Hierarchies, multiple energy barriers, and robustness govern the fracture mechanics of alpha-helical and beta-sheet protein domains

Application of Silk Light Chain on a Graphene Composite Surface: A Molecular Dynamics and Electrochemical Experiment

The surface functionalization of pristine graphene (PG) with beneficial biocomposites is important for biomedical and tissue engineering. This study introduces silk light chain as novel biocomposites to increase the biocompatibility of PG. We explored the supramolecular structures of the silk heavy and light chains. Through molecular dynamics, we compared and analyzed the structural effects and binding mechanisms of these domains in their interaction with PG. Our results highlighted a significant hydrophobic interaction between the silk light chain and PG, without structural collapse. The supramolecular structure of the silk light chain was identified by analyzing the amino acids bound to PG. Moreover, using the silk light chain, the hydrophobic surface of PG has changed to a hydrophilic surface, and the silk light-chain-PG electron transfer rate was evaluated for the graphene congeners: graphene oxide (GO) and reduced graphene oxide. Therefore, we are confident that the dispersibility and biocompatibility of PG can be increased using silk light chains, which will contribute to broadening the field of application of PG-based materials.

CSSP-2.0: A refined consensus method for accurate protein secondary structure prediction

Studying the relationship between sequences and their corresponding three-dimensional structure assists structural biologists in solving the protein-folding problem. Despite several experimental and in-silico approaches, still understanding or decoding the three-dimensional structures from the sequence remains a mystery. In such cases, the accuracy of the structure prediction plays an indispensable role. To address this issue, an updated web server (CSSP-2.0) has been created to improve the accuracy of our previous version of CSSP by deploying the existing algorithms. It uses input as probabilities and predicts the consensus for the secondary structure as a highly accurate three-state Q3 (helix, strand, and coil). This prediction is achieved using six recent top-performing methods: MUFOLD-SS, RaptorX, PSSpred v4, PSIPRED, JPred v4, and Porter 5.0. CSSP-2.0 validation includes datasets involving various protein classes from the PDB, CullPDB, and AlphaFold databases. Our results indicate a significant improvement in the accuracy of the consensus Q3 prediction. Using CSSP-2.0, crystallographers can sort out the stable regular secondary structures from the entire complex structure, which would aid in inferring the functional annotation of hypothetical proteins. The web server is freely available at https://bioserver3.physics.iisc.ac.in/cgi-bin/cssp-2/.

Accumulation of Hydrogen Bonds and van der Waals Interactions Determines Force Response between Two Parallel Cellulose Chains: Steered Molecular Dynamics Simulations

We investigated the response forces between two parallel cellulose chains during the shearing and tearing processes by using steered molecular dynamics simulations. It was found that there are two logarithmic dependencies between response force and pulling speed in shearing processes but only one in tearing, according to Bell's equation by fitting the f-ln v curve. The mechanism is that there are 2-fold interactions determining the force response between two parallel cellulose chains resisting chain separation during a shearing process. Our results indicate that hydrogen bonds dominate the interchain interactions in the fast pull mode (FPM) for shearing, while van der Waals interactions dominate in the slow pull mode (SPM). For tearing, the one-by-one breaking of hydrogen bonds and van der Waals interactions plays a main role.

ProtAgents: protein discovery via large language model multi-agent collaborations combining physics and machine learning

Designing de novo proteins beyond those found in nature holds significant promise for advancements in both scientific and engineering applications. Current methodologies for protein design often rely on AI-based models, such as surrogate models that address end-to-end problems by linking protein structure to material properties or vice versa. However, these models frequently focus on specific material objectives or structural properties, limiting their flexibility when incorporating out-of-domain knowledge into the design process or comprehensive data analysis is required. In this study, we introduce ProtAgents, a platform for de novo protein design based on Large Language Models (LLMs), where multiple AI agents with distinct capabilities collaboratively address complex tasks within a dynamic environment. The versatility in agent development allows for expertise in diverse domains, including knowledge retrieval, protein structure analysis, physics-based simulations, and results analysis. The dynamic collaboration between agents, empowered by LLMs, provides a versatile approach to tackling protein design and analysis problems, as demonstrated through diverse examples in this study. The problems of interest encompass designing new proteins, analyzing protein structures and obtaining new first-principles data - natural vibrational frequencies - via physics simulations. The concerted effort of the system allows for powerful automated and synergistic design of de novo proteins with targeted mechanical properties. The flexibility in designing the agents, on one hand, and their capacity in autonomous collaboration through the dynamic LLM-based multi-agent environment on the other hand, unleashes great potentials of LLMs in addressing multi-objective materials problems and opens up new avenues for autonomous materials discovery and design.

Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to β-Sheet Transition in Tubulins: Potential Implications for Alzheimer's and Other Neurodegenerative Diseases

In small clinical studies, the application of transcranial photobiomodulation (PBM), which typically delivers low-intensity near-infrared (NIR) to treat the brain, has led to some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, despite the extensive literature detailing the mechanisms of action underlying PBM outcomes, the specific mechanisms affecting neurodegenerative diseases are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and thus provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer's and other neurodegenerative diseases. Thus, we investigated the effects of PBM on these cellular structures in the quest for insights into the underlying therapeutic mechanisms. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300-1900 cm-1)-in particular, in the amide I band (1600-1700 cm-1)-were used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed, producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of polymerized NIR-exposed tubulin, characterized by a notable decrease in α-helix content and a concurrent increase in β-sheets compared to the control samples. This PBM-induced α-helix to β-sheet transition connects to reduced microtubule stability and the introduction of dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer's disease, through the introduction of an intervention following this transition.

ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model

Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play crucial roles in mechanobiology. However, going beyond natural designs to discover proteins that meet specified mechanical properties remains challenging. Here, we report a generative model that predicts protein designs to meet complex nonlinear mechanical property-design objectives. Our model leverages deep knowledge on protein sequences from a pretrained protein language model and maps mechanical unfolding responses to create proteins. Via full-atom molecular simulations for direct validation, we demonstrate that the designed proteins are de novo, and fulfill the targeted mechanical properties, including unfolding energy and mechanical strength, as well as the detailed unfolding force-separation curves. Our model offers rapid pathways to explore the enormous mechanobiological protein sequence space unconstrained by biological synthesis, using mechanical features as the target to enable the discovery of protein materials with superior mechanical properties.

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.

