Electronics of peptide- and protein-based biomaterials

Tyrosine-specific bioconjugation allowing hole hopping along aromatic chains of glucose oxidase

The potential of bioconjugated glucose oxidase enzymes for bioelectronic applications has been revealed in this research. By selectively modifying the enzyme with redox-active groups, we aimed to enhance the electrochemical properties of the enzyme while maintaining its biocatalytic activity. The phenothiazin-5-oxide and phenoxazine groups were selectively bioconjugated to the tyrosine residues on the enzyme surface. This bioconjugation was confirmed by mass spectrometry after enzymatic digestion of the protein. The self-assembly monolayer of modified enzyme exhibited improved bioelectrochemical behaviour, with enhanced anodic currents compared to the native enzyme. Marcus theory-based theoretical calculations revealed that hole hopping through the internal residues and from the electrode to the bioconjugated residues of the enzyme is thermodynamically favourable. The rate-limiting step for the bioelectrocatalytic process was identified as hole injection from the electrode to the bioconjugated enzyme surface. These findings demonstrate the potential of bioconjugated glucose oxidase for single molecule-based biosensing and bioelectronics.

Neural network conditioned to produce thermophilic protein sequences can increase thermal stability

This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 million protein homologous pairs from organisms adapted to different temperatures, demonstrates promising capability in targeting thermal stability. A designed variant of the Drosophila melanogaster Engrailed Homeodomain shows a melting temperature increase of 15.5 K. Furthermore, NOMELT achieves zero-shot predictive capabilities in ranking experimental melting and half-activation temperatures across a number of protein families. It achieves this without requiring extensive homology data or massive training datasets as do existing zero-shot predictors by specifically learning thermophilicity, as opposed to all natural variation. These findings underscore the potential of leveraging organismal growth temperatures in context-dependent design of proteins for enhanced thermal stability.

Peptide-Perovskite Based Bio-Inspired Materials for Optoelectronics Applications

The growing demand for environmentally friendly semiconductors that can be tailored and developed easily is compelling researchers and technologists to design inherently bio-compatible, self-assembling nanostructures with tunable semiconducting characteristics. Peptide-based bioinspired materials exhibit a variety of supramolecular morphologies and have the potential to function as organic semiconductors. Such biologically or naturally derived peptides with intrinsic semiconducting characteristics create new opportunities for sustainable biomolecule-based optoelectronics devices. Affably, halide perovskite nanocrystals are emerging as potentially attractive nano-electronic analogs, in this vein creating synergies and probing peptide-perovskite-based bio-electronics are of paramount interest. The physical properties and inherent aromatic short-peptide assemblies that can stabilize, and passivate the defects at surfaces assist in improving the charge transport in halide perovskite devices. This review sheds light on how these peptide-perovskite nano-assemblies can be developed for optical sensing, optoelectronics, and imaging for biomedical and healthcare applications. The charge transfer mechanism in peptides along with as an outlook the electron transfer mechanism between perovskite and short peptide chains, which is paramount to facilitate their entry into molecular electronics is discussed. Future aspects, prevailing challenges, and research directions in the field of perovskite-peptides are also presented.

Piezoelectric biomaterials for providing electrical stimulation in bone tissue engineering: Barium titanate

With the increasing clinical demand for orthopedic implants, bone tissue engineering based on a variety of bioactive materials has shown promising applications in bone repair. And various physiological cues, such as mechanical, electrical, and magnetic stimulation, can influence cell fate and participate in bone regeneration. Natural bone has a piezoelectric effect due to the non-centrosymmetric nature of collagen, which can aid in cell adhesion, proliferation and differentiation, and bone growth by converting mechanical stimuli into electrical stimuli. Piezoelectric materials have the same piezoelectric effect as human bone, and they are able to deform in response to physiological movement, thus providing electrical stimulation to cells or damaged tissue without the need for an external power source. Among them, Barium titanate (BaTiO3) is widely used in tumor therapy, tissue engineering, health detection and drug delivery because of its good biocompatibility, low cytotoxicity and good piezoelectric properties. This review describes the piezoelectric effect of natural bone and the characteristics of various types of piezoelectric materials, from the synthesis and physicochemical characteristics of BaTiO3 and its application in biomedicine. And it highlights the great potential of BaTiO3 as piezoelectric biomaterials in the field of bone tissue engineering in anticipation of providing new ideas and opportunities for researchers. The translational potential of this article: This review systematically discusses barium titanate, a bioactive material that can mimic the piezoelectric effect of natural bone tissue, which can intervene in the regenerative repair of bone by providing a sustained electrical microenvironment for bone repair scaffolds. This may help to solve the current problem of poor osteogenic properties of bioactive materials by utilizing barium titanate.

