Discovering design principles of collagen molecular stability using a genetic algorithm, deep learning, and experimental validation.

Collagen is the most abundant structural protein in humans, providing crucial mechanical properties, including high strength and toughness, in tissues. Collagen-based biomaterials are, therefore, used for tissue repair and regeneration. Utilizing collagen effectively during materials processing ex vivo and subsequent function in vivo requires stability over wide temperature ranges to avoid denaturation and loss of structure, measured as melting temperature (Tm). Although significant research has been conducted on understanding how collagen primary amino acid sequences correspond to Tm values, a robust framework to facilitate the design of collagen sequences with specific Tm remains a challenge. Here, we develop a general model using a genetic algorithm within a deep learning framework to design collagen sequences with specific Tm values. We report 1,000 de novo collagen sequences, and we show that we can efficiently use this model to generate collagen sequences and verify their Tm values using both experimental and computational methods. We find that the model accurately predicts Tm values within a few degrees centigrade. Further, using this model, we conduct a high-throughput study to identify the most frequently occurring collagen triplets that can be directly incorporated into collagen. We further discovered that the number of hydrogen bonds within collagen calculated with molecular dynamics (MD) is directly correlated to the experimental measurement of triple-helical quality. Ultimately, we see this work as a critical step to helping researchers develop collagen sequences with specific Tm values for intended materials manufacturing methods and biomedical applications, realizing a mechanistic materials by design paradigm.

Charge-Modulated Accessibility of Tyrosine Residues for Silk-Elastin Copolymer Cross-Linking.

The modulation of reaction kinetics with horseradish peroxidase (HRP)-catalyzed cross-linking of proteins remains a useful strategy to modulate hydrogel formation. Here, we demonstrate that the presence of positively charged lysines in silk-elastin-like polymers impacts the thermal transition temperature of these proteins, while the location in the primary sequence modulates the reactivity of the tyrosines. The positively charged lysine side chains decreased π-π interactions among the tyrosines and reduced the rate of formation and number of HRP-mediated dityrosine bonds, dependent on the proximity of the charged group to the tyrosine. The results suggest that the location of repulsive charges can be used to tailor the reaction kinetics for enzymatic cross-linking, providing further control of gelation rates for in situ gel formation and the resulting protein-based gel characteristics.

3D Printing of Monolithic Proteinaceous Cantilevers Using Regenerated Silk Fibroin.

Silk fibroin, regenerated from Bombyx mori, has shown considerable promise as a printable, aqueous-based ink using a bioinspired salt-bath system in our previous work. Here, we further developed and characterized silk fibroin inks that exhibit concentration-dependent fluorescence spectra at the molecular level. These insights supported extrusion-based 3D printing using concentrated silk fibroin solutions as printing inks. 3D monolithic proteinaceous structures with high aspect ratios were successfully printed using these approaches, including cantilevers only supported at one end. This work provides further insight and broadens the utility of 3D printing with silk fibroin inks for the microfabrication of proteinaceous structures.

Complex Morphogenesis by a Model Intrinsically Disordered Protein.

The development of intricate and complex self-assembling structures in the micrometer range, such as biomorphs, is a major challenge in materials science. Although complex structures can be obtained from self-assembling materials as they segregate from solution, their size is usually in the nanometer range or requires accessory techniques. Previous studies with intrinsically disordered proteins (IDPs) have shown that the active interplay of different molecular interactions provides access to new and more complex nanostructures. As such, it is hypothesized that enriching the variety of intra- and intermolecular interactions in a model IDP will widen the landscape of sophisticated intermediate structures that can be accessed. In this study, a model silk-elastin-like recombinamer capable of interacting via three non-covalent interactions, namely hydrophobic, ion-pairing, and H-bonding is built. This model material is shown to self-assemble into complex stable micrometer-sized biomorphs. Variation of the block composition, pH, and temperature demonstrates the necessary interplay of all three interactions for the formation of such complex structures.

Heterogeneous and Cooperative Rupture of Histidine-Ni2+ Metal-Coordination Bonds on Rationally Designed Protein Templates.

Metal-coordination bonds, a highly tunable class of dynamic noncovalent interactions, are pivotal to the function of a variety of protein-based natural materials and have emerged as binding motifs to produce strong, tough, and self-healing bioinspired materials. While natural proteins use clusters of metal-coordination bonds, synthetic materials frequently employ individual bonds, resulting in mechanically weak materials. To overcome this current limitation, we rationally designed a series of elastin-like polypeptide templates with the capability of forming an increasing number of intermolecular histidine-Ni2+ metal-coordination bonds. Using single-molecule force spectroscopy and steered molecular dynamics simulations, we show that templates with three histidine residues exhibit heterogeneous rupture pathways, including the simultaneous rupture of at least two bonds with more-than-additive rupture forces. The methodology and insights developed improve our understanding of the molecular interactions that stabilize metal-coordinated proteins and provide a general route for the design of new strong, metal-coordinated materials with a broad spectrum of dissipative time scales.

Delivering on the promise of recombinant silk-inspired proteins for drug delivery.