Bond clusters control rupture force limit in shear loaded histidine-Ni2+ metal-coordinated proteins

Dynamic noncovalent interactions are pivotal to the structure and function of biological proteins and have been used in bioinspired materials for similar roles. Metal-coordination bonds, in particular, are especially tunable and enable control over static and dynamic properties when incorporated into synthetic materials. Despite growing efforts to engineer metal-coordination bonds to produce strong, tough, and self-healing materials, the systematic characterization of the exact contribution of these bonds towards mechanical strength and the effect of geometric arrangements is missing, limiting the full design potential of these bonds. In this work, we engineer the cooperative rupture of metal-coordination bonds to increase the rupture strength of metal-coordinated peptide dimers. Utilizing all-atom steered molecular dynamics simulations on idealized bidentate histidine-Ni²⁺ coordinated peptides, we show that histidine-Ni²⁺ bonds can rupture cooperatively in groups of two to three bonds. We find that there is a strength limit, where adding additional coordination bonds does not contribute to the additional increase in the protein rupture strength, likely due to the highly heterogeneous rupture behavior exhibited by the coordination bonds. Further, we show that this coordination bond limit is also found natural metal-coordinated biological proteins. Using these insights, we quantitatively suggest how other proteins can be rationally designed with dynamic noncovalent interactions to exhibit cooperative bond breaking behavior. Altogether, this work provides a quantitative analysis of the cooperativity and intrinsic strength limit for metal-coordination bonds with the aim of advancing clear guiding molecular principles for the mechanical design of metal-coordinated materials.

Computational Design and Manufacturing of Sustainable Materials through First-Principles and Materiomics

Engineered materials are ubiquitous throughout society and are critical to the development of modern technology, yet many current material systems are inexorably tied to widespread deterioration of ecological processes. Next-generation material systems can address goals of environmental sustainability by providing alternatives to fossil fuel-based materials and by reducing destructive extraction processes, energy costs, and accumulation of solid waste. However, development of sustainable materials faces several key challenges including investigation, processing, and architecting of new feedstocks that are often relatively mechanically weak, complex, and difficult to characterize or standardize. In this review paper, we outline a framework for examining sustainability in material systems and discuss how recent developments in modeling, machine learning, and other computational tools can aid the discovery of novel sustainable materials. We consider these through the lens of materiomics, an approach that considers material systems holistically by incorporating perspectives of all relevant scales, beginning with first-principles approaches and extending through the macroscale to consider sustainable material design from the bottom-up. We follow with an examination of how computational methods are currently applied to select examples of sustainable material development, with particular emphasis on bioinspired and biobased materials, and conclude with perspectives on opportunities and open challenges.

Atomistic insights into migration mechanism of graphene-based membranes on soil mineral phases

Graphene-based membranes (GBM) will migrate in the soil and enter the groundwater system or plant roots, which will eventually pose potential risks to human beings. The migration mechanism of GBM depends on the interface behavior of complex soil components. Herein, we use molecular dynamics (MD) simulations to probe the interface behavior between GBM and three type minerals (quartz, calcite and kaolinite). Based on the investigation of binding energy, maximum pulling force and barrier energy, the order of the difficulty of GBM adsorption and desorption on the three minerals from small to large is roughly: quartz, calcite and kaolinite respectively. The graphene-oxide (GO), improves the binding energy and energy barrier, making GBM difficult to migrate in soil. Remarkably, a larger GBM sheet and high velocity external load improve GBM migration in soil to a certain extent. These investigations give the dynamic information on the GBM/mineral interaction and provide nanoscale insights into the migration mechanisms of GBM in soil.

SARS-CoV-2 Infection-Of Music and Mechanics of Its Spikes! A Perspective

The COVID-19 pandemic has been inflicted upon humanity by the SARS-CoV-2 virus, the latest insidious incarnation of the coronaviruses group. While in its wake intense scientific research has produced breakthrough vaccines and cures, there still exists an immediate need to further understand the origin, mechanobiology and biochemistry, and destiny of this virus so that future pandemics arising from similar coronaviruses may be contained more effectively. In this Perspective, we discuss the various evidential findings of virus propagation and connect them to respective underpinning cellular biomechanical states leading to corresponding manifestations of the viral activity. We further propose avenues to tackle the virus, including from a "musical" vantage point, and contain its relentless strides that are currently afflicting the global populace.

ColGen: An end-to-end deep learning model to predict thermal stability of de novo collagen sequences

Collagen is the most abundant structural protein in humans, with dozens of sequence variants accounting for over 30% of the protein in an animal body. The fibrillar and hierarchical arrangements of collagen are critical in providing mechanical properties with high strength and toughness. Due to this ubiquitous role in human tissues, collagen-based biomaterials are commonly used for tissue repairs and regeneration, requiring chemical and thermal stability over a range of temperatures during materials preparation ex vivo and subsequent utility in vivo. Collagen unfolds from a triple helix to a random coil structure during a temperature interval in which the midpoint or T_m is used as a measure to evaluate the thermal stability of the molecules. However, finding a robust framework to facilitate the design of a specific collagen sequence to yield a specific T_m remains a challenge, including using conventional molecular dynamics modeling. Here we propose a de novo framework to provide a model that outputs the T_m values of input collagen sequences by incorporating deep learning trained on a large data set of collagen sequences and corresponding T_m values. By using this framework, we are able to quickly evaluate how mutations and order in the primary sequence affect the stability of collagen triple helices. Specifically, we confirm that mutations to glycines, mutations in the middle of a sequence, and short sequence lengths cause the greatest drop in T_m values.

Interpretation of Single-Molecule Force Experiments on Proteins Using Normal Mode Analysis

Single-molecule force spectroscopy experiments allow protein folding and unfolding to be explored using mechanical force. Probably the most informative technique for interpreting the results of these experiments at the structural level makes use of steered molecular dynamics (MD) simulations, which can explicitly model the protein under load. Unfortunately, this technique is computationally expensive for many of the most interesting biological molecules. Here, we find that normal mode analysis (NMA), a significantly cheaper technique from a computational perspective, allows at least some of the insights provided by MD simulation to be gathered. We apply this technique to three non-homologous proteins that were previously studied by force spectroscopy: T4 lysozyme (T4L), Hsp70 and the glucocorticoid receptor domain (GCR). The NMA results for T4L and Hsp70 are compared with steered MD simulations conducted previously, and we find that we can recover the main results. For the GCR, which did not undergo MD simulation, our approach identifies substructures that correlate with experimentally identified unfolding intermediates. Overall, we find that NMA can make a valuable addition to the analysis toolkit for the structural analysis of single-molecule force experiments on proteins.

