Molecular Systems Design & Engineering最新文献

Detection of cortisol (Cort), a stress hormone, is essential in monitoring chronic and mental health stress. As such, there is growing interest in the development of cortisol molecularly imprinted polymers (MIPs) as molecular receptors for sensor development. Of the cortisol MIPs described in the literature, the optimization of the functional monomers has been through trial-and-error experimentation. Through a computational approach, the number of optimization experiments can be reduced, which is time efficient and cost effective, while reducing chemical wastage. In addition to density functional theory (DFT) calculations, this study used an atomistic molecular dynamics simulation approach that resembles that of the real-life experimental methods to elucidate the compatibility of template-monomer-crosslinkers-solvent for cortisol MIP receptors that can efficiently recognize and capture cortisol from biological fluids. The functional monomer investigated were 4-vinylpyridine (4VP), acrylic acid (AA), acrylamide (AM), glycidyl methacrylate (GMA), 2-hydroxyethyl methacrylate (HEMA) and methylacrylic acid (MAA) with ethylene glycol dimethacrylate (EGDMA) as the crosslinker. The intermolecular hydrogen bonds and the template-monomer binding energies obtained through DFT suggested Cort-MAA as the most stable complex both in the gas phase and solution. Considering the calculated solvent energies, acetonitrile was recommended as a porogenic solvent. Through molecular dynamics simulation, various parameters were analyzed to explain the compatibility of the functional monomer with the cortisol template in the MIP development. From blend analysis of template-monomer, Cort-4VP was found to be the most miscible complex. For template-monomer-crosslinker (EGDMA), the mean square displacement (MSD) and diffusion coefficient analyses indicated 1 : 2 (cortisol/monomer) as the ratio in which the complexes are most stable. The highest peaks observed from the Radial distribution function were for Cort-MAA and Cort-AA at 1 : 4 indicating better interactions of the functional monomers with the Cort. Investigating the effect of solvents for template-monomer-crosslinker-solvent, the lowest MSD was at 1 : 4 with three complexes having the lowest values for solubility parameters at 1 : 4 confirming this ratio to be generally suitable for the composition of cortisol MIPs pre-polymerization.

Amphiphilic molecules spontaneously form self-assembly structures depending on physical conditions such as the molecular structure, concentration, and temperature. These structures exhibit various functionalities according to their morphology. The critical packing parameter (CPP) is used to correlate self-organized structures with the chemical composition. However, accurately calculating it requires information about both the molecular shape and molecular aggregates, making it challenging to apply directly in molecular design. We aimed to predict the self-assembled structure of a molecule directly from its chemical structure and to analyze the factors influencing it using machine learning. Dissipative particle dynamics simulations were used to reproduce many self-assembly structures comprising various chemical structures, and their CPPs were calculated. Machine learning models were built using the chemical structures as input data and the CPPs as output data. As a result, both random forest and the gated recurrent unit showed high prediction accuracy. Feature importance analysis and sample size dependence revealed that the amphiphilic nature of molecules significantly influences the self-assembly structures. Additionally, selecting an appropriate molecular structure representation for each algorithm is crucial. The study results should contribute to product development in the fields of materials science, materials chemistry, and medical materials.

Water-harvesting polymer materials have the potential to create new sources of potable water. However, a holistic understanding of the relationship between polymer structure and water-harvesting properties is lacking compared to studies on specific materials. In this work, we synthesised a library of methacrylic acid-co-poly(ethylene glycol) methyl ether methacrylate)-based hydrogels (poly(MAA-co-PEGMA)) with directed modifications, including composition, crosslinker lengths, crosslinking density and preparation of the hydrogels. MAA serves as a hygroscopic monomer while PEGMA provides hydrophilicity and thermoresponsive properties. The water uptake and release capabilities of all materials was also assessed. The optimised composition of the copolymer (75 : 5 : 20 MAA : EGDMA : PEGMA, mole%) has a water uptake of 98 mg g⁻¹ polymer at 60% RH after 24 hours. The poly(MAA-co-PEGMA) materials also show a capability for water release, showing no significant decrease in water uptake capacity after repeated uptake-release cycles. Minimum temperatures for water release could easily be adjusted with polymer composition, ranging from 50–70 °C. The data presented in this body of work serves as a foundation for future efforts in creating thermoresponsive, water-harvesting polymers with real-world applications.

