Molecular Systems Design & Engineering最新文献

Salbutamol (SBM), a β₂-adrenergic agonist commonly prescribed for bronchospasm, is increasingly monitored in sports medicine due to its potential misuse as a performance-enhancing agent. To address the need for rapid, cost-effective, and portable anti-doping diagnostics, a nanozyme-based sensing platform using copper–gallic acid hybrid structures (Cu@GA·HSs) was developed. These nanozymes exhibited oxidase-like activity, enabling sensitive and selective optical detection of SBM across a wide concentration range (125–5000 μg mL⁻¹), with excellent analytical accuracy (96.8–99.8%) and precision (CV < 2.0%). The system demonstrated strong operational stability, retaining 60% catalytic activity after 24 days at 4 °C, and strong resistance to chemical interference, including metal ions and non-polar solvents (selectivity coefficient ≈1). Benchmarking against HPLC revealed excellent agreement (R² = 0.997; deviation <0.06%), validating its analytical performance. Molecular docking and dynamics simulations further revealed specific SBM–matrix interactions underlying the sensor's selectivity and robustness. Together, these results highlight a systems-level approach integrating nanozyme chemistry with computational modeling to engineer next-generation biosensors for anti-doping applications.

Photonic crystals can be self-assembled from binary colloidal dispersions, but the robust assembly of high-quality crystals in quantities sufficient for large-scale applications remains challenging. Here, we study the assembly of polyhedral colloidal nanoparticles at surfaces with spherical and flat-wall geometries to examine the influence of confinement on the process and products of crystallization compared to the bulk. We find that confinement improves crystallization at non-ideal stoichiometries but does not lower the minimal packing fraction at which crystallization occurs. Crystals formed in confinement exhibit higher degrees of crystallinity and lower quantities of secondary-phase defects: the formation of well-ordered layers and shells appears to be promoted by flat walls and spherical container interfaces. These findings demonstrate the potential for enhanced control over the synthesis of novel materials with tailored structures and properties for photonic applications.

Retraction of ‘Identification of MIG7, TGM2, CXCL8, and PDGFC as key genes in colon cancer with a bioinformatics-driven strategy for multi-epitope vaccine design’ by Zhenhai Jing et al., Mol. Syst. Des. Eng., 2025, https://doi.org/10.1039/D5ME00104H.

The use of granular fertilizers offers significant advantages over traditional powder forms, including improved nutrient distribution, reduced dust, and controlled nutrient release. These benefits enhance plant growth while minimizing negative environmental impacts. The addition of reused materials (recycle) significantly influences the size distribution and strength of granular fertilizers. It was determined that incorporating 60% recycle increases the part of commercial granules (size 2.0–4.0 mm) from 22% to about 68%. However, this increase is accompanied by a decrease in static strength, which drops from 2.8–3.8 MPa to 1.7–2.3 MPa. Modelling granulation processes holds substantial potential for the fertilizer industry, enabling the optimization of high-quality granular fertilizer production while minimizing the need for extensive experimental trials. This approach not only streamlines manufacturing but also ensures consistent nutrient supply, ultimately contributing to improved crop yields and sustainable agricultural practices. In this study, a simulation model based on an actual granulation drum was used to investigate the granulation process of a mixture containing recycled material, crystalline urea, and the microalgae Chlorella vulgaris sp. The granulation simulation data showed that granule formation began within 30 seconds and that the desired quantity of the mixture was produced in just 30 seconds. Throughout the process, the segregation coefficient remained near zero, indicating effective granule formation and distribution.

The thermal stability of CRISPR-Cas nucleases is a critical factor for their successful application in 'one-pot' diagnostic assays that utilize high-temperature isothermal amplification. To understand the atomistic mechanism of stabilization in a previously engineered variant of the thermostable BrCas12b protein, we performed all-atom molecular dynamics (MD) simulations on the wild-type and mutant forms of apo BrCas12b. High-temperature simulations reveal a small structural change along with greater flexibility in the PAM-interacting domain of the mutant BrCas12b, with marginal structural and flexibility changes in the other mutated domains. Comparative essential dynamics analysis between the wild-type and mutant BrCas12b at both ambient and elevated temperatures provides insights into the stabilizing effects of the mutations. Our findings offer comprehensive insights into the important protein motions induced by these mutations. These results provide insights into thermal stability mechanisms in BrCas12b that may inform the future design of CRISPR-based tools.

Soft material-based synthetic polymer membranes are emerging as transformative platforms for energy, environmental, and healthcare technologies, attributed to their flexibility, tunability, and multifunctionality. These membranes are designed through two principal strategies, i.e. pore-filling and surface/interface engineering. Hydrogels could also be used, especially in biomedical applications, with fibre reinforcement to enhance mechanical stability. Pore-filled or “gel-in-shell” membranes incorporate hydrogels or functional soft materials within porous polymer matrices, combining chemical functionality with structural support. These systems enable the fast and selective transport of ions or molecules, finding applications in fuel cells, batteries, solar desalination, and water purification. Stimuli-responsive designs, where thermally, chemically, piezoelectric or optically sensitive polymers are grafted within or onto membrane pores, enable dynamic control over permeability, critical for smart drug delivery and adaptive filtration. Self-healing hydrogels, driven by dynamic bonding or ionic crosslinking, further enhance membrane longevity under operational stress. On the surface engineering side, functionalization via plasma treatment, graft polymerization, layer-by-layer assembly, molecular layer deposition, or mussel-inspired polydopamine coatings enables control over surface charge, hydrophilicity, and antifouling performance. Advanced materials such as MOFs and MXenes could also be incorporated in membrane designs to enhance functional properties. These engineered interfaces, such as surface patterning or nanofiber anchoring of the surface, are crucial for addressing challenges such as fouling, poor selectivity, and biocompatibility issues typically encountered in traditional membranes. Fibre-reinforced hydrogels further expand the application scope into biomedical systems, offering tissue-like mechanical resilience for tissue scaffolds, wound dressings, and wearable biosensors. This review highlights the integrated design of soft material-based membrane systems and their application across clean energy, sustainable water technology, environmental remediation, and biomedical fields. Such multifunctional membranes are central to next-generation technologies aligned with global sustainability goals.