Helix-coil transition and conformational deformity in Aβ42-monomer: a case study using the Zn2+ cation

The metal ions (like Fe2+, Zn²⁺, Cu2+) are known to influence the amyloid beta (Aβ) aggregation. In this study, we have examined the conformational and dynamical changes during the coordination of Aβ-monomer with the Zn2+ ion using all-atom molecular dynamics (MD) simulations using explicit solvent models. We have probed the unfolding of the full-length Aβ₄₂ monomer both inclusive and exclusive of the Zn2+ cation, with 1:1 ratio of the peptide and the Zn2+ cation. The inclusion of the Zn2+ cation shows differential intra-peptide interactions which has been probed using various analyses. The Helix - Coil transition of the wild type Aβ42 monomer is studied using the steered molecular dynamics simulations by taking the end-to-end C-α distance across the peptide. This gives an idea of the unequal intra - peptide and peptide - water interactions being found across the length of the Aβ monomer. The transition of an α-helix dominated wild-type (WT) Aβ structure to the unfolded coil structure gives significant evidence of the intra-peptide hydrogen bonding shifts in the presence of the Zn2+ cation. This accounts for the structural and the dynamical variations that take place in the Aβ monomer in the presence of the Zn2+ cation to mimic the conditions/environment at the onset of fibrillation.Communicated by Ramaswamy H. Sarma.

Practical Guide to Single-Protein AFM Nanomechanical Spectroscopy Mapping: Insights and Pitfalls As Unraveled by All-Atom MD Simulations on Immunoglobulin G

Atomic force microscopy is an invaluable characterization tool in almost every biophysics laboratory. However, obtaining atomic/sub-nanometer resolution on single proteins has thus far remained elusive-a feat long achieved on hard substrates. In this regard, nanomechanical spectroscopy mapping may provide a viable approach to overcome this limitation. By complementing topography with mechanical properties measured locally, one may thus enhance spatial resolution at the single-protein level. In this work, we perform all-atom molecular dynamics simulations of the indentation process on a single immunoglobulin G (IgG) adsorbed on a graphene slab. Our simulations reveal three different stages as a function of strain: a noncontact regime-where the mechanical response is linked to the presence of the water environment- followed by an elastic response and a final plastic deformation regime. In the noncontact regime, we are able to identify hydrophobic/hydrophilic patches over the protein. This regime provides the most local mechanical information that allows one to discern different regions with similar height/topography and leads to the best spatial resolution. In the elastic regime, we conclude that the Young modulus is a well-defined property only within mechanically decoupled domains. This is caused by the fact that the elastic deformation is associated with a global reorganization of the domain. Differences in the mechanical response are large enough to clearly resolve domains within a single protein, such as the three subunits forming the IgG. Two events, unfolding or protein slipping, are observed in the plastic regime. Our simulations allow us to characterize these two processes and to provide a strategy to identify them in the force curves. Finally, we elaborate on possible challenges that could hamper the interpretation of such experiments/simulations and how to overcome them. All in all, our simulations provide a detailed picture of nanomechanical spectroscopy mapping on single proteins, showing its potential and the challenges that need to be overcome to unlock its full potential.

Knit Architecture for Water-Actuating Woolen Knitwear and Its Personalized Thermal Management

Personalized thermal management using water-actuated woolen knitwear has great potential for smart textile production. However, woolen knitwear exists in a wide range of forms with different derivatives. Manufacturing of smart woolen structures with excellent cooling properties is linked to certain parameters such as changes in loop formation, loop shape, and yarn arrangement upon stimulation of body fluids. To address this issue, textile knit structures with different physical and mechanical properties have been prepared using water-responsive descaled wool fibers and their smart heat and moisture regulation behavior have been investigated and compared to detect the fabric architectural effect on water actuation and cooling performance of woolen garments. The evidence suggests that the technical structure of the fabrics plays a crucial role in pore actuation and fabric cooling performance. The water actuation and thermal management abilities of single jersey were greatly enhanced because of unbalanced structures with lower mechanical stress among the loops and yarns. The experimental data is also in line with the theoretical analysis. Hence, the unbalanced structures control fast heat and mass transfer from the human body, which may offer a promising year-round clothing material to the wearer. This material can have a similar response upon contact with body sweat and humid environments and hence can act as a skinlike fabric. Their possible applications can lie in different fields, such as thermoregulation, functional clothing, sportswear, and medical care.

Unfolding mechanism and free energy landscape of single, stable, alpha helices at low pull speeds

Single alpha helices (SAHs) stable in isolated form are often found in motor proteins where they bridge functional domains. Understanding the mechanical response of SAHs is thus critical to understand their function. The quasi-static force-extension relation of a small number of SAHs is known from single-molecule experiments. Unknown, or still controversial, are the molecular scale details behind those observations. We show that the deformation mechanism of SAHs pulled from the termini at pull speeds approaching the quasi-static limit differs from that of typical helices found in proteins, which are stable only when interacting with other protein domains. Using molecular dynamics simulations with atomistic resolution at low pull speeds previously inaccessible to simulation, we show that SAHs start unfolding from the termini at all pull speeds we investigated. Unfolding proceeds residue-by-residue and hydrogen bond breaking is not the main event determining the barrier to unfolding. We use the molecular simulation data to test the cooperative sticky chain model. This model yields excellent fits of the force-extension curves and quantifies the distance, xE = 0.13 nm, to the transition state, the natural frequency of bond vibration, ν0 = 0.82 ns-1, and the height, V0 = 2.9 kcal mol-1, of the free energy barrier associated with the deformation of single residues. Our results demonstrate that the sticky chain model could advantageously be used to analyze experimental force-extension curves of SAHs and other biopolymers.

Frequency dependent inelastic response of collagen architecture of pig dermis under cyclic tensile loading: An experimental study

The evaluation of collagen architecture of the dermis in response to mechanical stimulation is important as it affects the macroscopic mechanical properties of the dermis. A detailed understanding of the processes involved in the alteration of the collagen structure is required to correlate the mechanical stimulation with tissue remodeling. This study investigated the effect of cyclic frequencies i.e. low (0.1 Hz), medium (2.0 Hz), and high (5.0 Hz) (physiological range) in the alteration of pig dermis collagen structure and its correlation with the macroscopic mechanical response of the dermis. The assessment of the collagen structure of virgin and mechanical tested specimens at tropocollagen, collagen fibril, and fiber level was performed using Fourier-transform infrared-attenuated total reflection (FTIR-ATR), atomic force microscopy (AFM), and scanning electron microscopy (SEM) respectively. After 10³ cycles, a significantly higher alteration in collagen structure with discrete plastic-type damage was found for low frequency. This frequency dependent alteration of the collagen structure was found in correlation with the dermis macroscopic response. The value of inelastic strain, stress softening, damage parameter (reduction in elastic modulus), and reduction in energy dissipation were observed significantly large for slow frequency. A power-law based empirical relations, as a function of frequency and number of cycles, were proposed to predict the value of inelastic strain and damage parameter. This study also suggests that hierarchical structural response against the mechanical stimulation is time-dependent rather than cycle-dependent, may affect the tissue remodeling.

