Residual Interaction Research Articles

An Updated Account of Multifaceted Medicinal Values of Garlic: A Systematic Review

Background: Garlic (Allium sativum L.), one of the most important medicinal plants and spices, has many neuroprotective medicinal properties. Garlic has been mentioned in Indian medical traditions and Chinese literature as a remedy for infectious and other non-communicable diseases. Raw garlic and its derivatives have been used to treat a variety of ailments. Objectives: In this article, we attempted to summarize the numerous characteristics of specific sulfur-containing garlic components that have been observed thus far, to have a variety of medicinal aspects. Methods: Non-overlapping literature sources from recent years were searched and extracted using databases such as Dimensions, Google Scholar, and PubMed. We have summarized the concluding outputs collectively from the systematic literature search. Second, the catalytic site of the alliinase enzyme was identified to be formed by Y165, N207, D225, Y228, and K251 amino acid residues. We investigated the interaction of active site residues with the alliinase enzyme's natural substrate further, and the catalytic mechanism was deduced using molecular docking. Results: Several studies on various garlic products and their numerous derivatives are currently being conducted and vividly reported. These studies have found that it has antitumor activity as well as the ability to treat digestive issues and ulcers. Additionally, several potential antibacterial, antiviral, anticoagulant, etc. characteristics were reported by garlic components. Conclusion: In conclusion, the review focuses on the successful research on numerous novel garlic components and their derivatives, which may be useful in next-generation therapeutic approaches. In addition, it advises the use of garlic in moderation rather than carelessly.

Shot peening simulation oriented to residual stress interaction with gear grinding

The current study proposes a shot peening model which enables the residual stress interaction with grinding, a typical combination for gear finishing. The effect of the interaction on the stress state development was addressed by comparing the residual stress state from a standalone shot peening procedure, against the residual stress state arising from a manufacturing route where the interaction of shot peening and grinding takes place. In the interaction model, the grinding procedure generates a pre-loaded condition on the material, modifying the internal strain system of the gear tooth. This pre-loaded system, when disturbed by shot peening, reaches a new internal strain equilibrium. In the interaction model, a 24% less compressive stress state was attained when compared with the standalone shot peening process. A significant shift in the depth and magnitude of the peak compressive stress was also observed. On account of the numerical study of the processes’ interaction, the developed model substantially contributed to understanding the residual stress formation during manufacturing chains.

Structural basis of the American mink ACE2 binding by Y453F trimeric spike glycoproteins of SARS-CoV-2.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) enters the host cell by binding to angiotensin-converting enzyme 2 (ACE2). While evolutionarily conserved, ACE2 receptors differ across various species and differential interactions with Spike (S) glycoproteins of SARS-CoV-2 viruses impact species specificity. Reverse zoonoses led to SARS-CoV-2 outbreaks on multiple American mink (Mustela vison) farms during the pandemic and gave rise to mink-associated S substitutions known for transmissibility between mink and zoonotic transmission to humans. In this study, we used bio-layer interferometry (BLI) to discern the differences in binding affinity between multiple human and mink-derived S glycoproteins of SARS-CoV-2 and their respective ACE2 receptors. Further, we conducted a structural analysis of a mink variant S glycoprotein and American mink ACE2 (mvACE2) using cryo-electron microscopy (cryo-EM), revealing four distinct conformations. We discovered a novel intermediary conformation where the mvACE2 receptor is bound to the receptor-binding domain (RBD) of the S glycoprotein in a "down" position, approximately 34° lower than previously reported "up" RBD. Finally, we compared residue interactions in the S-ACE2 complex interface of S glycoprotein conformations with varying RBD orientations. These findings provide valuable insights into the molecular mechanisms of SARS-CoV-2 entry.

In-silico and in-vitro studies of two cannabinoids of Cannabis sativa against prostate cancer

The phytochemical profiling of different extracts revealed the presence of high concentration of CBD in 80:20 hydroalcoholic extract, and that of THC in 60:40 hydroalcoholic extract. The MTT assay of combination of CBD and THC highlighted the extracts as potent cytotoxic agents against prostate cancer (PC3) cells, with IC50 values of 1292 ng/ml, 953.3 ng/ml and 1134 ng/ml, respectively for HCP-CO4, HCM-CO1 & HCZ-CO1. The molecular docking study revealed a good binding of androgen receptor (PDB ID, 2am9) with CBD and THC possessing binding affinity energy of -7.1 and -7.2 kcal/mol respectively. Based on the amino acid residual interaction of CBD and THC within the 2am9 receptor, THC reported additional hydrogen bonds as compared to CBD, suggesting it to be more potent antagonist in comparison to CBD. The present study highlighted the potential of CBD and THC as a therapeutic agent for treatment of prostate cancer.