Evaluation of the electrochemical response of aromatic peptides for biodetection of dopamine

Biologically inspired aromatic peptide-based materials are gaining increasing interest as novel charge transport materials for bioelectronics due to their remarkable electrical response and inherent biocompatibility. In this work, the electrochemical response of ten aromatic amino acids and eleven aromatic peptides has been evaluated to assess the potential of incorporating peptides into electrochemical sensors not as biorecognition elements but as biocompatible electronic materials. While the electrochemical response of amino acids is null in all cases, the hexapeptide of phenylalanine (Phe) capped with eight polyethylene glycol units at the N-terminus and, especially, the cyclic dipeptide formed by two dehydro-phenylalanine residues (cyclo(ΔPhe2)), which organize in fibrillary self-assembled structures of nano- and submicrometric size, respectively, are the most electroactive peptides. Electrodes to electrochemically detect the oxidation of dopamine have been prepared using a plasma-activated polyethylene terephthalate glycol substrate covered with a poly(3,4-ethylenedioxythiophene) layer and a peptide coating deposited at the surface. The highest analytical sensitivity and the lowest limits of detection and quantifications have been obtained for the electrode coated with cyclo(ΔPhe2), which shows much better results than that without peptide. These results, on the one hand, confirm the significant role of electron transport through π-stacking interactions in the electrochemical response of peptides and, on the other hand, demonstrate that peptides can be directly used as electronic materials rather than as simple recognition elements in electrochemical biosensors.

Leveraging supramolecular systems in biomedical breakthroughs

Supramolecular systems, intricate assemblies of molecular subunits organized through various intermolecular interactions, offer versatile platforms for diverse applications, including gene therapy, antimicrobial therapy, and cellular engineering. These systems are cost-effective and environmentally friendly, contributing to their attractiveness in biomaterial design. Furthermore, supramolecular biomaterials based on acyclic, macrocyclic compounds and lipid-based assembly offer potential applications in distinct types of biomedical approaches. In this context, they can transport several therapeutic agents very effectively to the target site. Supramolecular hydrogels exhibit potent antimicrobial activity by disrupting microbial membranes, offering promising solutions to combat drug-resistant pathogens. Additionally, supramolecular luminescent nanoparticles enable targeted cell imaging, facilitating disease diagnosis and treatment with high specificity and sensitivity. In cellular engineering, supramolecular assemblies of small molecules demonstrate biological activities, overcoming challenges in cancer treatment by inhibiting signaling pathways and inducing apoptosis in cancer cells. This review emphasizes the applications of supramolecular systems from gene therapy to cellular imaging, tissue engineering, and antimicrobial therapy, showcasing their potential to drive innovation and address pressing healthcare challenges.

Learning peptide properties with positive examples only

Deep learning can create accurate predictive models by exploiting existing large-scale experimental data, and guide the design of molecules. However, a major barrier is the requirement of both positive and negative examples in the classical supervised learning frameworks. Notably, most peptide databases come with missing information and low number of observations on negative examples, as such sequences are hard to obtain using high-throughput screening methods. To address this challenge, we solely exploit the limited known positive examples in a semi-supervised setting, and discover peptide sequences that are likely to map to certain antimicrobial properties via positive-unlabeled learning (PU). In particular, we use the two learning strategies of adapting base classifier and reliable negative identification to build deep learning models for inferring solubility, hemolysis, binding against SHP-2, and non-fouling activity of peptides, given their sequence. We evaluate the predictive performance of our PU learning method and show that by only using the positive data, it can achieve competitive performance when compared with the classical positive-negative (PN) classification approach, where there is access to both positive and negative examples.