Single-molecule mechanical unfolding experiments reveal a critical length for the formation of α-helices in peptides

α-Helix is the most predominant secondary structure in proteins and supports many functions in biological machineries. The conformation of the helix is dictated by many factors such as its primary sequence, intramolecular interactions, or the effect of the close environment. Several computational studies have proposed that there is a critical maximum length for the formation of intact compact helical structures, supporting the fact that most intact α-helices in proteins are constituted of a small number of amino acids. To obtain a detailed picture on the formation of α-helices in peptides and their mechanical stability, we have synthesized a long homopolypeptide of about 90 amino acids, poly(γ-benzyl-l-glutamate), and investigated its mechanical behaviour by AFM-based single-molecule force spectroscopy. The characteristic plateaus observed in the force-extension curves reveal the unfolding of a series of small helices (from 1 to 4) of about 20 amino acid residues connected to each other, rather than a long helix of 90 residues. Our results suggest the formation of a tertiary structure made of short helices with kinks, instead of an intact compact helical structure for sequences of more than 20 amino acid residues. To our knowledge, this is the first experimental evidence supporting the concept of a helical critical length previously proposed by several computational studies.

Monitoring Biochemical and Structural Changes in Human Periodontal Ligaments during Orthodontic Treatment by Means of Micro-Raman Spectroscopy

The aim of the study was to examine the biochemical and structural changes occurring in the periodontal ligament (PDL) during orthodontic-force application using micro-Raman spectroscopy ( μ -RS). Adolescent and young patients who needed orthodontic treatment with first premolar extractions were recruited. Before extractions, orthodontic forces were applied using a closed-coil spring that was positioned between the molar and premolar. Patients were randomly divided into three groups, whose extractions were performed after 2, 7, and 14 days of force application. From the extracted premolars, PDL samples were obtained, and a fixation procedure with paraformaldehyde was adopted. Raman spectra were acquired for each PDL sample in the range of 1000-3200 cm - 1 and the more relevant vibrational modes of proteins (Amide I and Amide III bands) and CH 2 and CH 3 modes were shown. Analysis indicated that the protein structure in the PDL samples after different time points of orthodontic-force application was modified. In addition, changes were observed in the CH 2 and CH 3 high wavenumber region due to local hypoxia and mechanical force transduction. The reported results indicated that μ -RS provides a valuable tool for investigating molecular interchain interactions and conformational modifications in periodontal fibers after orthodontic tooth movement, providing quantitative insight of time occurring for PDL molecular readjustment.

Design of hydrogel-based scaffolds for the treatment of spinal cord injuries

Hydrogel-based scaffold design approaches for the treatment of spinal cord injuries.

Machine learning model for fast prediction of the natural frequencies of protein molecules

Natural vibrations and resonances are intrinsic features of protein structures and enable differentiation of one structure from another. These nanoscale features are important to help to understand the dynamics of a protein molecule and identify the effects of small sequence or other geometric alterations that may not cause significant visible structural changes, such as point mutations associated with disease or drug design. Although normal mode analysis provides a powerful way to accurately extract the natural frequencies of a protein, it must meet several critical conditions, including availability of high-resolution structures, availability of good chemical force fields and memory-intensive large-scale computing resources. Here, we study the natural frequency of over 100 000 known protein molecular structures from the Protein Data Bank and use this dataset to carefully investigate the correlation between their structural features and these natural frequencies by using a machine learning model composed of a Feedforward Neural Network made of four hidden layers that predicts the natural frequencies in excellent agreement with full-atomistic normal mode calculations, but is significantly more computationally efficient. In addition to the computational advance, we demonstrate that this model can be used to directly obtain the natural frequencies by merely using five structural features of protein molecules as predictor variables, including the largest and smallest diameter, and the ratio of amino acid residues with alpha-helix, beta strand and 3–10 helix domains. These structural features can be either experimentally or computationally obtained, and do not require a full-atomistic model of a protein of interest. This method is helpful in predicting the absorption and resonance functions of an unknown protein molecule without solving its full atomic structure.

Natural vibrations and resonances are intrinsic features of protein structures and can be learnt from existing structures.

How strong are hydrogen bonds in the peptide model?

We provide a methodology based on the steered molecular dynamics simulations and dynamic force spectroscopy calculations to determine the kinetic and energetic characteristics of hydrogen bonds.

Plastic Deformation and Fragmentation of Strained Actin Filaments

The assembly of actin filaments and filament networks generate forces that drive cell and vesicle movement. These structures and the comprising actin filaments must be mechanically stable to sustain these forces and maintain their structural integrity. Filaments in these dynamic structures must also be disassembled to recycle and replenish the pool of actin monomers available for polymerization. Actin-severing proteins such as cofilin and contractile myosin motor proteins fragment these nominally stable structures. We developed a mesoscopic-length-scale actin filament model to investigate force-induced filament fragmentation. We show that fragmentation in our model occurs at curvatures similar to previous measurements of fragmentation within (cofil)actin and actin-cofilactin boundaries. Boundaries between bare and cofilin-decorated segments are brittle and fragment at small bending and twisting deformations. Extending filaments disperses strain uniformly over subunit interfaces, and filaments fragment with no detectable partial rupture or plastic deformation. In contrast, bending or twisting filaments imposes nonuniform interface strain and leads to partial interface rupture, accelerating filament fragmentation. As a result, the rupture force under compressive loads is an order of magnitude lower than under tensile loads. Partial interface rupture may be a primary mechanism of accelerating actin filament fragmentation by other actin-destabilizing proteins.