M Protein from Dengue virus oligomerizes to pentameric channel protein: in silico analysis study.

The Dengue virus M protein is a 75 amino acid polypeptide with two helical transmembranes (TM). The TM domain oligomerizes to form an ion channel, facilitating viral release from the host cells. The M protein has a critical role in the virus entry and life cycle, making it a potent drug target. The oligomerization of the monomeric protein was studied using ab initio modeling and molecular dynamics (MD) simulation in an implicit membrane environment. The representative structures obtained showed pentamer as the most stable oligomeric state, resembling an ion channel. Glutamic acid, threonine, serine, tryptophan, alanine, isoleucine form the pore-lining residues of the pentameric channel, conferring an overall negative charge to the channel with approximate length of 51.9 Å. Residue interaction analysis (RIN) for M protein shows that Ala94, Leu95, Ser112, Glu124, and Phe155 are the central hub residues representing the physicochemical interactions between domains. The virtual screening with 165 different ion channel inhibitors from the ion channel library shows monovalent ion channel blockers, namely lumacaftor, glipizide, gliquidone, glisoxepide, and azelnidipine to be the inhibitors with high docking scores. Understanding the three-dimensional structure of M protein will help design therapeutics and vaccines for Dengue infection.

Showcasing Different G-Quadruplex Folds of a G-Rich Sequence: Between Rule-Based Prediction and Butterfly Effect.

In better understanding the interactions of G-quadruplexes in a cellular or noncellular environment, a reliable sequence-based prediction of their three-dimensional fold would be extremely useful, yet is often limited by their remarkable structural diversity. A G-rich sequence related to a promoter sequence of the PDGFR-β nuclease hypersensitivity element (NHE) comprises a G3-G3-G2-G4-G3 pattern of five G-runs with two to four G residues. Although the predominant formation of three-layered canonical G-quadruplexes with uninterrupted G-columns can be expected, minimal base substitutions in a non-G-tract domain were shown to guide folding into either a basket-type antiparallel quadruplex, a parallel-stranded quadruplex with an interrupted G-column, a quadruplex with a V-shaped loop, or a (3+1) hybrid quadruplex. A 3D NMR structure for each of the different folds was determined. Supported by thermodynamic profiling on additional sequence variants, formed topologies were rationalized by the identification and assessment of specific critical interactions of loop and overhang residues, giving valuable insights into their contribution to favor a particular conformer. The variability of such tertiary interactions, together with only small differences in quadruplex free energies, emphasizes current limits for a reliable sequence-dependent prediction of favored topologies from sequences with multiple irregularly positioned G-tracts.

Machine learning models based on residue interaction network for ABCG2 transportable compounds recognition

As the one of the most important protein of placental transport of environmental substances, the identification of ABCG2 transport molecules is the key step for assessing the risk of placental exposure to environmental chemicals. Here, residue interaction network (RIN) was used to explore the difference of ABCG2 binding conformations between transportable and non-transportable compounds. The RIN were treated as a kind of special quantitative data of protein conformation, which not only reflected the changes of single amino acid conformation in protein, but also indicated the changes of distance and action type between amino acids. Based on the quantitative RIN, four machine learning algorithms were applied to establish the classification and recognition model for 1100 compounds with transported by ABCG2 potential. The random forest (RF) models constructed with RIN presented the best and satisfied predictive ability with an accuracy of training set of 0.97 and the test set of 0.96 respectively. In conclusion, the construction of residue interaction network provided a new perspective for the quantitative characterization of protein conformation and the establishment of prediction models for transporter molecular recognition. The ABCG2 transport molecular recognition model based on residue interaction network provides a possible way for screening environmental chemistry transported through placenta.

Free Energy Landscapes of the Tautomeric Interconversion of Pyridoxal 5'-Phosphate Aldimines at the Active Site of Ornithine Decarboxylase in Aqueous Media.