Peptide-based self-assembled monolayers (SAMs): what peptides can do for SAMs and vice versa

Self-assembled monolayers (SAMs) represent highly ordered molecular materials with versatile biochemical features and multidisciplinary applications. Research on SAMs has made much progress since the early begginings of Au substrates and alkanethiols, and numerous examples of peptide-displaying SAMs can be found in the literature. Peptides, presenting increasing structural complexity, stimuli-responsiveness, and biological relevance, represent versatile functional components in SAMs-based platforms. This review examines the major findings and progress made on the use of peptide building blocks displayed as part of SAMs with specific functions, such as selective cell adhesion, migration and differentiation, biomolecular binding, advanced biosensing, molecular electronics, antimicrobial, osteointegrative and antifouling surfaces, among others. Peptide selection and design, functionalisation strategies, as well as structural and functional characteristics from selected examples are discussed. Additionally, advanced fabrication methods for dynamic peptide spatiotemporal presentation are presented, as well as a number of characterisation techniques. All together, these features and approaches enable the preparation and use of increasingly complex peptide-based SAMs to mimic and study biological processes, and provide convergent platforms for high throughput screening discovery and validation of promising therapeutics and technologies.

PVDF-Based Piezo-Catalytic Membranes-A Net-Zero Emission Approach towards Textile Wastewater Purification

Among the various water purification techniques, advancements in membrane technology, with better fabrication and analysis, are receiving the most research attention. The piezo-catalytic degradation of water pollutants is an emerging area of research in water purification technology. This review article focuses on piezoelectric polyvinylidene difluoride (PVDF) polymer-based membranes and their nanocomposites for textile wastewater remediation. At the beginning of this article, the classification of piezoelectric materials is discussed. Among the various membrane-forming polymers, PVDF is a piezoelectric polymer discussed in detail due to its exceptional piezoelectric properties. Polyvinylidene difluoride can show excellent piezoelectric properties in the beta phase. Therefore, various methods of β-phase enhancement within the PVDF polymer and various factors that have a critical impact on its piezo-catalytic activity are briefly explained. This review article also highlights the major aspects of piezoelectric membranes in the context of dye degradation and a net-zero approach. The β-phase of the PVDF piezoelectric material generates an electron-hole pair through external vibrations. The possibility of piezo-catalytic dye degradation via mechanical vibrations and the subsequent capture of the resulting CO2 and H2 gases open up the possibility of achieving the net-zero goal.

Neutron reflection and scattering in characterising peptide assemblies

Self-assemblies of de novo designed short peptides at interface and in bulk solution provide potential platforms for developing applications in many medical and technological areas. However, characterising how bioinspired supramolecular nanostructures evolve with dynamic self-assembling processes and respond to different stimuli remains challenging. Neutron scattering technologies including small angle neutron scattering (SANS) and neutron reflection (NR) can be advantageous and complementary to other state-of-the-art techniques in tracing structural changes under different conditions. With more neutron sources now available, SANS and NR are becoming increasingly popular in studying self-assembling processes of diverse peptide and protein systems, but the difficulty in experimental manipulation and data analysis can deter beginners. This review will introduce the basic theory, general experimental setup and data analysis of SANS and NR, followed by provision of their applications in characterising interfacial and solution self-assemblies of representative peptides and proteins. SANS and NR are remarkably effective in determining the morphological features self-assembled short peptides, especially size and shape transitions as a result of either sequence changes or in response to environmental stimuli, demonstrating the unique capability of NR and SANS in unravelling the interactive processes. These examples highlight the potential of NR and SANS in supporting the development of novel short peptides and proteins as biopharmaceutical candidates in the fight against many diseases and infections that share common features of membrane interactive processes.