Combined molecular/continuum modeling reveals the role of friction during fast unfolding of coiled-coil proteins

Coiled-coils are filamentous proteins that form the basic building block of important force-bearing cellular elements, such as intermediate filaments and myosin motors. In addition to their biological importance, coiled-coil proteins are increasingly used in new biomaterials including fibers, nanotubes, or hydrogels. Coiled-coils undergo a structural transition from an α-helical coil to an unfolded state upon extension, which allows them to sustain large strains and is critical for their biological function. By performing equilibrium and out-of-equilibrium all-atom molecular dynamics (MD) simulations of coiled-coils in explicit solvent, we show that two-state models based on Kramers' or Bell's theories fail to predict the rate of unfolding at high pulling rates. We further show that an atomistically informed continuum rod model accounting for phase transformations and for the hydrodynamic interactions with the solvent can reconcile two-state models with our MD results. Our results show that frictional forces, usually neglected in theories of fibrous protein unfolding, reduce the thermodynamic force acting on the interface, and thus control the dynamics of unfolding at different pulling rates. Our results may help interpret MD simulations at high pulling rates, and could be pertinent to cytoskeletal networks or protein-based artificial materials subjected to shocks or blasts.

Mechanical unfolding of alpha- and beta-helical protein motifs

Alpha-helices and beta-sheets are the two most common secondary structure motifs in proteins. Beta-helical structures merge features of the two motifs, containing two or three beta-sheet faces connected by loops or turns in a single protein. Beta-helical structures form the basis of proteins with diverse mechanical functions such as bacterial adhesins, phage cell-puncture devices, antifreeze proteins, and extracellular matrices. Alpha-helices are commonly found in cellular and extracellular matrix components, whereas beta-helices such as curli fibrils are more common as bacterial and biofilm matrix components. It is currently not known whether it may be advantageous to use one helical motif over the other for different structural and mechanical functions. To better understand the mechanical implications of using different helix motifs in networks, here we use Steered Molecular Dynamics (SMD) simulations to mechanically unfold multiple alpha- and beta-helical proteins at constant velocity at the single molecule scale. We focus on the energy dissipated during unfolding as a means of comparison between proteins and work normalized by protein characteristics (initial and final length, # H-bonds, # residues, etc.). We find that although alpha-helices such as keratin and beta-helices CsgA and CsgB can require similar amounts of work to unfold, the normalized work per hydrogen bond, initial end to end length, and number of residues is greater for beta-helices at the same pulling rate. To explain this, we analyze the orientation of the backbone alpha carbons and backbone hydrogen bonds during unfolding. We find that the larger width and shorter height of beta-helices results in smaller angles between the protein backbone and the pulling direction during unfolding. As subsequent strands are separated from the beta-helix core, the angle between the backbone and the pulling direction diminishes. This marks a transition where beta-sheet hydrogen bonds become loaded predominantly in a collective shearing mode, which requires a larger rupture force. This finding underlines the importance of geometry in optimizing resistance to mechanical unfolding in proteins. The helix radius is identified here as an important parameter that governs how much sacrificial energy dissipation capacity can be stored in protein networks, where beta-helices offer unique properties.

A High Coordination of Cross-Links Is Beneficial for the Strength of Cross-Linked Fibers

The influence of the coordination of (reversible) cross-links on the mechanical properties of aligned fiber bundles is investigated. Two polymeric systems containing cross-links of different coordination (two- and three-fold coordination) but having the same binding energy are investigated. In particular, the response to loading of these systems is compared. Mechanical parameters (strength, stiffness and work-to-fracture) are obtained by computational loading tests. The influence of coordination is studied for simple test systems with pre-defined topologies that maximize strength as well as for more realistic fiber bundles containing nine chains. The results show that a higher coordination of cross-links has a beneficial effect on the strength and the stiffness of the systems, while the work-to-fracture was found larger for the system having a smaller coordination of cross-links. It can be concluded that controlling the coordination of cross-links is a versatile tool to specifically tailor the mechanical properties of polymeric structures.

Fatigue of soft fibrous tissues: Multi-scale mechanics and constitutive modeling

In recent experimental studies a possible damage mechanism of collagenous tissues mainly caused by fatigue was disclosed. In this contribution, a multi-scale constitutive model ranging from the tropocollagen (TC) molecule level up to bundles of collagen fibers is proposed and utilized to predict the elastic and inelastic long-term tissue response. Material failure of collagen fibrils is elucidated by a permanent opening of the triple helical collagen molecule conformation, triggered either by overstretching or reaction kinetics of non-covalent bonds. This kinetics is described within a probabilistic framework of adhesive detachments of molecular linkages providing collagen fiber integrity. Both intramolecular and interfibrillar linkages are considered. The final constitutive equations are validated against recent experimental data available in literature for both uniaxial tension to failure and the evolution of fatigue in subsequent loading cycles. All material parameters of the proposed model have a clear physical interpretation.

STATEMENT OF SIGNIFICANCE

Irreversible changes take place at different length scales of soft fibrous tissues under supra-physiological loading and alter their macroscopic mechanical properties. Understanding the evolution of those histologic pathologies under loading and incorporating them into a continuum mechanical framework appears to be crucial in order to predict long-term evolution of various diseases and to support the development of tissue engineering.

Moisture effect on interfacial integrity of epoxy-bonded system: a hierarchical approach

The epoxy-bonded system has been widely used in various applications across different scale lengths. Prior investigations have indicated that the moisture-affected interfacial debonding is the major failure mode of such a system, but the fundamental mechanism remains unknown, such as the basis for the invasion of water molecules in the cross-linked epoxy and the epoxy-bonded interface. This prevents us from predicting the long-term performance of the epoxy-related applications under the effect of the moisture. Here, we use full atomistic models to investigate the response of the epoxy-bonded system towards the adhesion test, and provide a detailed analysis of the interfacial integrity under the moisture effect and the associated debonding mechanism. Molecular dynamics simulations show that water molecules affect the hierarchical structure of the epoxy-bonded system at the nanoscale by disrupting the film-substrate interaction and the molecular interaction within the epoxy, which leads to the detachment of the epoxy thin film, and the final interfacial debonding. The simulation results show good agreement with the experimental results of the epoxy-bonded system. Through identifying the relationship between the epoxy structure and the debonding mechanism at multiple scales, it is shown that the hierarchical structure of the epoxy-bonded system is crucial for the interfacial integrity. In particular, the available space of the epoxy-bonded system, which consists of various sizes ranging from the atomistic scale to the macroscale and is close to the interface facilitates the moisture accumulation, leading to a distinct interfacial debonding when compared to the dry scenario.

