissue engineering as they are tunable, viscoelastic, and show a pronounced strain-stiffening response. These characteristics make them ideal to create in vitro environments to grow cells and develop tissues. As in many other biopolymers, viscoelasticity and poroelasticity coexist as time-dependent behaviors in agarose gels. While the viscoelastic behavior of these hydrogels has been considered using both phenomenological and continuum models, there remains a lack of connection between the underlying physics and the macroscopic material response. Through a finite element analysis and complimentary experiments, we evaluated the complex time-dependent mechanical response of agarose gels in various conditions. We then conceptualized these gels as a dynamic network where the global dissociation/association rate of intermolecular bonds is described as a combination of a fast rate native to double helices forming between aligned agarose molecules and a slow rate of the agarose molecules present in the clusters. Using the foundation of the transient network theory, we developed a physics-based constitutive model that accurately describes agarose behavior. Integrating experimental results and model prediction, we demonstrated that the fast dissociation/association rate follows a nonlinear force-dependent response, whose exponential evolution agrees with Eyring's model based on the transition state theory. Overall, our results establish a more accurate understanding of the time-dependent mechanics of agarose gels and provide a model that can inform design of a variety of biopolymers with a similar network topology.

Multiscale mechanical design of the lightweight, stiff, and damage-tolerant cuttlebone: A computational study

Cuttlebone, the endoskeleton of cuttlefish, offers an intriguing biological structural model for designing low-density cellular ceramics with high stiffness and damage tolerance. Cuttlebone is highly porous (porosity ∼93%) and lightweight (density less than 20% of seawater), constructed mainly by brittle aragonite (95 wt%), but capable of sustaining hydrostatic water pressures over 20 atmospheres and exhibits energy absorption capability under compression comparable to many metallic foams (∼4.4 kJ/kg). In this work, we computationally investigate how such remarkable mechanical efficiency is enabled by the multiscale structure of cuttlebone. Using the common cuttlefish, Sepia Officinalis, as a model system, we first conducted high-resolution synchrotron micro-computed tomography (µ-CT) and quantified the cuttlebone's multiscale geometry, including the 3D asymmetric shape of individual walls, the wall assembly patterns, and the long-range structural gradient of walls across the entire cuttlebone (ca. 38 chambers). The acquired 3D structural information enables systematic finite-element simulations, which further reveal the multiscale mechanical design of cuttlebone: at the wall level, wall asymmetry provides optimized energy absorption while maintaining high structural stiffness; at the chamber level, variation of walls (number, pattern, and waviness amplitude) contributes to progressive damage; at the entire skeletal level, the gradient of chamber heights tailors the local mechanical anisotropy of the cuttlebone for reduced stress concentration. Our results provide integrated insights into understanding the cuttlebone's multiscale mechanical design and provide useful knowledge for the designs of lightweight cellular ceramics. STATEMENT OF SIGNIFICANCE: Cuttlebone has been demonstrated to be a biological ceramic cellular material with remarkable lightweight, high stiffness and energy absorption. However, our knowledge on how such mechanical properties are enabled by cuttlebone's multiscale structure is not complete. Here, we combine systematic tomography-based 3D structural analysis and finite-element simulations to reveal how the hierarchical structure of cuttlebone at multiple length scales synergistically contribute to cuttlebone's impressive mechanical efficiency. These findings have important implications for designing biomimetic low-density cellular ceramic materials.

CollagenTransformer: End-to-End Transformer Model to Predict Thermal Stability of Collagen Triple Helices Using an NLP Approach

Collagen is one of the most important structural proteins in biology, and its structural hierarchy plays a crucial role in many mechanically important biomaterials. Here, we demonstrate how transformer models can be used to predict, directly from the primary amino acid sequence, the thermal stability of collagen triple helices, measured via the melting temperature T_m. We report two distinct transformer architectures to compare performance. First, we train a small transformer model from scratch, using our collagen data set featuring only 633 sequence-to-T_m pairings. Second, we use a large pretrained transformer model, ProtBERT, and fine-tune it for a particular downstream task by utilizing sequence-to-T_m pairings, using a deep convolutional network to translate natural language processing BERT embeddings into required features. Both the small transformer model and the fine-tuned ProtBERT model have similar R² values of test data (R² = 0.84 vs 0.79, respectively), but the ProtBERT is a much larger pretrained model that may not always be applicable for other biological or biomaterials questions. Specifically, we show that the small transformer model requires only 0.026% of the number of parameters compared to the much larger model but reaches almost the same accuracy for the test set. We compare the performance of both models against 71 newly published sequences for which T_m has been obtained as a validation set and find reasonable agreement, with ProtBERT outperforming the small transformer model. The results presented here are, to our best knowledge, the first demonstration of the use of transformer models for relatively small data sets and for the prediction of specific biophysical properties of interest. We anticipate that the work presented here serves as a starting point for transformer models to be applied to other biophysical problems.