Effective drug delivery is essential for the success of a medical treatment. Polymeric drug delivery systems (DDSs) are preferred over systemic administration of drugs due to their protection capacity, directed release, and reduced side effects. Among the numerous polymer sources, silks and recombinant silks have drawn significant attention over the past decade as DDSs. Native silk is produced from a variety of organisms, which are then used as sources or guides of genetic material for heterologous expression or engineered designs. Recombinant silks bear the outstanding properties of natural silk, such as processability in aqueous solution, self-assembly, drug loading capacity, drug stabilization/protection, and degradability, while incorporating specific properties beneficial for their success as DDS, such as monodispersity and tailored physicochemical properties. Moreover, the on-demand inclusion of sequences that customize the DDS for the specific application enhances efficiency. Often, inclusion of a drug into a DDS is achieved by simple mixing or diffusion and stabilized by non-specific molecular interactions; however, these interactions can be improved by the incorporation of drug-binding peptide sequences. In this review we provide an overview of native sources for silks and silk sequences, as well as the design and formulation of recombinant silk biomaterials as drug delivery systems in a variety of formats, such as films, hydrogels, porous sponges, or particles.

Fast and reversible crosslinking of a silk elastin-like polymer.

Elastin-like polymers (ELPs) and their chimeric subfamily the silk elastin-like polymers (SELPs) exhibit a lower critical solvation temperature (LCST) behavior in water which has been extensively studied from theoretical, computational and experimental perspectives. The inclusion of silk domains in the backbone of the ELPs effects the molecular dynamics of the elastin-like domains in response to increased temperature above its transition temperature and confers gelation ability. This response has been studied in terms of initial and long-term changes in structures, however, intermediate transition states have been less investigated. Moreover, little is known about the effects of reversible hydration on the elastin versus silk domains in the physical crosslinks. We used spectroscopic techniques to analyze initial, intermediate and long-term states of the crosslinks in SELPs. A combination of thermoanalytical and rheological measurements demonstrated that the fast reversible rehydration of the elastin motifs adjacent to the relatively small silk domains was capable of breaking the silk physical crosslinks. This feature can be exploited to tailor the dynamics of these types of crosslinks in SELPs. STATEMENT OF SIGNIFICANCE: The combination of silk and elastin in a single molecule results in synergy via their interactions to impact the protein polymer properties. The ability of the silk domains to crosslink affects the thermoresponsive properties of the elastin domains. These interactions have been studied at early and late states of the physical crosslinking, while the intermediate states were the focus of the present study to understand the reversible phase-transitions of the elastin domains over the silk physical crosslinking. The thermoresponsive properties of the elastin domains at the initial, intermediate and late states of silk crosslinking were characterized to demonstrate that reversible hydration of the elastin domains influenced the reversibility of the silk crosslinks.

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

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

A transferrin receptor-binding mucoadhesive elastin-like recombinamer: In vitro and in vivo characterization.

The development of mucoadhesive materials is of great interest and is also a major challenge. Being adsorption sites, mucosae are suitable targets for drug delivery, but as defensive barriers they are complex biological surfaces to interact with, mainly due to their protective mucus layer. As such, first- and second-generation mucoadhesives focused on material-mucus interactions, whereas the third generation of mucoadhesives introduced structural motifs that are able to interact with the cells beneath the mucus layer. The combination of different prerequisites (water solubility, soft gel formation at body temperature and able to interact with the mucus) in a single molecule is easily achieved using elastin-like recombinamers (ELRs) given their multiple block design. Moreover, we have been able to introduce a short amino-acid sequence known as T7 that is able to bind to transferrin receptors in the epithelial cell layer. The T7 sequence enhances the cell-binding properties of the mucoadhesive ELR (MELR), as demonstrated using a Caco-2 epithelial cell model. In vivo experiments confirmed the mucoadhesive properties found in vitro. STATEMENT OF SIGNIFICANCE: The development of a mucoadhesive material is a major challenge. Mucosae are suitable targets for drug delivery, but as defense barriers, they are complex surfaces to interact with. In this work we report the first ELR that combines different functional blocks, in a single molecule, which provide it with the properties of soft-gel forming at body temperature and being able of efficiently adhering to the mucus layer of mucosas, as well as to the underlying epithelial cell layer, as demonstrated in vitro and in vivo. The rationally designed materials presented in this work sets the basis for developing ELR-based, mucosa-directed drug delivery systems, which could improve patient's compliance, enhancing drug retention at the mucosal site.

Recombinant Technology in the Development of Materials and Systems for Soft-Tissue Repair.

The field of biomedicine is constantly investing significant research efforts in order to gain a more in-depth understanding of the mechanisms that govern the function of body compartments and to develop creative solutions for the repair and regeneration of damaged tissues. The main overall goal is to develop relatively simple systems that are able to mimic naturally occurring constructs and can therefore be used in regenerative medicine. Recombinant technology, which is widely used to obtain new tailored synthetic genes that express polymeric protein-based structures, now offers a broad range of advantages for that purpose by permitting the tuning of biological and mechanical properties depending on the intended application while simultaneously ensuring adequate biocompatibility and biodegradability of the scaffold formed by the polymers. This Progress Report is focused on recombinant protein-based materials that resemble naturally occurring proteins of interest for use in soft tissue repair. An overview of recombinant biomaterials derived from elastin, silk, collagen and resilin is given, along with a description of their characteristics and suggested applications. Current endeavors in this field are continuously providing more-improved materials in comparison with conventional ones. As such, a great effort is being made to put these materials through clinical trials in order to favor their future use.