Molecular Interactions Research Articles

Challenges and opportunities for cancer stem cell-targeted immunotherapies include immune checkpoint inhibitor, cancer stem cell-dendritic cell vaccine, chimeric antigen receptor immune cells, and modified exosomes.

Cancer stem cells (CSCs) are associated with the tumor microenvironment (TME). CSCs induce tumorigenesis, tumor recurrence and progression, and resistance to standard therapies. Indeed, CSCs pose an increasing challenge to current cancer therapy due to their stemness or self-renewal properties. The molecular and cellular interactions between heterogeneous CSCs and surrounding TME components and tumor-supporting immune cells show synergistic effects toward treatment failure. In the immunosuppressive TME, CSCs express various immunoregulatory proteins, growth factors, metabolites and cytokines, and also produce exosomes, a type of extracellular vesicles, to protect themselves from host immune surveillance. Among these, the identification and application of CSC-derived exosomes could be considered for the development of therapeutic approaches to eliminate CSCs or cancer, in addition to targeting the modulators that remodel the composition of the TME, as reviewed in this study. Here, we introduce the role of CSCs and how their interaction with TME complicates immunotherapies, and then present the CSC-based immunotherapy and the limitation of these therapies. We describe the biology and role of tumor/CSC-derived exosomes that induce immune suppression in the TME, and finally, introduce their potentials for the development of CSC-based targeted immunotherapy in the future.

Unravelling the effect of molecular interactions on macroscale properties in Sustainion anion exchange membrane (AEM) under hydrated conditions using MD simulations

Sustainion is an anion exchange water electrolyser membrane that has exhibited a scalable performance. In this work, we present a molecular model for the Sustainion membrane incorporating functionalization of the polymer in order to better mimic experimental conditions. Here in, we present a comprehensive exploration of its structural and transport properties like density, diffusivity and conductivity at various operating hydration levels using molecular dynamics simulations. The density exhibits a non-monotonic trend while the diffusivity showcases a non-linear behavior with hydration. Furthermore, diffusion exhibits an Arrhenius-like dependence on temperature with the activation energies exhibiting a non-monotonic relationship akin to the density. It is concluded that the afore-mentioned properties of the Sustainion membrane are due to the counteracting influence of the enhancement in coordination number, and a reduction in the potentials of mean force of the different atomic pairs in the system. The effect of added salt on Sustainion properties is also determined and collated with experiments. Based on comparison with experiment, we deduce that vehicular diffusion is the predominant mechanism in the diffusion of the chloride ion, while it contributes approximately 15% to the diffusivity of the hydroxide ion.

Blown film of PLA for packaging with green tea and fish industrial residues: an insight on their properties

The use of food waste on the production of packaging can be seen as a promising strategy to cost reduction and new properties. Moreover, packaging, besides food physical protection, should establish a barrier to light and oxygen together with antioxidant and antibacterial activity, to extend the shelf-life of perishable products. In this study, PLA films with the incorporation of natural additives (cold fish protein - cFG and green tea extract - GTE) were successfully produced by blown film extrusion. While PLA exhibits favorable water vapor barrier properties due to its hydrophobic nature, a significant drawback in terms of high oxygen permeability. Although the cFG and GTE incorporation into the PLA matrix decreased the water vapor barrier and mechanical properties, it improves the oxygen barrier along with wettability and antioxidant activity. Moreover, GTE polyphenol compounds seem to improve molecular interaction between the PLA and cFG particles by establishing a better dispersion with enhanced compatibility. These results exhibit the benefits of adding cFG and GTE to a PLA matrix to produce an active film with reliable properties for food packaging.

In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Simulation Studies of Nucleoside Analogs for Drug Discovery- A Mini Review.

Nucleoside analogs have been widely used as antiviral, antitumor, and antiparasitic agents due to their ability to inhibit nucleic acid synthesis. Adenosine, cytidine, guanosine, thymidine and uridine analogs such as didanosine, vidarabine, remdesivir, gemcitabine, lamivudine, acyclovir, abacavir, zidovusine, stavudine, and idoxuridine showed remarkable anticancer and antiviral activities. In our previously published articles, our main intention was to develop newer generation nucleoside analogs with acylation-induced modification of the hydroxyl group and showcase their biological potencies. In the process of developing nucleoside analogs, in silico studies play an important role and provide a scientific background for biological data. Molecular interactions between drugs and receptors followed by assessment of their stability in physiological environments, help to optimize the drug development process and minimize the burden of unwanted synthesis. Computational approaches, such as DFT, FMO, MEP, ADMET prediction, PASS prediction, POM analysis, molecular docking, and molecular dynamics simulation, are the most popular tools to culminate all preclinical study data and deliver a molecule with maximum bioactivity and minimum toxicity. Although clinical drug trials are crucial for providing dosage recommendations, they can only indirectly provide mechanistic information through researchers for pathological, physiological, and pharmacological determinants. As a result, in silico approaches are increasingly used in drug discovery and development to provide mechanistic information of clinical value. This article portrays the current status of these methods and highlights some remarkable contributions to the development of nucleoside analogs with optimized bioactivity.