Molecular investigations of the prenucleation mechanism of bone-like apatite assisted by type I collagen nanofibrils: insights into intrafibrillar mineralization

Bone is a typical inorganic-organic composite material with a multilevel hierarchical organization. In the lowest level of bone tissue, inorganic minerals, which are mainly composed of hydroxyapatite, are mineralized within the type I collagen fibril scaffold. Understanding the crystal prenucleation mechanism and growth of the inorganic phase is particularly important in the design and development of materials with biomimetic nanostructures. In this study, we built an all-atom human type I collagen fibrillar model with a 67 nm overlap/gap D-periodicity. Arginine residues were shown to serve as the dominant cross-linker to stabilize the fibril scaffold. Subsequently, the prenucleation mechanism of collagen intrafibrillar mineralization was investigated using a molecular dynamics approach. Considering the physiological pH of the human body (i.e., ∼7.4), HPO₄^2- was initially used to simulate the protonation state of the phosphate ions. Due to the spatially constrained effects resulting from the overlap/gap structure of the collagen fibrils, calcium phosphate clusters formed mainly inside the hole zone but with different spatial distributions along the long axis direction; this indicated that the nucleation of calcium phosphate may be highly site-selective. Furthermore, the model containing both HPO₄^2- and PO₄^3- in the solution phase formed significantly larger clusters without any change in the nucleation sites. This phenomenon suggests that the existence of PO₄^3- is beneficial for the mineralization process, and so the conversion of HPO₄^2- to PO₄^3- was considered a critical step during mineralization. Finally, we summarize the nucleation mechanism for collagen intrafibrillar mineralization, which could contribute to the fabrication of mineralized collagen biomimetic materials.

Design, manufacture, and testing of customized sterilizable respirator

The respirator as one of the personal protective equipment is essential for industrial activities (e.g., mining, painting, woodcutting, manufacturing) for protection from contaminants in the air and during the Covid-19 pandemic to protect the wearer from infection. The respirators nowadays are commonly made of rigid plastic. They are expensive, cumbersome, and not comfortable to wear. The many components with complex structures prevent it from cleaning and reusing. We develop a practical and scalable strategy to create customized respirators with durability using computational modeling and 3D printing. It is shown that by morphing the shape according to the user's photo, the respirator is designed to fit a user's face without air leaks. Using a printing-mold-casting method, this respirator can be manufactured by silicone rubber with accuracy, which is highly durable, with its mechanics primarily not affected by sterilization. These features provide the current respirator adaptivity and convenience in carrying and storing, as well as more comfort for long-time wearing.

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

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

End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins

Structural proteins are the basis of many biomaterials and key construction and functional components of all life. Further, it is well-known that the diversity of proteins' function relies on their local structures derived from their primary amino acid sequences. Here, we report a deep learning model to predict the secondary structure content of proteins directly from primary sequences, with high computational efficiency. Understanding the secondary structure content of proteins is crucial to designing proteins with targeted material functions, especially mechanical properties. Using convolutional and recurrent architectures and natural language models, our deep learning model predicts the content of two essential types of secondary structures, the α-helix and the β-sheet. The training data are collected from the Protein Data Bank and contain many existing protein geometries. We find that our model can learn the hidden features as patterns of input sequences that can then be directly related to secondary structure content. The α-helix and β-sheet content predictions show excellent agreement with training data and newly deposited protein structures that were recently identified and that were not included in the original training set. We further demonstrate the features of the model by a search for de novo protein sequences that optimize max/min α-helix/β-sheet content and compare the predictions with folded models of these sequences based on AlphaFold2. Excellent agreement is found, underscoring that our model has predictive potential for rapidly designing proteins with specific secondary structures and could be widely applied to biomedical industries, including protein biomaterial designs and regenerative medicine applications.

A Genetically Engineered, Chain Mail-Like Nanostructured Protein Material with Increased Fatigue Resistance and Enhanced Self-Healing

Protein-based nanostructured materials are being developed for many biomedical and nanotechnological applications. Despite their many desirable features, protein materials are highly susceptible to disruption by mechanical stress and fatigue. This study is aimed to increase fatigue resistance and enhance self-healing of a natural protein-based supramolecular nanomaterial through permanent genetic modification. The authors envisage the conversion of a model nanosheet, formed by a regular array of noncovalently bound human immunodeficiency virus capsid protein molecules, into a supramolecular "chain mail." Rationally engineered mutations allow the formation of a regular network of disulfide bridges in the protein lattice. This network links each molecule in the lattice to each adjacent molecule through one covalent bond, analogous to the rivetting of interlinked iron rings in the chain mail of a medieval knight. The engineered protein nanosheet shows greatly increased thermostability and resistance to mechanical stress and fatigue in particular, as well as enhanced self-healing, without undesirable stiffening compared to the original material. The results provide proof of concept for a genetic design to permanently increase fatigue resistance and enhance self-healing of protein-based nanostructured materials. They also provide insights into the molecular basis for fatigue of protein materials.