The pyridoxal 5'-phosphate (PLP) acts as a coenzyme for a large number of biochemical reactions. It exists in mainly two bound forms at the active site of the concerned enzyme: the internal aldimine, in which the PLP is bound with the ϵ-amino group of lysine at the active site, and the external aldimine, where the PLP is bound to the substrate amino acid. Both the internal and external aldimines have Schiff base linkage (N-H-O) and can exist in two tautomeric structures of ketoenamine and enolimine forms. In this work, we have investigated the free energy landscape for the tautomeric proton transfer in the internal and external aldimines at the active site of the ornithine decarboxylase enzyme in an aqueous medium. We performed hybrid quantum-classical metadynamics and force field-based molecular dynamics simulations, which revealed that the ketoenamine tautomer is more stable than the enolimine form. The QM/MM metadynamics calculations show that the free energy difference between the ketoenamine and enolimine forms for the internal aldimine is 3.9 kcal/mol, and it is found to be 5.8 kcal/mol for the external aldimine, with the ketoenamine form being more stable in both cases. The results are further supported by calculations of the binding free energies from classical simulations and static quantum chemical calculations in different environments. We have also analyzed the configurational structure of the microenvironment at the active site in order to have better insights into the interactions of the active site residues with the PLP in its two tautomeric forms.

Elucidation of benzene sulfonamide derivative binding at a novel interprotomer pocket of wild type and mutants of coxsackievirus B3 viral capsid using molecular dynamics simulations and density functional theory

Coxsackievirus B3 (CVB3), a serotype of enterovirus B, causes hand, foot, and mouth disease; pericarditis; and myocarditis. A benzene sulfonamide derivative is reported to have inhibitory activity against wild-type (WT) and eight mutants of the viral capsid of CVB3. Furthermore, the crystal structure of the complex formed between WT viral capsid of CVB3 and the derivative revealed binding at a novel druggable interprotomer pocket. We investigated how the compound could be a potent inhibitor of both WT and some mutants of CVB3 by determining binding to the viral capsid and the interaction energy with the binding pocket based on molecular dynamics simulations and density functional theory. We found that hydrogen bonds, pi–pi interactions, and electrostatic interactions are the key interactions with a protomer unit of CVB3 viral capsid. The residual interaction energy determined using density functional theory revealed key binding with VP1:Arg234 and a residue in the nearby VP1 unit (VP1’:Arg219). These results explain why the compound is still a potent inhibitor against eight mutants. Moreover, the decreased inhibitory activity for some mutants could be explained by the calculated binding energy and the highest occupied molecular orbital and lowest unoccupied molecular orbital energy. The results will be helpful for the development of drugs resistant to CVB3.

EGCG-Mediated Protection of Transthyretin Amyloidosis by Stabilizing Transthyretin Tetramers and Disrupting Transthyretin Aggregates.

Transthyretin amyloidosis (ATTR) is a progressive and systemic disease caused by the misfolding and amyloid aggregation of transthyretin (TTR). Stabilizing the TTR tetramers and disrupting the formed TTR aggregation are treated as a promising strategy for the treatment of ATTR. Previous studies have reported that epigallocatechin gallate (EGCG) can participate in the whole process of TTR aggregation to prevent ATTR. However, the interaction mechanism of EGCG in this process is still obscure. In this work, we performed molecular dynamics simulations to investigate the interactions between EGCG and TTR tetramers, and between EGCG and TTR aggregates formed by the V30M mutation. The obtained results suggest that EGCG at the binding site of the V30M TTR tetramer can form stable hydrogen bonds with residues in the flexible AB-loop and EF-helix-loop, which reduces the structural mobility of these regions significantly. Additionally, the polyaromatic property of EGCG contributes to the increasement of hydrophobicity at the binding site and thus makes the tetramer difficult to be solvated and dissociated. For V30M-TTR-generated aggregates, EGCG can promote the dissociation of boundary β-strands by destroying key residue interactions of TTR aggregates. Moreover, EGCG is capable of inserting into the side-chain of residues of neighboring β-strands and disrupting the highly structured aggregates. Taken together, this study elucidates the role of EGCG in preventing TTR amyloidosis, which can provide important theoretical support for the future of drug design for ATTR.

AQcalc: A web server that identifies weak molecular interactions in protein structures.