A facile and eco-friendly synthetic strategy has been developed to achieve a series of hydrogen bonding-rich bio-based thermosetting resins in this study. Using both safe and green solvents, we successfully synthesized target bio-based bisbenzoxazines (DcTa-fa, DcTa-sa, and DcTa-da) with high purity from five different naturally resourced raw materials. The chemical structures of the obtained bisbenzoxazine monomers were verified by nuclear magnetic resonance technology (including ¹H and ¹³C NMR, two-dimensional ¹H–¹H nuclear Overhauser effect spectroscopy (NOESY), and ¹H–¹³C heteronuclear multiple quantum coherence (HMQC)) and Fourier transform infrared spectroscopy (FT-IR). The polymerization processes were systematically investigated by differential scanning calorimetry (DSC) and in situ FT-IR analysis. Contact angle measurements were conducted and the corresponding results revealed tunable surface properties during the polymerization process of each bio-based bisbenzoxazine resin. In order to understand the relationship between the chemical structure and surface properties, more detailed FT-IR analyses were carried out to investigate the hydrogen bonding networks in the resulting polybenzoxazines. Notably, poly(DcTa-fa) presented excellent thermal stability (T_d10 of 377 °C, Y_c of 53.7 wt%) and strong adhesion strength (5.232 ± 0.26 MPa), while poly(DcTa-sa) and poly(DcTa-da) showed outstanding surface properties with very low surface free energy values (22.91 and 22.84 mJ m⁻²). These results highlight the utility of smart and sustainable benzoxazine chemistry and offer a facile and green synthetic approach to access hydrogen bonding-rich bio-based benzoxazine resins with many attractive properties.

This work reports the mesoscale artificial synthesis of a conjugated microporous polymer, CMP-1, using a hybrid coarse-grained methodology. Whilst using a coarse grain approach does give a lower density and surface area when compared to the all-atom equivalent, this allowed a simulation cell volume scale-up of up to 64 times, and an overall speed-up factor of 44% when compared to the all-atom equivalent.

Inspired by the host–guest recognition of crown ethers, the current era is evolving around the graphene-crown-based atomically thin membranes that will profoundly impact diverse fields of science and engineering. Using extensive MD simulations and DFT calculations, we investigate the binding affinities of graphene-embedded 18-crown-6, 16-crown-5, and 14-crown-4 for Li⁺, Na⁺, K⁺, Mg²⁺, and Ca²⁺ metal ions. We highlight that the binding preference of these membranes depends not only on the size of the crown ether cavity but also on the stability of the hydration shell of binding ions, as demonstrated by the hydration-induced energy transfer barrier. The diverse transport behavior of these membranes is attributed to ion transport over a free energy barrier raised from ionic dehydration. Results designate that the deformation of the hydration shell is a necessary condition for the adsorption of metal ions within crown ether pores, which controls the selectivity of the membrane for particular metal ions. The findings from microstructure analysis about the ion location and pore occupancy reveal how sub-nanopores of graphene-crown membranes are capable of distinguishing ions of similar characteristics. The observed ion dehydration and kinetic behavior are sensitive to pore size and the chemical environment lining the pore, similar to those observed with biological ion channels.

PqsD is an anthraniloyl-CoA anthraniloyltransferase involved in the synthesis of the secondary metabolites essential to the formation of Pseudomonas quinolone signal (PQS) inducer molecules. Its main substrate is anthraniloyl-coenzyme A (ACoA) but it can accept malonyl-CoA as secondary substrate. Suppression of PqsD activity has been connected to the inhibition of biofilm formation and can also be a good target for dual inhibition, when combined with PqsR inhibition. Here we describe the validation and application of an in silico methodology to find new compounds to inhibit PqsD. Using molecular docking and structure-based virtual screening protocols, five databases of compounds were screened (FDA approved subset of the ZINC database, Chimiothèque Nationale, Mu.Ta.Lig. Virtual Chemotheca, Interbioscreen (IBS), and Comprehensive Marine Natural Products Database (CMNPD)), representing a total of 221 146 molecules. The top five compounds of each database were selected to be further analysed using molecular dynamics simulations. Binding affinity was validated using free energy calculations, enabling the selection and characterization of eight compounds for future studies aiming to develop new quorum sensing inhibitors.