Protein Assembly by Design

Proteins are nature's primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

A coarse-grained mechanical model for folding and unfolding of tropoelastin with possible mutations

We propose a simple general framework to predict folding, native states, energy barriers, protein unfolding, as well as mutation induced diseases and other protein structural analyses. The model should not be considered as an alternative to classical approaches (Molecular Dynamics or Monte Carlo) because it neglects low scale details and rather focuses on global features of proteins and structural information. We aim at the description of phenomena that are out of the range of classical molecular modeling approaches due to the large computational cost: multimolecular interactions, cyclic behavior under variable external interactions, and similar. To demonstrate the effectiveness of the approach in a real case, we focus on the folding and unfolding behavior of tropoelastin and its mutations. Specifically, we derive a discrete mechanical model whose structure is deduced based on a coarse graining approach that allows us to group the amino acids sequence in a smaller number of `equivalent' masses. Nearest neighbor energy terms are then introduced to reproduce the interaction of such amino acid groups. Nearest and non-nearest neighbor energy terms, inter and intra functional blocks are phenomenologically added in the form of Morse potentials. As we show, the resulting system reproduces important properties of the folding-unfolding mechanical response, including the monotonic and cyclic force-elongation behavior, representing a physiologically important information for elastin. The comparison with the experimental behavior of mutated tropoelastin confirms the predictivity of the model. STATEMENT OF SIGNIFICANCE: Classical approaches to the study of phenomena at the molecular scale such as Molecular Dynamics (MD) represent an incredible tool to unveil mechanical and conformational properties of macromolecules, in particular for biological and medical applications. On the other hand, due to the computational cost, the time and spatial scales are limited. Focusing of the real case of tropoelastin, we propose a new approach based on a careful coarse graining of the system, able to describe the overall properties of the macromolecule and amenable of extension to larger scale effects (protein bundles, protein-protein interactions, cyclic loading). The comparison with tropoelastin behavior, also for mutations, is very promising.

Stem cell therapies in tendon-bone healing

Tendon-bone insertion injuries such as rotator cuff and anterior cruciate ligament injuries are currently highly common and severe. The key method of treating this kind of injury is the reconstruction operation. The success of this reconstructive process depends on the ability of the graft to incorporate into the bone. Recently, there has been substantial discussion about how to enhance the integration of tendon and bone through biological methods. Stem cells like bone marrow mesenchymal stem cells (MSCs), tendon stem/progenitor cells, synovium-derived MSCs, adipose-derived stem cells, or periosteum-derived periosteal stem cells can self-regenerate and potentially differentiate into different cell types, which have been widely used in tissue repair and regeneration. Thus, we concentrate in this review on the current circumstances of tendon-bone healing using stem cell therapy.

Selective Adsorption and Separation of Proteins by Ligand-Modified Nanofiber Fabric

Electrospun polyvinyl alcohol (PVA) nanofiber fabric was modified by Cibacron Blue F3GA (CB) to enhance the affinity of the fabric. Batch experiments were performed to study the nanofiber fabric's bovine hemoglobin (BHb) adsorption capacity at different protein concentrations before and after modification. The maximum BHb adsorption capacity of the modified nanofiber fabric was 686 mg/g, which was much larger than the 58 mg/g of the original fabric. After that, the effect of feed concentration and permeation rate on the dynamic adsorption behaviors for BHb of the nanofiber fabric was investigated. The pH impact on BHb and bovine serum albumin (BSA) adsorption was examined by static adsorption experiments of single protein solutions. The selective separation experiments of the BHb-BSA binary solution were carried out at the optimal pH value, and a high selectivity factor of 5.45 for BHb was achieved. Finally, the reusability of the nanofiber fabric was examined using three adsorption-elution cycle tests. This research demonstrated the potential of the CB-modified PVA nanofiber fabric in protein adsorption and selective separation.

Synthesis, Characterization, and Simulation of Four-Armed Megamolecules

This paper describes the synthesis, characterization, and modeling of a series of molecules having four protein domains attached to a central core. The molecules were assembled with the "megamolecule" strategy, wherein enzymes react with their covalent inhibitors that are substituted on a linker. Three linkers were synthesized, where each had four oligo(ethylene glycol)-based arms terminated in a para-nitrophenyl phosphonate group that is a covalent inhibitor for cutinase. This enzyme is a serine hydrolase and reacts efficiently with the phosphonate to give a new ester linkage at the Ser-120 residue in the active site of the enzyme. Negative-stain transmission electron microscopy (TEM) images confirmed the architecture of the four-armed megamolecules. These cutinase tetramers were also characterized by X-ray crystallography, which confirmed the active-site serine-phosphonate linkage by electron-density maps. Molecular dynamics simulations of the tetracutinase megamolecules using three different force field setups were performed and compared with the TEM observations. Using the Amberff99SB-disp + pH7 force field, the two-dimensional projection distances of the megamolecules were found to agree with the measured dimensions from TEM. The study described here, which combines high-resolution characterization with molecular dynamics simulations, will lead to a comprehensive understanding of the molecular structures and dynamics for this new class of molecules.