Examination of binding of cellulose to ice using ab initio modeling reveals that new C–O bonds are formed on the basal ice surfaces, where some of the O atoms are exposed at the surface due to missing H bonds. Further analysis suggests that the cellulose unit binds in such a way as to form a tetrahedral arrangement at the ice surface, evidenced by a geometric measure of tetrahedrality. This hypothesis is further validated for both primary and secondary prismatic planes. This leads us to conclude that in the case of cellulose molecules, binding at ice is dependent on preserving its tetrahedral bonding arrangement. Our findings suggest that the idea of tetrahedrality is very widely applicable to coordination ranging from water to ice-binding proteins, highlighting a design criterion for novel ice-binding/antifreeze proteins/materials.

The structural design of hole transport materials (HTMs) is a crucial approach to improving the efficiency and stability of perovskite solar cells (PSCs). In this study, a series of isomeric dibenzo[b,d]furan-based carbazole derivatives (CX11–CX14) were designed to provide a design strategy for the development of HTMs in PSC applications. Side chain isomerism has a significant impact on molecular conjugation, exhibiting distinct isomer-dependent effects in terms of energy levels, planarity, dipole moment, and hole mobility. Furthermore, theoretical calculations and experimental results indicate that the molecule CX11 with superior hole mobility and stronger adsorption on the perovskite surface can act as a potential HTM for PSC applications. According to the results of the optimized PSC devices, the power conversion efficiency (PCE) of the CX11-based PSC exceeded 23%, which is higher than that of devices based on other molecules. The close agreement between computational predictions and experimental validation not only validates the theoretical framework for designing molecular isomers of HTMs but also provides crucial molecular-level insights. The demonstrated methodology is expected to motivate researchers to develop even more efficient HTM isomers for PSCs with higher PCEs.

Water-lean solvents have emerged as alternatives to conventional aqueous amines for CO₂ capture, although there is delicate balance between achieving high CO₂ loadings while maintaining sufficiently low viscosity. In this work, we present the advantages of serinol as a framework for designing single component water-lean solvents which meet these criteria. Starting from commercially available glycidyl ethers or epichlorohydrin, several symmetric and non-symmetric 1,3-diether-2-amino molecules were synthesized and thoroughly studied. Spectroscopic analyses (¹³C NMR and FTIR) confirmed chemical reactions between CO₂ and the serinol-based water-lean solvents. CO₂ absorption studies showed these solvents had high loading capacities with positive indications for stability and recyclability. The serinol-based molecules have low viscosities in their neat states (1–4 cP at 30 °C) with viscosities as low as 28 cP at 30 °C in highly CO₂-rich states. Furthermore, based on choice of functional groups, serinol-based molecules also show potential as switchable solvents that transition from hydrophobic to hydrophilic upon reaction with CO₂. Our molecular-level simulations reveal how CO₂ binding alters H-bonding networks, reduces free volume, and dramatically increases viscosity with increasing levels of complexation, mirroring the trends observed experimentally. The simulation data also support the observed switchable solvent behavior by elucidating the structural reorganization and dynamic constraints induced by CO₂ loading.

Group contribution (GC) models are powerful, simple, and popular methods for property prediction. However, the most accessible and computationally efficient GC methods, like the Joback and Reid (JR) GC models, often exhibit severe systematic bias. Furthermore, most GC methods do not have uncertainty estimates associated with their predictions. The present work develops a hybrid method for property prediction that integrates GC models with Gaussian process (GP) regression. Predictions from the JR GC method, along with the molecular weight, are used as input features to the GP models, which learn and correct the systematic biases in the GC predictions, resulting in highly accurate property predictions with reliable uncertainty estimates. The method was applied to six properties: normal boiling temperature (T_b), enthalpy of vaporization at T_b (ΔH_vap), normal melting temperature (T_m), critical pressure (P_c), critical molar volume (V_c), and critical temperature (T_c). The CRC Handbook of Chemistry and Physics was used as the primary source of experimental data. The final collected experimental data ranged from 485 molecules for ΔH_vap to 5640 for T_m. The proposed GCGP method significantly improved property prediction accuracy compared to the GC-only method. The coefficient of determination (R²) values of the testing set predictions are ≥0.85 for five out of six and ≥0.90 for four out of six properties modeled, and compare favorably with other methods in the literature. T_m was used to demonstrate one way the GCGP method can be tuned for even better predictive accuracy. The GCGP method provides reliable uncertainty estimates and computational efficiency for making new predictions. The GCGP method proved robust to variations in GP model architecture and kernel choice.