Weak molecular interactions play an important role in protein structure and function. Computational tools that identify weak molecular interactions are, therefore, valuable for the study of proteins. Here, we present AQcalc, a web server (https://aqcalcbiocomputing.com/) that can be used to identify anion-quadrupole (AQ) interactions, which are weak interactions involving aromatic residue (Trp, Tyr, and Phe) ring edges and anions (Asp, Glu, and phosphate ion) both within proteins and at their interfaces (protein-protein, protein-nucleic acids, and protein-lipid bilayer). AQcalc identifies AQ interactions as well as clusters involving AQ, cation-π, and salt bridges, among others. Utilizing AQcalc we analyzed weak interactions in protein models, even in the absence of experimental structures, to understand the contributions of weak interactions to deleterious structural changes, including those associated with oncogenic and germline disease variants. We identified several deleterious variants with disrupted AQ interactions (comparable in frequency to cation-π disruptions). Amyloid fibrils utilize AQ to bury anions at frequencies that far exceed those observed for globular proteins. AQ interactions were detected three and five times more frequently than the hydrogen-bonded AQ (HBAQ) in fibril structures and protein-lipid bilayer interfaces, respectively. By contrast, AQ and HBAQ interactions were detected with similar frequencies in globular proteins. Collectively, these findings suggest AQcalc will be effective in facilitating fine structural analysis. As other web utilities designed to identify protein residue interaction networks do not report AQ interactions, wide use of AQcalc will enrich our understanding of residue interaction networks and facilitate hypothesis testing by identifying and experimentally characterizing these comparably weak but important interactions.

P2Y12 receptor residues crucial for thrombosis regulation.

Thrombosis, or the formation of blood clots, can lead to serious medical conditions such as stroke, heart attack, and deep vein thrombosis. The purinoreceptor P2Y12 plays a critical role in the thrombotic pathway and is targeted for therapy to prevent clot formation. However, it is essential to balance the regulation of thrombosis to avoid adverse situations. This study focuses on the P2Y12 receptor and aims to discern the protein residue network and differentiate residues based on their intramolecular interactions. The study utilized a statistical analysis to characterize the significant residues involved in ligand interaction, which helps to identify critical residues that are essential for the function of the receptor. A parametric analysis of interactions of residues in the intraprotein interaction was conducted, which revealed significant residue-based contacts that facilitate protein interactions. By examining the interactions between residues, the mechanisms underlying protein interactions were studied and the importance of specific residues in facilitating these interactions was determined. This research provides important information on P2Y12, and the findings based on the networkbased significance of interacting residues may contribute to the development of new therapies that target the receptor to prevent clot formation while maintaining a balance in thrombosis regulation to avoid adverse outcomes. Ultimately, this study could lead to improved treatments for thrombotic disorders and better patient outcomes.

Rinmaker: a fast, versatile and reliable tool to determine residue interaction networks in proteins

BackgroundResidue Interaction Networks (RINs) map the crystallographic description of a protein into a graph, where amino acids are represented as nodes and non-covalent bonds as edges. Determination and visualization of a protein as a RIN provides insights on the topological properties (and hence their related biological functions) of large proteins without dealing with the full complexity of the three-dimensional description, and hence it represents an invaluable tool of modern bioinformatics.ResultsWe present RINmaker, a fast, flexible, and powerful tool for determining and visualizing RINs that include all standard non-covalent interactions. RINmaker is offered as a cross-platform and open source software that can be used either as a command-line tool or through a web application or a web API service. We benchmark its efficiency against the main alternatives and provide explicit tests to show its performance and its correctness.ConclusionsRINmaker is designed to be fully customizable, from a simple and handy support for experimental research to a sophisticated computational tool that can be embedded into a large computational pipeline. Hence, it paves the way to bridge the gap between data-driven/machine learning approaches and numerical simulations of simple, physically motivated, models.

Inducing an LCST in hydrophilic polysaccharides via engineered macromolecular hydrophobicity

Thermoresponsive polysaccharide-based materials with tunable transition temperatures regulating phase-separated microdomains offer substantial opportunities in tissue engineering and biomedical applications. To develop novel synthetic thermoresponsive polysaccharides, we employed versatile chemical routes to attach hydrophobic adducts to the backbone of hydrophilic dextran and gradually increased the hydrophobicity of the dextran chains to engineer phase separation. Conjugating methacrylate moieties to the dextran backbone yielded a continuous increase in macromolecular hydrophobicity that induced a reversible phase transition whose lower critical solution temperature can be modulated via variations in polysaccharide concentration, molecular weight, degree of methacrylation, ionic strength, surfactant, urea and Hofmeister salts. The phase separation is driven by increased hydrophobic interactions of methacrylate residues, where the addition of surfactant and urea disassociates hydrophobic interactions and eliminates phase transition. Morphological characterization of phase-separated dextran solutions via scanning electron and flow imaging microscopy revealed the formation of microdomains upon phase transition. These novel thermoresponsive dextrans exhibited promising cytocompatibility in cell culture where the phase transition exerted negligible effects on the attachment, spreading and proliferation of human dermal fibroblasts. Leveraging the conjugated methacrylate groups, we employed photo-initiated radical polymerization to generate phase-separated hydrogels with distinct microdomains. Our bottom-up approach to engineering macromolecular hydrophobicity of conventional hydrophilic, non-phase separating dextrans to induce robust phase transition and generate thermoresponsive phase-separated biomaterials will find applications in mechanobiology, tissue repair and regenerative medicine.