Effect of receptors on the resonant and transient harmonic vibrations of Coronavirus

The paper is concerned with the vibration characteristics of the Coronavirus family. There are some 25-100 receptors, commonly called spikes protruding from the envelope shell of the virus. Spikes, resembling the shape of a hot air balloon, may have a total mass similar to the mass of the lipid bi-layer shell. The lipid proteins of the virus are treated as homogeneous elastic material and the problem is formulated as the interaction of thin elastic shell with discrete masses, modeled as short conical cross-sectional beams. The system is subjected to ultrasonic excitation. Using the methods of structural acoustics, it is shown that the scattered pressure is very small and the pressure on the viral shell is simply the incident pressure. The modal analysis is performed for a bare shell, a single spike, and the spike-decorated shell. The predicted vibration frequencies and modes are shown to compare well with the newly derived closed-form solutions for a single spike and existing analytical solutions for thin shells. The fully nonlinear dynamic simulation of the transient response revealed the true character of the complex interaction between local vibration of spikes and global vibration of the multi-degree-of-freedom system. It was shown that harmonic vibration at or below the lowest resonant modes can excite large amplitude vibration of spikes. The associated maximum principal strain in a spike can reach large values in a fraction of a millisecond. Implications for possible tearing off spikes from the shell are discussed. Another important result is that after a finite number of cycles, the shell buckles and collapses, developing internal contacts and folds with large curvatures and strains exceeding 10%. For the geometry and elastic properties of the SARS-CoV-2 virus, these effects are present in the range of frequencies close to the ones used for medical ultrasound diagnostics.

Porous Biphasic Calcium Phosphate for Biomedical Application

Excellent osteoconductivity and resorbability achieved when porous bioceramics have highsurface area that providing fast bone ingrowth. Porous samples were fabricated by using biphasic calcium phosphate BCP (achieved from HA heat treated at 850 oC) with 10 and 20 wt% of ovalbumin binder powder and mixture of carrot fibers and ovalbumin powders (1:1) then dried at 60oC and fired at 1300 oC. Structural, physical and mechanical properties of the prepared porous bioceramic were determined involved X-ray diffraction, Fourier transform infrared spectroscopy FTIR, apparent porosity, water absorption, apparent solid density and compressive strength. The results of X-ray and FTIR showed that the heat treatment of HA was succeeded in forming biphasic calcium phosphate. The apparent porosity values increased with increasing of the binder and carrot fibers content and the growths density of bacteria on bioceramics are less than natural bone. The effect of pathogenic bacteria (Pseudomonas & Staphylococcus) that cause pollution on porous calcium phosphate and natural bone (Albino mice) has been studied.

Comparative Analysis of Nanomechanical Features of Coronavirus Spike Proteins and Correlation with Lethality and Infection Rate

The novel coronavirus disease 2019 (COVID-19) has spread rapidly around the world. Its causative virus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), enters human cells through the physical interaction between the receptor-binding domain (RBD) of its spike protein and the human cell receptor ACE2. Here, we provide a novel way of understanding coronavirus spike proteins, connecting their nanomechanical features, specifically their vibrational spectrum and quantitative measures of mobility, with virus lethality and infection rate. The key result of our work is that both the overall flexibility of upward RBD and the mobility ratio of RBDs in different conformations represent two significant factors that show a positive scaling with virus lethality and an inverse correlation with the infection rate. Our analysis shows that epidemiological virus properties can be linked directly to pure nanomechanical, vibrational aspects, offering an alternative way of screening new viruses and mutations, and potentially exploring novel ways to prevent infections from occurring.

Nonlinear mechanics of lamin filaments and the meshwork topology build an emergent nuclear lamina

The nuclear lamina—a meshwork of intermediate filaments termed lamins—is primarily responsible for the mechanical stability of the nucleus in multicellular organisms. However, structural-mechanical characterization of lamin filaments assembled in situ remains elusive. Here, we apply an integrative approach combining atomic force microscopy, cryo-electron tomography, network analysis, and molecular dynamics simulations to directly measure the mechanical response of single lamin filaments in three-dimensional meshwork. Endogenous lamin filaments portray non-Hookean behavior – they deform reversibly at a few hundred picoNewtons and stiffen at nanoNewton forces. The filaments are extensible, strong and tough similar to natural silk and superior to the synthetic polymer Kevlar^®. Graph theory analysis shows that the lamin meshwork is not a random arrangement of filaments but exhibits small-world properties. Our results suggest that lamin filaments arrange to form an emergent meshwork whose topology dictates the mechanical properties of individual filaments. The quantitative insights imply a role of meshwork topology in laminopathies.

Mechanical strength of in situ assembled nuclear lamin filaments arranged in a 3D meshwork is unclear. Here, using mechanical, structural and simulation tools, the authors report the hierarchical organization of the lamin meshwork that imparts strength and toughness to lamin filaments at par with silk and Kevlar^®

Anisotropic Dynamics and Mechanics of Macromolecular Crystals Containing Lattice-Patterned Polymer Networks

The mechanical and functional properties of many crystalline materials depend on cooperative changes in lattice arrangements in response to external perturbations. However, the flexibility and adaptiveness of crystalline materials are limited. Additionally, the bottom-up, molecular-level design of crystals with desired dynamic and mechanical properties at the macroscopic level remains a considerable challenge. To address these challenges, we had previously integrated mesoporous, cubic ferritin crystals with hydrogel networks, resulting in hybrid materials (polymer-integrated crystals or PIX) which could undergo dramatic structural changes while maintaining crystalline periodicity and display efficient self-healing. The dynamics and mechanics of these ferritin-PIX were devoid of directionality, which is an important attribute of many molecular and macroscopic materials/devices. In this study, we report that such directionality can be achieved through the use of ferritin crystals with anisotropic symmetries (rhombohedral or trigonal), which enable the templated formation of patterned hydrogel networks in crystallo. The resulting PIX expand and contract anisotropically without losing crystallinity, undergo prompt bending motions in response to stimuli, and self-heal efficiently, capturing some of the essential features of sophisticated biological devices like skeletal muscles.

