Molecular Systems Design & Engineering最新文献

The lack of highly effective therapeutics to treat the life threatening disease caused by dengue virus (Denv) has posed several challenges to the human community. The increasing prevalence of dengue infections has demanded advanced strategies for disease surveillance and to accomplish precise diagnosis across all reported serotypes of Denv. A promising combating approach involved the targeted inhibition of specific viral proteins that are involved in the pathogenesis pathway of the virus. With the recently developed advanced strategies of rational drug design and chemical modifications such approaches have been more successful. Further, the efficacy and specificity of the proposed drugs can further be optimized through structure–activity relationship (SAR) evaluations. With the established role of non-structural protein 1 (NS1) of the dengue virus (dNS1) in pathogenesis, herein a few hydrazide-based derivatives were strategically designed to block its functions including replication, immune evasion, endothelial dysfunction, etc. The inhibition of this protein could effectively curb the viral pathogenicity. Moreover, this study explores the rational design and synthesis of novel hydrazide derivatives to target NS1, thereby offering a potential therapeutic intervention against dengue. The findings could contribute to the advancement of antiviral drug development, addressing the urgent need for effective treatment options against dengue infections.

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.

Cyclic swing adsorption processes, such as pressure/vacuum swing adsorption (PVSA), is a promising technology for upgrading biogas by separating carbon dioxide (CO₂) from methane (CH₄). The rational design of adsorbent materials with tailored properties is important for deployment of high-performance PVSA technology. Metal–organic frameworks (MOFs), particularly the CALF-20 isoreticular series, have attracted interest due to their high CO₂ selectivity, thermal and water stability. In this study, we report a multiscale assessment of CALF-20 and its isoreticular five derivatives by integrating molecular simulations with PVSA process optimization and techno-economic analysis. Structural and adsorption characteristics were calculated and employed to assess how each material performs in terms of energy efficiency and cost. The analysis reveals distinct differences in cost performance among the CALF-20 series, with CALF-20 showing the most favorable economics with >97% purity CH₄ production cost at $4.31 per kg of CH₄ and energy consumption of 9.35 kWh kg⁻¹ of CH₄. This study demonstrates that the integrated material-process optimization framework can effectively guide the search for adsorbent materials for biogas upgrading.

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

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.