Molecular Systems Design & Engineering最新文献

This study presents a cross-linked bisphenol A propoxylate diglycidyl ether network (BP17) synthesised via a dynamic transesterification reaction. The reaction involves a linear long chain bisphenol A propoxylate diglycidyl ether terminated (BP), high molecular weight cross-linker viz., Pripol 1017, and Zn(OAc)₂ as a catalyst. The thermal dynamics of the BP17 network are investigated using creep recovery tests. BP17 shows appreciable resistance to solvents such as dimethyl sulfoxide (DMSO), even at 160 °C. Thermogravimetric analysis reveals its excellent thermal stability, with an onset degradation temperature of 290 °C. In addition, it could be reprocessed by hot-pressing at 160 °C, retaining its mechanical properties even after the third cycle. Moreover, the cytocompatibility test confirms the biocompatibility of BP17, making it a promising candidate for use in maxillofacial prosthetics. Thus, the thermoset-like properties of BP17, at relatively high temperature, make it very promising for biomedical and other advanced applications.

Salmonellae, which pose a significant global health threat, cause a range of infections, including gastroenteritis and, in severe cases, meningitis, particularly in immunocompromised individuals. The emergence of multi-drug-resistant Salmonella enterica serovar Typhimurium underscores the urgent need for effective vaccine development. In this study, a chimeric vaccine was constructed, targeting UPF0721 transmembrane proteins of serovar Typhimurium strain L-4126, which are critical for its life cycle. Fifteen highly antigenic epitopes, including CTL, HTL, and B-cell epitopes, were recognised and assessed for their ability to elicit T-cell and IFN-γ-mediated immune-responses. Physiochemical analyses confirmed their safety profiles. The vaccine construct integrated these epitopes with linkers (EAAAK, GPGPG, AAY, and KK) and β-defensin adjuvants to enhance immunogenicity, stability, and molecular interactions. Molecular docking demonstrated robust binding affinity, particularly with TLR8, and highlighted the vaccine's structural stability and immunogenic potential. The eigenvalue analysis (9.728895) validated the vaccine's flexibility and favorable biophysical properties. Molecular dynamics simulations validated the energy minimization, molecular stability and flexibility assessments. Immune simulation results indicated strong immune responses, while the physicochemical analysis confirmed solubility and stability during recombinant peptide expression in E. coli. This study also explored mRNA vaccine constructs, emphasizing their potential in combating serovar Typhimurium infections such as meningitis. The vaccine construct showed high potential, demanding further investigation into their immune efficacy against serovar Typhimurium infections through experimental assays and medical trials.

Single-atom catalysts (SACs) have attracted great attention due to their distinct advantages; however, their complicated synthesis procedures have impeded their large-scale application. Additionally, nano-particles or subnano-clusters generated during the synthesis can adversely affect the final performance of the catalysts. The appearance of two-dimensional metal–organic frameworks (2D-MOFs) has provided a new strategy to synthesize SACs. Moreover, highly ordered MOFs have high electrical conductivity and are conducive to electron transfer, which is crucial in improving the electrochemical activity of catalysts. A series of single-atom catalysts TM₃(HATNA)₂ (where TM is one of ten different transition metals) based on 2D-MOFs has been designed using hexazine hetero-trinaphthalene (HATNA) as ligands. The mechanisms and routes of the carbon dioxide reduction reaction (CO₂RR) catalyzed by these materials have been studied using first-principles methods. The results testify that TM₃(HATNA)₂ (TM = Cr, Ru and Rh) may serve as potential catalysts for the CO₂RR with good stability and catalytic activity. The reduction product of Cr₃(HATNA)₂ is methane (CH₄), while that of both Ru₃(HATNA)₂ and Rh₃(HATNA)₂ is methanol (CH₃OH). This work provides a new substrate material for the development of single-atom catalysts with abundant and diverse catalytic products.