Tunable and Cooperative Thermomechanical Properties of Protein-Metal-Organic Frameworks

We recently introduced protein-metal-organic frameworks (protein-MOFs) as chemically designed protein crystals, composed of ferritin nodes that predictably assemble into 3D lattices upon coordination of various metal ions and ditopic, hydroxamate-based linkers. Owing to their unique tripartite construction, protein-MOFs possess extremely sparse lattice connectivity, suggesting that they might display unusual thermomechanical properties. Leveraging the synthetic modularity of ferritin-MOFs, we investigated the temperature-dependent structural dynamics of six distinct frameworks. Our results show that the thermostabilities of ferritin-MOFs can be tuned through the metal component or the presence of crowding agents. Our studies also reveal a framework that undergoes a reversible and isotropic first-order phase transition near-room temperature, corresponding to a 4% volumetric change within 1 °C and a hysteresis window of ∼10 °C. This highly cooperative crystal-to-crystal transformation, which stems from the soft crystallinity of ferritin-MOFs, illustrates the advantage of modular construction strategies in discovering tunable-and unpredictable-material properties.

Single molecule protein stabilisation translates to macromolecular mechanics of a protein network

Folded globular proteins are attractive building blocks for biopolymer-based materials, as their mechanically resistant structures carry out diverse biological functionality. While much is now understood about the mechanical response of single folded proteins, a major challenge is to understand and predictably control how single protein mechanics translates to the collective response of a network of connected folded proteins. Here, by utilising the binding of maltose to hydrogels constructed from photo-chemically cross-linked maltose binding protein (MBP), we investigate the effects of protein stabilisation at the molecular level on the macroscopic mechanical and structural properties of a protein-based hydrogel. Rheological measurements show an enhancement in the mechanical strength and energy dissipation of MBP hydrogels in the presence of maltose. Circular dichroism spectroscopy and differential scanning calorimetry measurements show that MBP remains both folded and functional in situ. By coupling these mechanical measurements with mesoscopic structural information obtained by small angle scattering, we propose an occupation model in which higher proportions of stabilised, ligand occupied, protein building blocks translate their increased stability to the macroscopic properties of the hydrogel network. This provides powerful opportunities to exploit environmentally responsive folded protein-based biomaterials for many broad applications.

Connectivity and plasticity determine collagen network fracture

Collagen forms the structural scaffold of connective tissues in all mammals. Tissues are remarkably resistant against mechanical deformations because collagen molecules hierarchically self-assemble in fibrous networks that stiffen with increasing strain. Nevertheless, collagen networks do fracture when tissues are overloaded or subject to pathological conditions such as aneurysms. Prior studies of the role of collagen in tissue fracture have mainly focused on tendons, which contain highly aligned bundles of collagen. By contrast, little is known about fracture of the orientationally more disordered collagen networks present in many other tissues such as skin and cartilage. Here, we combine shear rheology of reconstituted collagen networks with computer simulations to investigate the primary determinants of fracture in disordered collagen networks. We show that the fracture strain is controlled by the coordination number of the network junctions, with less connected networks fracturing at larger strains. The hierarchical structure of collagen fine-tunes the fracture strain by providing structural plasticity at the network and fiber level. Our findings imply that low connectivity and plasticity provide protective mechanisms against network fracture that can optimize the strength of biological tissues.

Sonification based de novo protein design using artificial intelligence, structure prediction, and analysis using molecular modeling

We report the use of a deep learning model to design de novo proteins, based on the interplay of elementary building blocks via hierarchical patterns. The deep neural network model is based on translating protein sequences and structural information into a musical score that features different pitches for each of the amino acids, and variations in note length and note volume reflecting secondary structure information and information about the chain length and distinct protein molecules. We train a deep learning model whose architecture is composed of several long short-term memory units from data consisting of musical representations of proteins classified by certain features, focused here on alpha-helix rich proteins. Using the deep learning model, we then generate de novo musical scores and translate the pitch information and chain lengths into sequences of amino acids. We use a Basic Local Alignment Search Tool to compare the predicted amino acid sequences against known proteins, and estimate folded protein structures using the Optimized protein fold RecognitION method (ORION) and MODELLER. We find that the method proposed here can be used to design de novo proteins that do not exist yet, and that the designed proteins fold into specified secondary structures. We validate the newly predicted protein by molecular dynamics equilibration in explicit water and subsequent characterization using a normal mode analysis. The method provides a tool to design novel protein materials that could find useful applications as materials in biology, medicine, and engineering.