Mechanical Deformation Mechanisms and Properties of Prion Fibrils Probed by Atomistic Simulations

Prion fibrils, which are a hallmark for neurodegenerative diseases, have recently been found to exhibit the structural diversity that governs disease pathology. Despite our recent finding concerning the role of the disease-specific structure of prion fibrils in determining their elastic properties, the mechanical deformation mechanisms and fracture properties of prion fibrils depending on their structures have not been fully characterized. In this work, we have studied the tensile deformation mechanisms of prion and non-prion amyloid fibrils by using steered molecular dynamics simulations. Our simulation results show that the elastic modulus of prion fibril, which is formed based on left-handed β-helical structure, is larger than that of non-prion fibril constructed based on right-handed β-helix. However, the mechanical toughness of prion fibril is found to be less than that of non-prion fibril, which indicates that infectious prion fibril is more fragile than non-infectious (non-prion) fibril. Our study sheds light on the role of the helical structure of amyloid fibrils, which is related to prion infectivity, in determining their mechanical deformation mechanisms and properties.

High Tensile Strength of Engineered β-Solenoid Fibrils via Sonication and Pulling

We present estimates of ultimate tensile strength (UTS) for two engineered β-solenoid protein mutant fibril structures (spruce budworm and Rhagium inquisitor antifreeze proteins) derived from sonication-based measurements and from force pulling molecular dynamics simulations, both in water. Sonication experiments generate limiting scissioned fibrils with a well-defined length-to-width correlation for the mutant spruce budworm protein and the resultant UTS estimate is 0.66 ± 0.08 GPa. For fibrils formed from engineered R. inquisitor antifreeze protein, depending upon geometry, we estimate UTSs of 3.5 ± 3.2-5.5 ± 5.1 GPa for proteins with interfacial disulfide bonds, and 1.6 ± 1.5-2.5 ± 2.3 GPa for the reduced form. The large error bars for the R. inquisitor structures are intrinsic to the broad distribution of limiting scission lengths. Simulations provide pulling velocity-dependent UTSs increasing from 0.2 to 1 GPa in the available speed range, and 1.5 GPa extrapolated to the speeds expected in the sonication experiments. Simulations yield low-velocity values for the Young's modulus of 6.0 GPa. Without protein optimization, these mechanical parameters are similar to those of spider silk and Kevlar, but in contrast to spider silk, these proteins have a precisely known sequence-structure relationship.

Molecular dynamics-based strength estimates of beta solenoid proteins

The use of beta solenoid proteins as functionalizable, nanoscale, self-assembling molecular building blocks may have many applications, including templating the growth of wires or higher-dimensional structures. By understanding their mechanical strengths, we can efficiently design the proteins for specific functions. We present a study of the mechanical properties of seven beta solenoid proteins using GROMACS molecular dynamics software to produce force/torque-displacement data, implement umbrella sampling of bending/twisting trajectories, produce Potentials of Mean Force (PMFs), extract effective spring constants, and calculate rigidities for two bending and two twisting directions for each protein. We examine the differences between computing the strength values from force/torque-displacement data alone and PMF data, and show how higher precision estimates can be obtained from the former. In addition to the analysis of the methods, we report estimates for the bend/twist persistence lengths for each protein, which range from 0.5-3.4 μm. We note that beta solenoid proteins with internal disulfide bridges do not enjoy enhanced bending or twisting strength, and that the strongest correlate with bend/twist rigidity is the number of hydrogen bonds per turn. In addition, we compute estimates of the Young's modulus (Y) for each protein, which range from Y = 3.5 to 7.2 GPa.

Effect of Terminal Modification on the Molecular Assembly and Mechanical Properties of Protein-Based Block Copolymers

Accurate prediction and validation of the assembly of bioinspired peptide sequences into fibers with defined mechanical characteristics would aid significantly in designing and creating materials with desired properties. This process may also be utilized to provide insight into how the molecular architecture of many natural protein fibers is assembled. In this work, computational modeling and experimentation are used in tandem to determine how peptide terminal modification affects a fiber-forming core domain. Modeling shows that increased terminal molecular weight and hydrophilicity improve peptide chain alignment under shearing conditions and promote consolidation of semicrystalline domains. Mechanical analysis shows acute improvements to strength and elasticity, but significantly reduced extensibility and overall toughness. These results highlight an important entropic function that terminal domains of fiber-forming peptides exhibit as chain alignment promoters, which ultimately has notable consequences on the mechanical behavior of the final fiber products.

Mutable polyelectrolyte tube arrays: mesoscale modeling and lateral force microscopy

In this study, the pH-dependent friction of layer-by-layer assemblies of poly(allylamine hydrochloride) and poly(acrylic acid) (PAH/PAA) are quantified for microtube array structures via experimental and simulated lateral force microscopy (LFM). A novel coarse-grain tube model is developed, utilizing a molecular dynamics (MD) framework with a Hertzian soft contact potential (such that F ∼ δ^3/2) to allow the efficient dynamic simulation of 3D arrays consisting of hundreds of tubes at micrometer length scales. By quantitatively comparing experimental LFM and computational results, the coupling between geometry (tube spacing and swelling) and material properties (intrinsic stiffness) results in a transition from bending dominated deformation to bending combined with inter-tube contact, independent of material adhesion assumptions. Variation of tube spacing (and thus control of contact) can be used to exploit the normal and lateral resistance of the tube arrays as a function of pH (2.0/5.5), beyond the effect of areal tube density, with increased resistances (potential mutability) up to a factor of ∼60. This study provides a novel modeling platform to assess and design dynamic polyelectrolyte-based substrates/coatings with tailorable stimulus-responsive surface friction. Our results show that micro-geometry can be used alongside stimulus-responsive material changes to amplify and systematically tune mutability.

Multiscale mechanics of the lateral pressure effect on enhancing the load transfer between polymer coated CNTs

While individual carbon nanotubes (CNTs) are known as one of the strongest fibers ever known, even the strongest fabricated macroscale CNT yarns and fibers are still significantly weaker than individual nanotubes. The loss in mechanical properties is mainly because the deformation mechanism of CNT fibers is highly governed by the weak shear strength corresponding to sliding of nanotubes on each other. Adding polymer coating to the bundles, and twisting the CNT yarns to enhance the intertube interactions are both efficient methods to improve the mechanical properties of macroscale yarns. Here, we perform molecular dynamics (MD) simulations to unravel the unknown deformation mechanism in the intertube polymer chains and also local deformations of the CNTs at the atomistic scale. Our results show that the lateral pressure can have both beneficial and adverse effects on shear strength of polymer coated CNTs, depending on the local deformations at the atomistic scale. In this paper we also introduce a bottom-up bridging strategy between a full atomistic model and a coarse-grained (CG) model. Our trained CG model is capable of incorporating the atomistic scale local deformations of each CNT to the larger scale collect behavior of bundles, which enables the model to accurately predict the effect of lateral pressure on larger CNT bundles and yarns. The developed multiscale CG model is implemented to study the effect of lateral pressure on the shear strength of straight polymer coated CNT yarns, and also the effect of twisting on the pull-out force of bundles in spun CNT yarns.