Electrochemistry in sensing of molecular interactions of proteins and their behavior in an electric field

Electrochemical methods can be used not only for the sensitive analysis of proteins but also for deeper research into their structure, transport functions (transfer of electrons and protons), and sensing their interactions with soft and solid surfaces. Last but not least, electrochemical tools are useful for investigating the effect of an electric field on protein structure, the direct application of electrochemical methods for controlling protein function, or the micromanipulation of supramolecular protein structures. There are many experimental arrangements (modalities), from the classic configuration that works with an electrochemical cell to miniaturized electrochemical sensors and microchip platforms. The support of computational chemistry methods which appropriately complement the interpretation framework of experimental results is also important. This text describes recent directions in electrochemical methods for the determination of proteins and briefly summarizes available methodologies for the selective labeling of proteins using redox-active probes. Attention is also paid to the theoretical aspects of electron transport and the effect of an external electric field on the structure of selected proteins. Instead of providing a comprehensive overview, we aim to highlight areas of interest that have not been summarized recently, but, at the same time, represent current trends in the field.

Advantages and Prospective Implications of Smart Materials in Tissue Engineering: Piezoelectric, Shape Memory, and Hydrogels

Conventional biomaterial is frequently used in the biomedical sector for various therapies, imaging, treatment, and theranostic functions. However, their properties are fixed to meet certain applications. Smart materials respond in a controllable and reversible way, modifying some of their properties because of external stimuli. However, protein-based smart materials allow modular protein domains with different functionalities and responsive behaviours to be easily combined. Wherein, these "smart" behaviours can be tuned by amino acid identity and sequence. This review aims to give an insight into the design of smart materials, mainly protein-based piezoelectric materials, shape-memory materials, and hydrogels, as well as highlight the current progress and challenges of protein-based smart materials in tissue engineering. These materials have demonstrated outstanding regeneration of neural, skin, cartilage, bone, and cardiac tissues with great stimuli-responsive properties, biocompatibility, biodegradability, and biofunctionality.

Learning Peptide Properties with Positive Examples Only

Deep learning can create accurate predictive models by exploiting existing large-scale experimental data, and guide the design of molecules. However, a major barrier is the requirement of both positive and negative examples in the classical supervised learning frameworks. Notably, most peptide databases come with missing information and low number of observations on negative examples, as such sequences are hard to obtain using high-throughput screening methods. To address this challenge, we solely exploit the limited known positive examples in a semi-supervised setting, and discover peptide sequences that are likely to map to certain antimicrobial properties via positive-unlabeled learning (PU). In particular, we use the two learning strategies of adapting base classifier and reliable negative identification to build deep learning models for inferring solubility, hemolysis, binding against SHP-2, and non-fouling activity of peptides, given their sequence. We evaluate the predictive performance of our PU learning method and show that by only using the positive data, it can achieve competitive performance when compared with the classical positive-negative (PN) classification approach, where there is access to both positive and negative examples.

Peptide-Based Materials That Exploit Metal Coordination

Metal-ion coordination has been widely exploited to control the supramolecular behavior of a variety of building blocks into functional materials. In particular, peptides offer great chemical diversity for metal-binding modes, combined with inherent biocompatibility and biodegradability that make them attractive especially for medicine, sensing, and environmental remediation. The focus of this review is the last 5 years' progress in this exciting field to conclude with an overview of the future directions that this research area is currently undertaking.

Conductive Materials with Elaborate Micro/Nanostructures for Bioelectronics

Bioelectronics, an emerging field with the mutual penetration of biological systems and electronic sciences, allows the quantitative analysis of complicated biosignals together with the dynamic regulation of fateful biological functions. In this area, the development of conductive materials with elaborate micro/nanostructures has been of great significance to the improvement of high-performance bioelectronic devices. Thus, here, a comprehensive and up-to-date summary of relevant research studies on the fabrication and properties of conductive materials with micro/nanostructures and their promising applications and future opportunities in bioelectronic applications is presented. In addition, a critical analysis of the current opportunities and challenges regarding the future developments of conductive materials with elaborate micro/nanostructures for bioelectronic applications is also presented.