Quantifying and Decoupling Molecular Interactions of Ionic Liquids with Gold Electrodes.

This work combined gold colloid probe atomic force microscopy (AFM) with a quartz crystal microbalance (QCM) to accurately quantify the molecular interactions of fluorine-free phosphonium-based ionic liquids (ILs) with gold electrode surfaces. First, the interactions of ILs with the gold electrode per unit area (, N/m2) were obtained via the force-distance curves measured by gold probe AFM. Second, a QCM was employed to detect the IL amount to acquire the equilibrium number of IL molecules adsorbed onto the gold electrode per unit area (NIL, Num/m2). Finally, the quantified molecular interactions of ILs with the gold electrode (F0, nN/Num) were estimated. F0 is closely related to the IL composition, in which the IL with the same anion but a longer phosphonium cation exhibits a stronger molecular interaction. The changes in the quantified interactions of gold with different ILs are consistent with the interactions predicted by the extended Derjaguin-Landau-Verwey-Overbeek theory, and the van der Waals interaction was identified as the major contribution of the overall interaction. The quantified molecular interaction is expected to enable the direct experimental-derived interaction parameters for molecular simulations and provide the virtual design of novel ILs for energy storage applications.

Revealing the Effect of Stereocontrol on Intermolecular Interactions between Abiotic, Sequence-Defined Polyurethanes and a Ligand.

The development of precision polymer synthesis has facilitated access to a diverse library of abiotic structures wherein chiral monomers are positioned at specific locations within macromolecular chains. These structures are anticipated to exhibit folding characteristics similar to those of biotic macromolecules and possess comparable functionalities. However, the extensive sequence space and numerous variables make selecting a sequence with the desired function challenging. Therefore, revealing sequence-function dependencies and developing practical tools are necessary to analyze their conformations and molecular interactions. In this study, we investigate the effect of stereochemistry, which dictates the spatial location of backbone and pendant groups, on the interaction between sequence-defined oligourethanes and bisphenol A ligands. Various methods are explored to analyze the receptor-like properties of model oligomers and the ligand. The accuracy of molecular dynamics simulations and experimental techniques is assessed to uncover the impact of discrete changes in stereochemical arrangements on the structures of the resulting complexes and their binding strengths. Detailed computational investigations providing atomistic details show that the formed complexes demonstrate significant structural diversity depending on the sequence of stereocenters, thus affecting the oligomer-ligand binding strength. Among the tested techniques, the fluorescence spectroscopy data, fitted to the Stern-Volmer equation, are consistently aligned with the calculations, thus validating the developed simulation methodology. The developed methodology opens a way to engineer the structure of sequence-defined oligomers with receptor-like functionality to explore their practical applications, e.g., as sensory materials.

Sex gaps and age differences in the structure of academic cyberloafing from early to middle adolescence: A network analysis.

Academic cyberloafing refers to students' engagement in non-learning-related online activities during online courses, which can negatively affect their academic performance. Prior studies investigated cyberloafing primarily in the workplace, neglecting core behaviors and interactions among academic cyberloafing in educational contexts. This study employed network analysis to capture academic cyberloafing as an interactive behavior network to explore the core behavioral patterns of academic cyberloafing and the interactions between these behaviors. A total of 3537 adolescents (Mage = 12.49; 53.7% boys and 46.3% girls) in China were included in this study. The findings indicated that "seeking gossip news" and "watching short videos" are central behaviors. Among boys, "browsing nonacademic web pages" and "watching short videos" are central behaviors; "seeking gossip news" is the most central behavior among girls. Furthermore, in early adolescence, central behaviors encompass "chatting privately" and "seeking gossip news"; in middle adolescence, central behaviors include "seeking gossip news" and "watching short videos."Additionally, the comparisons indicated that academic cyberloafing networks (between boys and girls; between early and middle adolescence) show a similar structure and global strength but differ in specific academic cyberloafing associations. As adolescents of different sexes and ages engage in academic cyberloafing differently, tailored education interventions can be implemented to address unregulated cyberloafing.