In this work, we have investigated the semiconducting properties of an unprecedented 1 : 1 π-stacked donor–acceptor cocrystal of 1,5-dihydroxynaphthalene (DHN) as the π-donor (D) with 7,7′,8,8′-tetracyanoquinodimethane (TCNQ) as the π-acceptor (A). Molecular semiconductors with electron dominant transport, narrow bandgap, solution processing ability, air-stability are highly sought-after for application in n-channel organic field effect transistors. The DHN : TCNQ cocrystal shows n-type semiconductor nature with a narrow bandgap of around 1 eV, and a low LUMO energy level (−3.8 eV) making it less prone to areal degradation. The electron dominant transport in this cocrystal is described by assuming that electron and hole hop via a super-exchange mechanism along the mixed ⋯D–A⋯ π-stack direction. The participation of bridging molecular orbitals other than donor HOMO make a significant contribution to the super-exchange electron transfer, thus resulting in electron hopping from acceptor to acceptor which is four times larger than the value of hole hopping from donor to donor. Detailed analysis of crystal packing and electronic properties demonstrate that the super-exchange charge carrier transport is facilitated by strong π⋯π stacking interaction between the donor and acceptor, and prominent charge transfer.

An aminal tying method was applied to post-synthetically modify a flexible organic cage, RCC1, to construct a porous ionic liquid (PIL). The resulting PIL, [RCC1-IM][NTf₂]₆, displayed melting behaviour below 100 °C, a transition to a glass phase on melt-quenching, CO₂ uptake, and its permanent porosity was confirmed using molecular dynamic simulations.

Machine learning accelerates material discovery which includes selection of candidate small molecules and polymers for high-efficiency organic photovoltaic (OPV) materials. However, conventional machine learning models suffer from data scarcity for conjugated oligomers, crucial for OPV material production. To address this challenge, transfer learning within a graph neural network was introduced to reduce the data requirement while accurately predicting the electronic properties of the conjugated oligomers. By leveraging on transfer learning using original conjugated oligomer data and pre-trained models from the renowned PubChemQC dataset, the limitations posed by insufficient data were mitigated. The models in this study achieved a low mean absolute error, ranging from 0.46 to 0.74 eV, for the HOMO, LUMO, and HOMO–LUMO gap. An original candidate dataset of 3710 conjugated oligomers was constructed for materials discovery, and a high-throughput screening pipeline was developed by integrating the models with density functional theory. This pipeline effectively identified 46 promising conjugated oligomer candidates, showcasing its effectiveness in accelerating the discovery of advanced materials for organic photovoltaics. These results demonstrated the potential of the approach used in this study to overcome data scarcity while accelerating the discovery of new innovative materials in organic electronics.

Chemical doping is a versatile method for tuning the optoelectronic properties of organic semiconductors (OSCs). Compared to p-type doping, achieving stable and efficient n-type doping in OSCs, especially in small molecules, remains a significant challenge. The lack of a universal doping strategy, along with OSCs having deep lowest unoccupied molecular orbital (LUMO) energy levels and high electron mobility, limits the development of n-type doped OSCs. In this work, a ternary system containing the small-molecule OSC 2DQTT-o, with a deep LUMO level and high electron mobility, the n-type dopant N-DMBI, and the polar insulating polymer PEO was developed. With the introduction of PEO, the miscibility, doping level and doping stability were significantly improved. Notably, the ternary doped components showed excellent air stability, retaining 82% of the initial electrical conductivity after exposure to air for 240 h, representing a 32% improvement compared to the system without PEO. Furthermore, the ternary doped films exhibited good thermal stability, retaining 55% of the initial electrical conductivity after heating at 200 °C. In contrast, the two-component doped films decomposed and became insulating.