Protein by-products: Composition, extraction, and biomedical applications

Significant upsurge in animal by-products such as skin, bones, wool, hides, feathers, and fats has become a global challenge and, if not properly disposed of, can spread contamination and viral diseases. Animal by-products are rich in proteins, which can be used as nutritional, pharmacologically functional ingredients, and biomedical materials. Therefore, recycling these abundant and renewable by-products and extracting high value-added components from them is a sustainable approach to reclaim animal by-products while addressing scarce landfill resources. This article appraises the most recent studies conducted in the last five years on animal-derived proteins' separation and biomedical application. The effort encompasses an introduction about the composition, an overview of the extraction and purification methods, and the broad range of biomedical applications of these ensuing proteins.

Remarkable enantioselectivity enhancement of the extractors with nonaxial chirality in liquid-liquid extraction of underivatized amino acids by introducing t-butyl group

A class of carbonyl extractors, (R)-3, (R)-4, and (R)-5, with nonaxial chirality containing asymmetric carbons has been synthesized and studied for their efficiencies in enantioselective liquid-liquid extraction for underivatized amino acids. The bulky t-butyl ketone extractors, (R)-4 and (R)-5, showed the stereoselectivities ranging 5.4-9.4 of l/d ratio much better than those of the aldehyde extractor, (R)-3, ranging 2.4-5.2. The imine formation rates and yields of the t-butyl ketones were not significantly affected by their bulkiness and even in the absence of resonance-assisted hydrogen bond. This work confirms that a bulky t-butyl ketone can be a good choice in the development of an extractor not only with axial chirality but also with nonaxial chirality for the enantioselective extraction of unprotected amino acids.

Unravelling the antimicrobial activity of peptide hydrogel systems: current and future perspectives

The use of hydrogels has garnered significant interest as biomaterial and drug delivery platforms for anti-infective applications. For decades antimicrobial peptides have been heralded as a much needed new class of antimicrobial drugs. Self-assembling peptide hydrogels with inherent antimicrobial ability have recently come to the fore. However, their fundamental antimicrobial properties, selectivity and mechanism of action are relatively undefined. This review attempts to establish a link between antimicrobial efficacy; the self-assembly process; peptide-membrane interactions and mechanical properties by studying several reported peptide systems: β-hairpin/β-loop peptides; multidomain peptides; amphiphilic surfactant-like peptides and ultrashort/low molecular weight peptides. We also explore their role in the formation of amyloid plaques and the potential for an infection etiology in diseases such as Alzheimer's. We look briefly at innovative methods of gel characterization. These may provide useful tools for future studies within this increasingly important field.

Self-Assembling Peptides and Carbon Nanomaterials Join Forces for Innovative Biomedical Applications

Self-assembling peptides and carbon nanomaterials have attracted great interest for their respective potential to bring innovation in the biomedical field. Combination of these two types of building blocks is not trivial in light of their very different physico-chemical properties, yet great progress has been made over the years at the interface between these two research areas. This concise review will analyze the latest developments at the forefront of research that combines self-assembling peptides with carbon nanostructures for biological use. Applications span from tissue regeneration, to biosensing and imaging, and bioelectronics.

Thermo-Viscoelastic Response of Protein-Based Hydrogels

Because of the bioactivity and biocompatibility of protein-based gels and the reversible nature of bonds between associating coiled coils, these materials demonstrate a wide spectrum of potential applications in targeted drug delivery, tissue engineering, and regenerative medicine. The kinetics of rearrangement (association and dissociation) of the physical bonds between chains has been traditionally studied in shear relaxation tests and small-amplitude oscillatory tests. A characteristic feature of recombinant protein gels is that chains in the polymer network are connected by temporary bonds between the coiled coil complexes and permanent cross-links between functional groups of amino acids. A simple model is developed for the linear viscoelastic behavior of protein-based gels. Its advantage is that, on the one hand, the model only involves five material parameters with transparent physical meaning and, on the other, it correctly reproduces experimental data in shear relaxation and oscillatory tests. The model is applied to study the effects of temperature, the concentration of proteins, and their structure on the viscoelastic response of hydrogels.