Wave Propagation and Energy Dissipation in Collagen Molecules

Collagen is the key protein of connective tissue (i.e., skin, tendons and ligaments, and cartilage, among others), accounting for 25-35% of the whole-body protein content and conferring mechanical stability. This protein is also a fundamental building block of bone because of its excellent mechanical properties together with carbonated hydroxyapatite minerals. Although the mechanical resilience and viscoelasticity have been studied both in vitro and in vivo from the molecular to tissue level, wave propagation properties and energy dissipation have not yet been deeply explored, in spite of being crucial to understanding the vibration dynamics of collagenous structures (e.g., eardrum, cochlear membranes) upon impulsive loads. By using a bottom-up atomistic modeling approach, here we study a collagen peptide under two distinct impulsive displacement loads, including longitudinal and transversal inputs. Using a one-dimensional string model as a model system, we investigate the roles of hydration and load direction on wave propagation along the collagen peptide and the related energy dissipation. We find that wave transmission and energy-dissipation strongly depend on the loading direction. Also, the hydrated collagen peptide can dissipate five times more energy than dehydrated one. Our work suggests a distinct role of collagen in term of wave transmission of different tissues such as tendon and eardrum. This study can step toward understanding the mechanical behavior of collagen upon transient loads, impact loading and fatigue, and designing biomimetic and bioinspired materials to replace specific native tissues such as the tympanic membrane.

3D Printing of Silk Protein Structures by Aqueous Solvent-Directed Molecular Assembly

Hierarchical molecular assembly is a fundamental strategy for manufacturing protein structures in nature. However, to translate this natural strategy into advanced digital manufacturing like three-dimensional (3D) printing remains a technical challenge. This work presents a 3D printing technique with silk fibroin to address this challenge, by rationally designing an aqueous salt bath capable of directing the hierarchical assembly of the protein molecules. This technique, conducted under aqueous and ambient conditions, results in 3D proteinaceous architectures characterized by intrinsic biocompatibility/biodegradability and robust mechanical features. The versatility of this method is shown in a diversity of 3D shapes and a range of functional components integrated into the 3D prints. The manufacturing capability is exemplified by the single-step construction of perfusable microfluidic chips which eliminates the use of supporting or sacrificial materials. The 3D shaping capability of the protein material can benefit a multitude of biomedical devices, from drug delivery to surgical implants to tissue scaffolds. This work also provides insights into the recapitulation of solvent-directed hierarchical molecular assembly for artificial manufacturing.

Revealing the assembly of filamentous proteins with scanning transmission electron microscopy

Filamentous proteins are responsible for the superior mechanical strength of our cells and tissues. The remarkable mechanical properties of protein filaments are tied to their complex molecular packing structure. However, since these filaments have widths of several to tens of nanometers, it has remained challenging to quantitatively probe their molecular mass density and three-dimensional packing order. Scanning transmission electron microscopy (STEM) is a powerful tool to perform simultaneous mass and morphology measurements on filamentous proteins at high resolution, but its applicability has been greatly limited by the lack of automated image processing methods. Here, we demonstrate a semi-automated tracking algorithm that is capable of analyzing the molecular packing density of intra- and extracellular protein filaments over a broad mass range from STEM images. We prove the wide applicability of the technique by analyzing the mass densities of two cytoskeletal proteins (actin and microtubules) and of the main protein in the extracellular matrix, collagen. The high-throughput and spatial resolution of our approach allow us to quantify the internal packing of these filaments and their polymorphism by correlating mass and morphology information. Moreover, we are able to identify periodic mass variations in collagen fibrils that reveal details of their axially ordered longitudinal self-assembly. STEM-based mass mapping coupled with our tracking algorithm is therefore a powerful technique in the characterization of a wide range of biological and synthetic filaments.

Patterned Amyloid Materials Integrating Robustness and Genetically Programmable Functionality

The precise manipulation, localization, and assembly of biological and bioinspired molecules into organized structures have greatly promoted material science and bionanotechnology. Further technological innovation calls for new patternable soft materials with the long-sought qualities of environmental tolerance and functional flexibility. Here, we report a patterned amyloid material (PAM) platform for producing hierarchically ordered structures that integrate these material attributes. This platform, combining soft lithography with generic amyloid monomer inks (consisting of genetically engineered biofilm proteins dissolved in hexafluoroisopropanol), along with methanol-assisted curing, enables the spatially controlled deposition and in situ reassembly of amyloid monomers. The resulting patterned structures exhibit spectacular chemical and thermal stability and mechanical robustness under harsh conditions. The PAMs can be programmed for a vast array of multilevel functionalities, including anchoring nanoparticles, enabling diverse fluorescent protein arrays, and serving as self-supporting porous sheets for cellular growth. This PAM platform will not only drive innovation in biomanufacturing but also broaden the applications of patterned soft architectures in optics, electronics, biocatalysis, analytical regents, cell engineering, medicine, and other areas.