Structural characterization of human RPA70N association with DNA damage response proteins.

The heterotrimeric Replication protein A (RPA) is the ubiquitous eukaryotic single-stranded DNA (ssDNA) binding protein and participates in nearly all aspects of DNA metabolism, especially DNA damage response. The N-terminal OB domain of the RPA70 subunit (RPA70N) is a major protein-protein interaction element for RPA and binds to more than 20 partner proteins. Previous crystallography studies of RPA70N with p53, DNA2 and PrimPol fragments revealed that RPA70N binds to amphipathic peptides that mimic ssDNA. NMR chemical-shift studies also provided valuable information on the interaction of RPA70N residues with target sequences. However, it is still unclear how RPA70N recognizes and distinguishes such a diverse group of target proteins. Here, we present high-resolution crystal structures of RPA70N in complex with peptides from eight DNA damage response proteins. The structures show that, in addition to the ssDNA mimicry mode of interaction, RPA70N employs multiple ways to bind its partners. Our results advance the mechanistic understanding of RPA70N-mediated recruitment of DNA damage response proteins.

DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction.

Computationally predicting major histocompatibility complex class I (MHC-I) peptide binding affinity is an important problem in immunological bioinformatics, which is also crucial for the identification of neoantigens for personalized therapeutic cancer vaccines. Recent cutting-edge deep learning-based methods for this problem cannot achieve satisfactory performance, especially for non-9-mer peptides. This is because such methods generate the input by simply concatenating the two given sequences: a peptide and (the pseudo sequence of) an MHC class I molecule, which cannot precisely capture the anchor positions of the MHC binding motif for the peptides with variable lengths. We thus developed an anchor position-aware and high-performance deep model, DeepMHCI, with a position-wise gated layer and a residual binding interaction convolution layer. This allows the model to control the information flow in peptides to be aware of anchor positions and model the interactions between peptides and the MHC pseudo (binding) sequence directly with multiple convolutional kernels. The performance of DeepMHCI has been thoroughly validated by extensive experiments on four benchmark datasets under various settings, such as 5-fold cross-validation, validation with the independent testing set, external HPV vaccine identification, and external CD8+ epitope identification. Experimental results with visualization of binding motifs demonstrate that DeepMHCI outperformed all competing methods, especially on non-9-mer peptides binding prediction. DeepMHCI is publicly available at https://github.com/ZhuLab-Fudan/DeepMHCI.

Underlying Mechanisms of Bergenia spp. to Treat Hepatocellular Carcinoma Using an Integrated Network Pharmacology and Molecular Docking Approach.

Hepatocellular carcinoma (HCC) is the fifth most common and fatal cancer reported, representing 72.5% of malignancies around the world. The majority of HCC incidents have been associated with infections caused by hepatitis B and C viruses. Many first- and second-line conventional drugs, e.g., sorafenib, cabozantinib, or ramucirumab, have been used for the management of HCC. Despite different combinational therapies, there are still no defined biomarkers for an early stage diagnosis of HCC. The current study evaluated the potential of Bergenia stracheyi, Bergenia ciliata, Bergenia pacumbis, and Bergenia purpurascens, which belong to the family Saxifragaceae, to treat HCC using an integrated network pharmacology and molecular docking approach. Four active phytochemicals were selected based on oral bioavailability (OB) and drug likeness (DL) parameters. The criteria of phytochemical selection were set to OB > 30% and DL > 0.18. Similarly, the gene targets related to Bergenia spp. and the genes related to HCC were retrieved from different databases. The integration of these genes revealed 98 most common overlapping genes, which were mainly interrelated with HCC pathogenesis. Ultimately, the 98 Bergenia-HCC associated genes were used for protein-protein interaction (PPI), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) enrichment analyses. Finally, the topological analysis revealed the top ten hub genes with maximum degree rank. From the top ten genes, STAT3, MAPK3, and SRC were selected due to their involvement in GO annotation and KEGG pathway. To confirm the network pharmacology results, molecular docking analysis was performed to target STAT3, MAPK3, and SRC receptor proteins. The phytochemical (+)-catechin 3-gallate exhibited a maximum binding score and strong residue interactions with the active amino acids of MAPK3-binding pockets (S-score: -10.2 kcal/mol), SRC (S-score: -8.9 kcal/mol), and STAT3 (S-score: -8.9 kcal/mol) as receptor proteins. (+)-Catechin 3-gallate and β-sitosterol induced a significant reduction in cell viability in HepG2 after 24 h of treatment in a dose-dependent manner. The results of this study explore the potential of (+)-catechin 3-gallate and β-sitosterol, which can be used in the future as potential drug candidates to suppress HCC.