Modeling and Experiment Reveal Structure and Nanomechanics across the Inverse Temperature Transition in B. mori Silk-Elastin-like Protein Polymers

Silk and elastin are exemplary protein materials that exhibit exceptional material properties. Silk is uniquely strong, surpassing engineering materials such as Kevlar and steel, while elastin has exquisite flexibility and can reversibly fold into a more structured form at high temperatures when many other proteins would unfold and denature. This phenomenon in elastin is termed the inverse temperature transition. It is a reversible, controllable process that motivates applications in drug delivery, shape change materials, and biomimetic devices. Silk-elastinlike protein polymers (SELPs), which combine repeating B. mori silk and elastin blocks, have been introduced as biologically inspired materials that combine the distinctive properties of the component parts to achieve strong and extensible, tunable biomaterials. Here, we considered a single SELP sequence to examine temperature transition effects at the molecular scale. SELP molecular models were created using Replica Exchange Molecular Dynamics, an accelerated sampling method, and confirmed in experiment by comparing secondary structure distributions. A molecular collapse of the SELP molecule was observed with increased temperature in both molecular simulation and experiment. Temperature-specific differences were observed in the mechanical properties and the unfolding pathways of the polypeptide. Using the Bell-Evans model, we analyzed the free energy landscape associated with molecular unfolding at temperatures below and above the transition temperature range (T_t) of the polypeptide. We found that at physiological pulling rates, the energy barrier to unfold SELPs was counterintuitively higher above T_t. Our findings offer a foundational perspective on the molecular scale mechanisms of temperature-induced phase transition in SELPs, and suggest a novel approach to combine simulation and experiment to study materials for multifunctional biomimetic applications.

Molecular level detection and localization of mechanical damage in collagen enabled by collagen hybridizing peptides

Mechanical injury to connective tissue causes changes in collagen structure and material behaviour, but the role and mechanisms of molecular damage have not been established. In the case of mechanical subfailure damage, no apparent macroscale damage can be detected, yet this damage initiates and potentiates in pathological processes. Here, we utilize collagen hybridizing peptide (CHP), which binds unfolded collagen by triple helix formation, to detect molecular level subfailure damage to collagen in mechanically stretched rat tail tendon fascicle. Our results directly reveal that collagen triple helix unfolding occurs during tensile loading of collagenous tissues and thus is an important damage mechanism. Steered molecular dynamics simulations suggest that a likely mechanism for triple helix unfolding is intermolecular shearing of collagen α-chains. Our results elucidate a probable molecular failure mechanism associated with subfailure injuries, and demonstrate the potential of CHP targeting for diagnosis, treatment and monitoring of tissue disease and injury.

Collagen denaturation is thought to occur during tissue mechanical damage, but its role in damage initiation is still unclear. Here, the authors use a collagen hybridizing peptide to provide insights into the molecular mechanisms leading to collagen unfolding during tendon mechanical stretch.

Fabrication of nanofibrous electrospun scaffolds from a heterogeneous library of co- and self-assembling peptides

Self-assembling (SAPs) and co-assembling peptides (CAPs) are driving increasing enthusiasm as synthetic but biologically inspired biomaterials amenable of easy functionalization for regenerative medicine. On the other hand, electrospinning (ES) is a versatile technique useful for tailoring the nanostructures of various biomaterials into scaffolds resembling the extracellular matrices found in organs and tissues. The synergistic merging of these two approaches is a long-awaited advance in nanomedicine that has not been deeply documented so far. In the present work, we describe the successful ES of a library of diverse SAPs and CAPs into biomimetic nanofibrous mats. Our results suggest that suitable ES solutions are characterized by high concentrations of peptides, providing backbone physical chain entanglements, and by random coil/α-helical conformations while β-sheet aggregation may be detrimental to spinnability. The resulting peptide fibers feature interconnected seamless mats with nanofibers average diameters ranging from ∼100nm to ∼400nm. Also, peptide chemical nature and ES set up parameters play pivotal roles in determining the conformational transitions and morphological properties of the produced nanofibers. Far from being an exhaustive description of the just-opened novel field of ES-assembled peptides, this seminal work aims at shining a light on a still missing general theory for the production of electrospun peptidic biomaterials bringing together the spatial, biochemical and biomimetic of these two techniques into unique scaffolds for tissue engineering.

STATEMENT OF SIGNIFICANCE

Construction of peptide hydrogels has received considerable attention due to their potential as nanostructures amenable of easy functionalization and capable of creating microenvironments suited for culturing cells and triggering tissue regeneration. They display a superior biocompatibility unmatched by other known synthetic biomaterials so far. However, their applications are confined to body fillers because most of them do spontaneously form hydrogels, while effective tissue regeneration often requires well-defined fibrous scaffolds. In this work, we developed electrospun fibers of various peptides (cross-beta self-assembling, hierarchically assembling, functionalized, co-assembling) and we provided a deep understanding of the crucial phenomena to be taken into account when peptides fibers fabrication. These results open new venues for exploring novel regenerative applications of peptide nanofibrous scaffolds.

Nanomechanical properties of MscL α helices: A steered molecular dynamics study

Gating of mechanosensitive (MS) channels is driven by a hierarchical cascade of movements and deformations of transmembrane helices in response to bilayer tension. Determining the intrinsic mechanical properties of the individual transmembrane helices is therefore central to understanding the intricacies of the gating mechanism of MS channels. We used a constant-force steered molecular dynamics (SMD) approach to perform unidirectional pulling tests on all the helices of MscL in M. tuberculosis and E. coli homologs. Using this method, we could overcome the issues encountered with the commonly used constant-velocity SMD simulations, such as low mechanical stability of the helix during stretching and high dependency of the elastic properties on the pulling rate. We estimated Young's moduli of the α-helices of MscL to vary between 0.2 and 12.5 GPa with TM2 helix being the stiffest. We also studied the effect of water on the properties of the pore-lining TM1 helix. In the absence of water, this helix exhibited a much stiffer response. By monitoring the number of hydrogen bonds, it appears that water acts like a 'lubricant' (softener) during TM1 helix elongation. These data shed light on another physical aspect underlying hydrophobic gating of MS channels, in particular MscL.