Placental Transcriptome Analysis in Connection with Low Litter Birth Weight Phenotype (LBWP) Sows

It is possible to identify sub-populations of sows in every pig herd that consistently give birth to low birth weight (BW) piglets, irrespective of the litter size. A previous study from our group demonstrated that placental development is a main factor affecting the litter birth weight phenotype (LBWP) in sows, thereby impacting the BW of entire litters, but the biological and molecular pathways behind this phenomenon are largely unknown. The aim of this study was to investigate the differential gene expression in placental tissues at day 30 of gestation between low LBWP (LLBWP) vs. high LBWP (HLBWP) sows from a purebred Large White maternal line. Using mRNA sequencing, we found 45 differentially expressed genes (DEGs) in placental tissues of LLBWP and HLBWP sows. Furthermore, (GO) enrichment of upregulated DEGs predicted that there were two biological processes significantly related to cornification and regulation of cell population proliferation. To better understand the molecular interaction between cell proliferation and cornification, we conducted transcriptional factor binding site (TFBS) prediction analysis. The results indicated that a highly significant TFBS was located at the 5′ upstream of all four upregulated genes (CDSN, DSG3, KLK14, KRT17), recognized by transcription factors EGR4 and FOSL1. Our findings provide novel insight into how transcriptional regulation of two different biological processes interact in placental tissues of LLBWP sows.

Toward Bioactive Hydrogels: A Tunable Approach via Nucleic Acid-Collagen Complexation

Abstract Purpose Nucleic acid-collagen complexes (NACCs) are unique biomaterials formed by binding short, monodisperse single-stranded DNA (ssDNA) with type I collagen. These complexes spontaneously generate microfibers and nanoparticles of varying sizes, offering a versatile platform with potential applications in tissue engineering and regenerative medicine. However, the detailed mechanisms behind the nucleic acid-driven assembly of collagen fibers still need to be established. We aim to understand the relationship between microscopic structure and bulk material properties and demonstrate that NACCs can be engineered as mechanically tunable systems. Methods We present a study to test NACCs with varying molar ratios of collagen to random ssDNA oligonucleotides. Our methods encompass the assessment of molecular interactions through infrared spectroscopy and the characterization of gelation and rheological behavior. We also include phase contrast, confocal reflectance, and transmission electron microscopy to provide complementary information on the 3D structural organization of the hydrogels. Results We report that adding DNA oligonucleotides within collagen robustly reinforces and rearranges the hydrogel network and accelerates gelation by triggering rapid fiber formation and spontaneous self-assembly. The elasticity of NACC hydrogels can be tailored according to the collagen-to-DNA molar ratio, ssDNA length, and collagen species. Conclusion Our findings hold significant implications for the design of mechanically tunable DNA-based hydrogel systems. The ability to manipulate hydrogel stiffness by tailoring DNA content and collagen concentration offers new avenues for fine tuning material properties, enhancing the versatility of bioactive hydrogels in diverse biomedical applications. Lay Summary This work is an example of forming fibers and gels with tunable elasticity that stems from the complexation of short-length nucleic acids (on the order of size of aptamers) and collagen, which can be potentially extended to a variety of functionalized hydrogel designs and tailored biomedical applications. Incorporating DNA induces mechanical changes in NACCs. Graphical Abstract

Identification of DPP-IV inhibitory peptides derived from buffalo colostrum: Mining through bioinformatics, in silico and in vitro approaches.

Bioactive peptides derived from foods provide physiological health benefits beyond nutrition. This study focused on profiling small peptide inhibitors against two key serine proteases, dipeptidyl peptidase-IV (DPP-IV) and prolyl oligopeptidase (POP). DPP-IV is a well-known protein involved in diverse pathways regulating inflammation, renal, cardiovascular physiology, and glucose homeostasis. POP is yet another key target protein for neurodegenerative disorders. The study evaluated peptide libraries of buffalo colostrum whey and fat globule membrane proteins derived from pepsin and pepsin-pancreatin digestion through in silico web tools and structure-based analysis by molecular docking and binding free-energy estimation, followed by in vitro assay for DPP-IV inhibition for the lead peptides. The bioinformatic study indicated 49 peptides presented motifs with DPP-IV inhibition while 5 peptides with sequences for POP inhibition. In the molecular docking interactions study, 22 peptides interacted with active site residues of DPP-IV and 3 peptides with that of POP. The synthesized peptides, SFVSEVPEL and LTFQHNF inhibited DPP-IV in vitro with an IC50 of 193.5 μM and 1.782 mM, respectively. The study revealed the key residues for inhibition of DPP-IV and POP thus affirming the DPP-IV inhibitory potential of milk-derived peptides.

Novel Multifunctional Meta-Surface Plasmon Resonance Chip Microplate for High-Throughput Molecular Screening.