Biomimetic Pulsating Vesicles with Both pH-Tunable Membrane Permeability and Light-Triggered Disassembly-Re-assembly Behaviors Prepared by Supra-Amphiphilic Helices

The reversible unfolding-refolding transition is considerably important for natural elastomeric proteins (e.g., titin) to fulfill their biological functions. It is of great importance to develop synthetic versions by borrowing their unique stretchable design principles. Herein, we present a novel pulsating vesicle by means of the aqueous self-assembly of supra-amphiphilic helices. Interestingly, this vesicle simultaneously features dynamic swelling and shrinkage movements in response to external proton triggers. Titin-like unfolding-refolding transformation of artificial helices was proved to play a crucial role in this pulsatile motion. Moreover, the vesicular membrane of this vesicle has exhibited tunable permeability during reversible expansion and contraction circulation. Meanwhile, light can also be used as a driving force to further regulate the disassembly-reassembly transformation of the pulsating vesicle. In addition, the drug delivery system was also employed as an investigating model to estimate the permeability variation and disassembly-reassembly behaviors of the pulsating vesicles, which displayed unique dual quick- and sustained-release behaviors toward anti-cancer agents. It is anticipated that this work opens an avenue for fabricating novel stretchable biomimetics by using the exclusive unfolding-refolding nature of artificial foldamers.

Study on the oxidation of fibrinogen using Fe3O4 magnetic nanoparticles and its influence to the formation of fibrin

Oxidative stress accompanies various diseases associated with chronic inflammation. In this work, H₂O₂ and H₂O₂-Fe₃O₄ magnetic nanoparticles were used as two reactive oxygen species to study the oxidative stress for the structure and polymerization behaviour of fibrinogen molecules. The alterations of secondary structure and component of fibrinogen molecule were characterized by circular dichroism spectra, ultraviolet-visible spectra and fluorescence spectra, the viscoelasticity of fibrinogen solution was studied by dynamic light scattering microrheology. Based on the molecular dynamics simulations and fluorescence properties, the possible oxidative stress sites were analyzed and confirmed by Tb³⁺ probe. The hydrophobicity/philicity and electrostatic net charges present on the exterior part of the fibrinogen molecules were measured with zeta potential. The height and image analysis obtained from atomic force microscope indicated that oxidative stress of fibrinogen molecules could influence the equilateral junctions of protofibrils and the different cross-linking patterns between the α- and γ-chains, result in the decrease of the fibre size, form a higher proportion of branching and a denser aggregation state. This study will provide insights into the misfolding and fibril formation of disease-associated fibrinogen, facilitate an increased understanding of how oxidative stress in vivo affects the formation and polymerization of fibrin, and support efforts for the improved treatment of patients suffering from the thrombotic disease.

The Rise of Hierarchical Nanostructured Materials from Renewable Sources: Learning from Nature

Mimicking Nature implies the use of bio-inspired hierarchical designs to manufacture nanostructured materials. Such materials should be produced from sustainable sources ( e.g., biomass) and through simple processes that use mild conditions, enabling sustainable solutions. The combination of different types of nanomaterials and the implementation of different features at different length scales can provide synthetic hierarchical nanostructures that mimic natural materials, outperforming the properties of their constitutive building blocks. Taking recent developments in flow-assisted assembly of nanocellulose crystals as a starting point, we review the state of the art and provide future perspectives on the manufacture of hierarchical nanostructured materials from sustainable sources, assembly techniques, and potential applications.

Interchain Overlap Affects Formation of Silk Fibroin Secondary Structures on Hydrophobic Polystyrene Surface Detected via Achiral/Chiral Sum Frequency Generation

Silk fibroin (SF) has been engineered in the biomedical applications on account of its structural robustness, biocompatibility, and biodegradability. However, in situ study is still lacking with respect to the formation of SF secondary structures at the interface. In this paper, by using methanol as an inducing agent, the formation of SF secondary structures at the polystyrene (PS)/SF solution interfaces was detected with achiral and chiral sum frequency generation (SFG) vibrational spectroscopy. SF solutions with two concentrations above and below the critical overlapping concentration ( C*) of SF (∼1.8 mg/mL) were chosen, namely, 90 and 1 mg/mL. We found that above C*, before adding methanol to the protein solution, no ordered SF secondary structures could be detected at the PS/SF solution interface; oppositely, after adding methanol to the protein solution, ordered SF secondary structure, for example, antiparallel β-sheet, could be formed at the PS/protein solution interface. Below C*, both before and after adding methanol to the SF solution, ordered SF secondary structure such as antiparallel β-sheet could be formed. Besides, the addition of methanol could induce the formation of an extended helical structure, verified by the achiral and chiral characteristic bands. Because C* represents a critical solution concentration above which the SF chains can interact with each other and below which the SF chains are isolated in the solution, this achiral/chiral SFG study emphasizes the importance of the chain-chain interaction or spatial confinement on the formation of the protein secondary structures, which provides an additional dimension for the future study of interfacial protein folding.

The quest for mechanically and biologically functional soft biomaterials via soft network composites

Developing multifunctional soft biomaterials capable of addressing all the requirements of the complex tissue regeneration process is a multifaceted problem. In order to tackle the current challenges, recent research efforts are increasingly being directed towards biomimetic design concepts that can be translated into soft biomaterials via advanced manufacturing technologies. Among those, soft network composites consisting of a continuous hydrogel matrix and a reinforcing fibrous network closely resemble native soft biological materials in terms of design and composition as well as physicochemical properties. This article reviews soft network composite systems with a particular emphasis on the design, biomaterial and fabrication aspects within the context of soft tissue engineering and drug delivery applications.