The novel coronavirus COVID-19 was first reported in Wuhan, China, in December 2019 and rapidly spread to the rest of the world, with the WHO declaring a global pandemic in March 2020. Rapid mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have challenged its diagnosis and treatments. Reverse transcription-polymerase chain reaction (RT-PCR) tests are widely used for the diagnosis of COVID-19; however, they present several drawbacks including high cost, long turnaround time, and need for sophisticated lab infrastructure and trained technical personnel. Lateral flow tests based on antigen sensing are an interesting alternative since they offer rapid (15–30 min) and low-cost analysis, although their low sensitivity has led to several adopted tests being withdrawn from the market. Henceforth, the development of detection methods which are fast, robust, reliable, cost-effective, easy to use and portable is indispensable to prevent community transmission of COVID-19. We have reviewed two different emerging colloidal-based methodologies, (a) functionalized gold nanoparticles (functionalized AuNPs) and (b) molecularly imprinted polymers (MIPs), for fast, highly specific, and reliable identification of SARS-CoV-2. Different modifications of AuNPs with antibodies, antigens and nucleoproteins and their various assays including colorimetric, electrochemical, localized surface plasmon resonance (LSPR) and lateral flow immunoassays are discussed. In contrast, with MIP-based sensors, various antigen proteins and virus particles can be imprinted within the polymeric nanoplatform and hence can be detected with various readout techniques. The operating characteristics of these two emerging diagnostic platforms were critically reviewed and compared against each other.

The development of dry adhesive pads (DAPs) is essential to prevent wafer detachment from high-speed wafer-transfer robot arms. However, polydimethylsiloxane (PDMS)-based DAPs, which are insulating elastomers, generate residual charges inside DAPs. These cause charge accumulation and electrostatic interactions between the DAP and the wafer interface. Furthermore, at a high processing temperature of >300 °C, the adhesive and mechanical strengths of conventional DAPs are degraded because of their low thermal and mechanical stability. In this study, we developed bio-inspired DAPs (BDAPs) with various shapes (hole, cylinder, and line patterns) and different contact areas (20, 40, and 60%) through systematic investigations to determine optimized patterns and shapes for different motions. Additionally, we fabricated a multi-walled carbon nanotube (MWCNT)/PDMS composite-based BDAP (c-BDAP), which exhibited high heat resistance and high electrical conductivity. The conductivity of c-BDAP was 6.16 × 10⁻³ S m⁻¹, and it had a weight loss of ∼4% at 300 °C after 1 h. Our findings can inspire the development of low-cost and high-performance c-BDAPs, which are reliable for various robot arm movements.

The sequence-to-function relationship of peptide-based catalysts remains a challenge, as even subtle modifications at the sequence level can alternate their catalytic activity. A set of linear and cyclic histidine-rich peptides was synthesized to assess the impact of amino acid disposition, cyclization, and incorporation of D-amino acids on their ability to self-assemble, coordinate Zn²⁺ ions, and show intrinsic hydrolase-like activity. Self-assembly into β-sheets was confirmed for both linear peptides and one cyclic analogue (cy-hh) by FTIR, ThT binding, CD, and AFM. Interestingly, only peptide A demonstrated efficient ester hydrolysis of p-NPA, p-NPB and p-NPO substrates, indicative of its effective Zn²⁺ coordination. Our findings highlight that increased rigidity of the peptide can hinder metal ion coordination by limiting the necessary conformational adjustments for optimal Zn²⁺ binding. These insights into the structural changes underlying the function of short peptides offer valuable knowledge for the design of metal-dependent peptide-based catalysts.