We develop a generic computational methodology to understand and predict adhesion between polymers and solid substrates. The motion of coarse-grained polymer segments is tracked via a hybrid particle-field mesoscopic simulation method (BD/kMC) combining Brownian dynamics (BD) and kinetic Monte Carlo (kMC) for the entanglement dynamics as described by the slip-spring model. The method addresses entangled polymer films capped between solid surfaces under both quiescent and nonequilibrium conditions. The latter entail imposing constant rate extension along the aperiodic (normal) direction, while keeping the lateral dimensions constant. Experimentally relevant length scales and elongation rates can be addressed thanks to the coarse-graining inherent in the approach. These simulations are representative of “tack” tests, employed routinely for assessing the performance of soft adhesive materials. The performance of each interface is characterized by the stress–strain curves, yield stress, and toughness. The failure mechanism is determined upon analyzing the evolution of the stress–strain curve and the morphology of the fractured interfaces. The simulations are conducted over a broad parameter space by varying the rate of elongation, the rate constants for attachment/detachment of polymer segments to/from the surface, and the activation length. The latter describes the coupling with the pulling forces exerted on the particles at the interface by the rest of the polymer. Setting the activation length to zero is suitable for describing strong adhesives or highly compressible materials (foams). Under these conditions, toughness is maximized and increases significantly with elongation rate, sometimes leading to chain fracture. With increasing activation length the toughness of the interface decreases and detachment becomes more efficient at higher elongation rates since the increased stress accelerates the detachment process. In all cases considered here, toughness increases monotonically with adhesion. Furthermore, the yield stress increases consistently with increasing elongation rate due to the inability of the polymer to relax the imposed stress.

Vasoactive intestinal peptide (VIP) is a promising anti-inflammatory peptide therapeutic that is known to induce biological effects by interacting with its cognate receptor (i.e., VPAC) on the surface of antigen presenting cells (APCs). Little is known about how VPAC targeting affects APC behavior for VIP-based drug delivery systems like nano- and microparticles. This is further influenced by the fact that particulate material properties including chemistry, shape, and size are all known to influence APC behavior. In this study, peptide amphiphile micelles (PAMs) were employed as a modifiable platform to study the impact VPAC targeting and physical particle properties have on their association with macrophages. VIP amphiphile micelles (VIPAMs) and their scrambled peptide amphiphile micelle analogs (^SVIPAMs) were fabricated from various chemistries yielding particle batches that were comprised of spheres (10–20 nm in diameter) and/or cylinders of varying lengths (i.e., 20–9000 nm). Micelle surface attachment to and internalization by macrophages were observed using confocal microscopy and their association was characterized by flow cytometry. The enclosed work provides strong evidence that macrophages rapidly bind VPAC specific micelles, and that micelle shape, size, and receptor-specificity all influence macrophage association and internalization. Specifically, a mixture of spherical and short cylindrical VIPAMs were able to achieve the greatest cell association which may correlate to their capacity to fully bind the VPAC receptors available on the surface of macrophages. These results provide the foundation of how nano- and microparticle physical properties and targeting capacity combine to influence their capacity to associate with APCs.

The formulation of biologics for increased shelf life stability is a complex task that depends on the chemical composition of both the active ingredient and any excipients in solution. A large number of unique excipients are typically required to stabilize biologics. However, it is not well-known how these excipient combinations influence biologics stability. To examine these formulations at the molecular level, we performed molecular dynamics simulations of arginine – a widely used excipient with unique properties – in solution both alone and with equimolar concentrations of lysine or glutamate. We studied the effects of these mixtures on a hydrophobic polymer model to isolate excipient mechanisms on hydrophobic interactions relevant in both protein folding and aggregation, crucial phenomena in biologics stability. We observed that arginine is the most effective single excipient in stabilizing hydrophobic polymer folding, and its effectiveness is augmented by lysine or glutamate addition. We decomposed the free energy of polymer folding/unfolding to identify that the key source of arginine–lysine and arginine–glutamate synergy is a reduction in destabilizing polymer–excipient interactions. We additionally applied principles from network theory to characterize the local solvent network embedding the hydrophobic polymer. Through this approach, we found arginine supports a more highly connected and stable local solvent network than in water, lysine, or glutamate solutions. These network properties are preserved when lysine or glutamate are added to arginine solutions. Taken together, our results highlight important molecular features in excipient solutions that establish the foundation for rational formulation design.