De Novo Design of Recombinant Spider Silk Proteins for Material Applications

Spider silks are well known for their superior mechanical properties that are stronger and tougher than steel despite being assembled at close to ambient conditions and using water as the solvent. However, it is a significant challenge to utilize spider silks for practical applications due to their limited sources. Fortunately, genetic engineering techniques offer a promising approach to produce useable amounts of spider silk variants. Starting from these recombinant spider silk proteins, a series of experiments and simulations strategies are developed to improve the recombinant spider silk proteins (RSSP) material design and fabrication with the aim of biomimicking the structure-property-function relationships of spider silks. Accordingly, in this review, the authors first introduce the structure-property-function relationship of spider silks. Then, the recent progress in the genetic synthesis of RSSPs is discussed and their related multiscale self-assembly behaviors is summarized. Finally, the authors outline works utilizing multiscale modeling to assist RSSP material design.

Nanofibrils in nature and materials engineering

Nanofibrillar materials, such as cellulose, chitin and silk, are highly ordered architectures, formed through the self-assembly of repetitive building blocks into higher-order structures, which are stabilized by non-covalent interactions. This hierarchical building principle endows many biological materials with remarkable mechanical strength, anisotropy, flexibility and optical properties, such as structural colour. These features make nanofibrillar biopolymers interesting candidates for the development of strong, sustainable and biocompatible materials for environmental, energy, optical and biomedical applications. However, recreating their architecture is challenging from an engineering perspective. Rational design approaches, applying a combination of theoretical and experimental protocols, have enabled the design of biopolymer-based materials through mimicking nature's multiscale assembly approach. In this Review, we summarize hierarchical design strategies of cellulose, silk and chitin, focusing on nanoconfinement, fibrillar orientation and alignment in 2D and 3D structures. These multiscale architectures are discussed in the context of mechanical and optical properties, and different fabrication strategies for the manufacturing of biopolymer nanofibril-based materials are investigated. We highlight the contribution of rational material design strategies to the development of mechanically anisotropic and responsive materials and examine the future of the material-by-design paradigm.

Rationally designed synthetic protein hydrogels with predictable mechanical properties

Designing synthetic protein hydrogels with tailored mechanical properties similar to naturally occurring tissues is an eternal pursuit in tissue engineering and stem cell and cancer research. However, it remains challenging to correlate the mechanical properties of protein hydrogels with the nanomechanics of individual building blocks. Here we use single-molecule force spectroscopy, protein engineering and theoretical modeling to prove that the mechanical properties of protein hydrogels are predictable based on the mechanical hierarchy of the cross-linkers and the load-bearing modules at the molecular level. These findings provide a framework for rationally designing protein hydrogels with independently tunable elasticity, extensibility, toughness and self-healing. Using this principle, we demonstrate the engineering of self-healable muscle-mimicking hydrogels that can significantly dissipate energy through protein unfolding. We expect that this principle can be generalized for the construction of protein hydrogels with customized mechanical properties for biomedical applications.

Micromechanical model for protein materials: From macromolecules to macroscopic fibers

We propose a model for the mechanical behavior of protein materials. Based on a limited number of experimental macromolecular parameters (persistence and contour length) we obtain the macroscopic behavior of keratin fibers (human, cow, and rabbit hair), taking into account the damage and residual stretches effects that are fundamental in many functions of life. We also show the capability of our approach to describe the main dissipation and permanent strain effects observed in the more complex spider silk fibers. The comparison between our results and the data obtained experimentally from cyclic tests demonstrates that our model is robust and is able to reproduce with a remarkable accuracy the experimental behavior of all protein materials we tested.

Multicomponent self-assembly as a tool to harness new properties from peptides and proteins in material design

Nature is enriched with a wide variety of complex, synergistic and highly functional protein-based multicomponent assemblies.

Functional and Biomimetic Materials for Engineering of the Three-Dimensional Cell Microenvironment

The cell microenvironment has emerged as a key determinant of cell behavior and function in development, physiology, and pathophysiology. The extracellular matrix (ECM) within the cell microenvironment serves not only as a structural foundation for cells but also as a source of three-dimensional (3D) biochemical and biophysical cues that trigger and regulate cell behaviors. Increasing evidence suggests that the 3D character of the microenvironment is required for development of many critical cell responses observed in vivo, fueling a surge in the development of functional and biomimetic materials for engineering the 3D cell microenvironment. Progress in the design of such materials has improved control of cell behaviors in 3D and advanced the fields of tissue regeneration, in vitro tissue models, large-scale cell differentiation, immunotherapy, and gene therapy. However, the field is still in its infancy, and discoveries about the nature of cell-microenvironment interactions continue to overturn much early progress in the field. Key challenges continue to be dissecting the roles of chemistry, structure, mechanics, and electrophysiology in the cell microenvironment, and understanding and harnessing the roles of periodicity and drift in these factors. This review encapsulates where recent advances appear to leave the ever-shifting state of the art, and it highlights areas in which substantial potential and uncertainty remain.