Mechanical Effects of Dynamic Binding between Tau Proteins on Microtubules during Axonal Injury

The viscoelastic nature of axons plays a key role in their selective vulnerability to damage in traumatic brain injury (TBI). Experimental studies have shown that although axons can tolerate 100% strain under slow loading rates, even strain as small as 5% can rupture microtubules (MTs) during the fast loading velocities relevant to TBI. Here, we developed a computational model to examine rate-dependent behavior related to dynamic interactions between MTs and the MT-associated protein tau under varying strains and strain rates. In the model, inverted pairs of tau proteins can dynamically cross-link parallel MTs via the respective MT-binding domain of each tau. The model also incorporates realistic thermodynamic breaking and reformation of the bonds between the connected tau proteins as they respond to mechanical stretch. With simulated stretch of the axon, the model shows that despite the highly dynamic nature of binding and unbinding events, under fast loading rates relevant to TBI, large tensile forces can be transmitted to the MTs that can lead to mechanical rupture of the MT cylinder, in agreement with experimental observations and as inferred in human TBI. In contrast, at slow loading rates, the progressive breaking and reformation of the bonds between the tau proteins facilitate the extension of axons up to ∼100% strain without any microstructural damage. The model also predicts that under fast loading rates, individual MTs detach from MT bundles via sequential breaking of the tau-tau bonds. Finally, the model demonstrates that longer MTs are more susceptible to mechanical rupture, whereas short MTs are more prone to detachment from the MT bundle, leading to disintegration of the axonal MT ultrastructure. Notably, the predictions from the model are in excellent agreement with the findings of the recent in vitro mechanical testing of micropatterned neuronal cultures.

The Gearbox of the Bacterial Flagellar Motor Switch

Switching of flagellar motor rotation sense dictates bacterial chemotaxis. Multi-subunit FliM-FliG rotor rings couple signal protein binding in FliM with reversal of a distant FliG C-terminal (FliG_C) helix involved in stator contacts. Subunit dynamics were examined in conformer ensembles generated by molecular simulations from the X-ray structures. Principal component analysis extracted collective motions. Interfacial loop immobilization by complex formation coupled elastic fluctuations of the FliM middle (FliM_M) and FliG middle (FliG_M) domains. Coevolved mutations captured interfacial dynamics as well as contacts. FliG_M rotation was amplified via two central hinges to the FliG_C helix. Intrinsic flexibility, reported by the FliG_MC ensembles, reconciled conformers with opposite FliG_C helix orientations. FliG domain stacking deformed the inter-domain linker and reduced flexibility; but conformational changes were not triggered by engineered linker deletions that cause a rotation-locked phenotype. These facts suggest that binary rotation states arise from conformational selection by stacking interactions.

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Switch complex exploits differential subunit stiffness for mechanical amplification

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Distinct rotor protein X-ray structures generate overlapping conformer ensembles

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Stacking constraints on a flexible helix linker could select diverse rotation states

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Non-contact elastic couplings at the subunit interface in the complex have coevolved

Animal Hairs as Water-stimulated Shape Memory Materials: Mechanism and Structural Networks in Molecular Assemblies

Animal hairs consisting of α-keratin biopolymers existing broadly in nature may be responsive to water for recovery to the innate shape from their fixed deformation, thus possess smart behavior, namely shape memory effect (SME). In this article, three typical animal hair fibers were first time investigated for their water-stimulated SME, and therefrom to identify the corresponding net-points and switches in their molecular and morphological structures. Experimentally, the SME manifested a good stability of high shape fixation ratio and reasonable recovery rate after many cycles of deformation programming under water stimulation. The effects of hydration on hair lateral size, recovery kinetics, dynamic mechanical behaviors and structural components (crystal, disulfide and hydrogen bonds) were then systematically studied. SME mechanisms were explored based on the variations of structural components in molecular assemblies of such smart fibers. A hybrid structural network model with single-switch and twin-net-points was thereafter proposed to interpret the water-stimulated shape memory mechanism of animal hairs. This original work is expected to provide inspiration for exploring other natural materials to reveal their smart functions and natural laws in animals including human as well as making more remarkable synthetic smart materials.

How soft is a single protein? The stress-strain curve of antibody pentamers with 5 pN and 50 pm resolutions

Understanding the mechanical functionalities of complex biological systems requires the measurement of the mechanical compliance of their smallest components. Here, we develop a force microscopy method to quantify the softness of a single antibody pentamer by measuring the stress-strain curve with force and deformation resolutions, respectively, of 5 pN and 50 pm. The curve shows three distinctive regions. For ultrasmall compressive forces (5-75 pN), the protein's central region shows that the strain and stress are proportional (elastic regime). This region has an average Young's modulus of 2.5 MPa. For forces between 80 and 220 pN, the stress is roughly proportional to the strain with a Young's modulus of 9 MPa. Higher forces lead to irreversible deformations (plastic regime). Full elastic recovery could reach deformations amounting to 40% of the protein height. The existence of two different elastic regions is explained in terms of the structure of the antibody central region. The stress-strain curve explains the capability of the antibody to sustain multiple collisions without any loss of biological functionality.

Mechanical Reinforcement of Proteins with Polymer Conjugation

Conjugating poly(ethylene glycol) (PEG) to peptides, also known as PEGylation, is proven to increase the thermodynamical stability of peptides, and has been successfully applied to prolong the lifetime of peptide-based vaccines and therapeutic agents. While it is known that protein structure and function can be altered by mechanical stress, whether PEGylation can reinforce proteins against mechanical unfolding remains to be ascertained. Here, we illustrate that PEGylation prolongs the lifetime of α-helices subject to constant stress. PEGylation is found to increase the unfolding time through two mechanisms. We see that (1) the unfolding rate of a helical segment is decreased through prolonged plateau regimes where the peptide helical content remains constant, and (2) the proportion of refolding to unfolding is increased, primarily by shielding water molecules from replacing forcibly exposed backbone hydrogen bonds near the conjugation site. Our findings demonstrate the feasibility of improving peptide mechanical stability with polymer conjugation. This provides a basis for future studies on optimizing conjugation location and chemistry to build custom biomolecules with unforeseen mechanical functions and stability.