Structure of the preholoproteasome reveals late steps in proteasome core particle biogenesis.

Assembly of the proteasome's core particle (CP), a barrel-shaped chamber of four stacked rings, requires five chaperones and five subunit propeptides. Fusion of two half-CP precursors yields a complete structure but remains immature until active site maturation. Here, using Saccharomyces cerevisiae, we report a high-resolution cryogenic electron microscopy structure of preholoproteasome, a post-fusion assembly intermediate. Our data reveal how CP midline-spanning interactions induce local changes in structure, facilitating maturation. Unexpectedly, we find that cleavage may not be sufficient for propeptide release, as residual interactions with chaperones such as Ump1 hold them in place. We evaluated previous models proposing that dynamic conformational changes in chaperones drive CP fusion and autocatalytic activation by comparing preholoproteasome to pre-fusion intermediates. Instead, the data suggest a scaffolding role for the chaperones Ump1 and Pba1/Pba2. Our data clarify key aspects of CP assembly, suggest that undiscovered mechanisms exist to explain CP fusion/activation, and have relevance for diseases of defective CP biogenesis.

Computational Elucidation of Protein-Protein Interactions in the Minimal Proteome of JCVI-syn3A

Proteins play a vital role in the regulation of biological processes, facilitating the transfer of intermediates and coordinating the sequential steps of biochemical pathways. Protein-protein interactions (PPIs) are crucial molecular events in which two or more proteins bind together, enabling the formation of protein complexes that govern various cellular activities, including signal transduction, gene expression, and enzymatic reactions. Evolutionary correlations arise due to the close proximity of amino acid side chains within these interactions, where amino acids on one side of an interaction surface may restrict which amino acids fit on the other side or encourage mutations that modify the surface. In this study, our aim is to investigate the correlation between protein sequence and structure in mycoplasma mycoides JCVI-syn3A, a minimal cell consisting of 493 genes. We utilize the EVCouplings framework, a coevolution-based approach with probabilistic scores for residue interactions, to predict protein-protein interactions and the specific surfaces that govern them. Our study demonstrates that coevolution-based computational methods can predict protein-protein interactions and their interaction surfaces. After analyzing multiple sequence alignment (MSA) data across 110 protein families, we identify a total of 33 inter-protein interactions. Our analysis of the protein-protein interactions in JCVI-syn3A provides valuable insights into the genetic architecture of Mycoplasma, one of the simplest cellular life forms known, and enhances our understanding of how the earliest cellular life forms might have functioned.

All natural mussel-inspired bioadhesives from soy proteins and plant derived polyphenols with marked water-resistance and favourable antibacterial profile for wound treatment applications

HypothesisImplementation of tissue adhesives from natural sources endowed with good mechanical properties and underwater resistance still represents a challenging research goal. Inspired by the extraordinary wet adhesion properties of mussel byssus proteins resulting from interaction of catechol and amino residues, hydrogels from soy protein isolate (SPI) and selected polyphenols i.e. caffeic acid (CA), chlorogenic acid (CGA) and gallic acid (GA) under mild aerial oxidative conditions were prepared. ExperimentsThe hydrogels were subjected to chemical assays, ATR FT-IR and EPR spectroscopy, rheological and morphological SEM analysis. Mechanical tests were carried out on hydrogels prepared by inclusion of agarose. Biological tests included evaluation of the antibacterial and wound healing activity, and hemocompatibility. FindingsThe decrease of free NH2 and SH groups of SPI, the EPR features, the good cohesive strength and excellent underwater resistance (15 days for SPI/GA) under conditions relevant to their use as surgical glues indicated an efficient interaction of the polyphenols with the protein in the hydrogels. The polyphenols greatly also improved the mechanical properties of the SPI/ agarose/polyphenols hydrogels. These latter proved biocompatible, hemocompatible, not harmful to skin, displayed durable adhesiveness and good water-vapour permeability. Excellent antibacterial properties and in some cases (SPI/CGA) a favourable wound healing activity on dermal fibroblasts was obtained.