The utilization of surface plasmon resonance (SPR) sensors for real-time label-free molecular interaction analysis is already being employed in the fields of in vitro diagnostics and biomedicine. However, the widespread application of SPR technology is hindered by its limited detection throughput and high cost. To address this issue, our study introduces a novel multifunctional MetaSPR high-throughput microplate biosensor featuring 3D nanocup microarrays, aiming to achieve high-throughput screening at a reduced cost and with enhanced speed. Different types of MetaSPR sensors and analytical detection methods have been developed for accurate subtype identification, epitope binding, affinity determination, antibody collocation, and other applications that have greatly promoted the screening and analysis of early antibody drugs. The MetaSPR platform combined with nano-enhanced particles amplified the detection signal and improved the detection sensitivity, making it more convenient, sensitive, and efficient than traditional ELISA. Our findings demonstrated that the MetaSPR biosensor is a new practical technology detection platform that can improve the efficiency of biomolecular interaction studies with unlimited potential for new drug development. This article is protected by copyright. All rights reserved.

In-silico analysis of ribosome inactivating protein (RIP) of the Cucurbitaceae family.

Ribosome-inactivating proteins (RIPs) are highly active N-glycosidases that depurinate both bacterial and eukaryotic rRNAs, halting protein synthesis during translation. Found in a diverse spectrum of plant species and tissues, RIPs possess antifungal, antibacterial, antiviral, and insecticidal properties linked to plant defense. In this study, we investigated the physiochemical properties of RIP peptides from the Cucurbitaceae family through bioinformatics approaches. Molecular weight, isoelectric point, aliphatic index, extinction coefficient, and secondary structures were analyzed, revealing their hydrophobic nature. The novelty of this work lies in the comprehensive examination of RIPs from the Cucurbitaceae family and their potential therapeutic applications. The study also elucidated the binding interactions of Cucurbitaceae RIPs with key biological targets, including Interleukin-6 (IL-6). Strong hydrogen bond interactions between RIPs and these targets suggest potential for innovative insilico drug design and therapeutic applications, particularly in cancer treatment. Comprehensive analysis of bond lengths using Ligpolt + software provides insights for optimizing molecular interactions, offering a valuable tool for drug design and structural biology studies.

Multimodal imbalanced‐data fault diagnosis method based on a dual‐branch interactive fusion network

AbstractBearing‐fault diagnosis in rotating machinery is essential for ensuring the safety and reliability of mechanical systems. However, under complicated working conditions, the number of normal mechanical equipment samples can far exceed the number of faulty ones. When the data are so imbalanced, data fault diagnosis cannot be easily conducted using conventional deep learning methods. This study proposes a fault diagnosis method based on a dual‐branch interactive fusion network, which improves the accuracy and stability of bearing‐fault diagnosis. First, a dual‐branch feature representation network comprising an iterative attention‐feature fusion residual neural network and a long short‐term memory network is designed for extracting different modal features. Meanwhile, intermodal fusion of the extracted features is performed through multilayer perception. Based on the cost‐sensitive regularization loss, a new joint loss function is then designed for network training. Finally, the effectiveness of the proposed method is verified through comparative experiments, visualization analyses, ablation experiments, and generalization performance experiments.

Single-sample image-fusion upsampling of fluorescence lifetime images.

Fluorescence lifetime imaging microscopy (FLIM) provides detailed information about molecular interactions and biological processes. A major bottleneck for FLIM is image resolution at high acquisition speeds due to the engineering and signal-processing limitations of time-resolved imaging technology. Here, we present single-sample image-fusion upsampling, a data-fusion approach to computational FLIM super-resolution that combines measurements from a low-resolution time-resolved detector (that measures photon arrival time) and a high-resolution camera (that measures intensity only). To solve this otherwise ill-posed inverse retrieval problem, we introduce statistically informed priors that encode local and global correlations between the two "single-sample" measurements. This bypasses the risk of out-of-distribution hallucination as in traditional data-driven approaches and delivers enhanced images compared, for example, to standard bilinear interpolation. The general approach laid out by single-sample image-fusion upsampling can be applied to other image super-resolution problems where two different datasets are available.

Adsorptive removal of synthetic dye from its aqueous solution by using chitosan-bentonite composite: DFT and experimental studies

AbstractThis research investigates the adsorption efficiency of a chitosan-bentonite (Ch–B) composite in removing methyl orange (MO), a common textile dye, from aqueous solutions. The study integrates experimental and theoretical analyses, employing density functional theory (DFT) to gain insights into the molecular interactions between the composite material and MO molecules. The Ch–B composite was characterized using various techniques, including FT-IR spectroscopy, XRD, and SEM–EDX. The experimental results indicate that the Ch–B composite exhibits a high adsorption capacity for MO, with optimal conditions identified for efficient removal. The Langmuir model was found to best fit the experimental data and the adsorption capacity was 117 mg g−1. Adsorption thermodynamics showed that the adsorption process was spontaneous, feasible, and exothermic. DFT calculation results are correlated with experimental findings to confirm theoretical predictions and improve the overall understanding of the adsorption process. Electronic structure calculations reveal the nature of the interactions between the Ch–B composite and MO molecules, including hydrogen bonds and electrostatic forces.

Spider-silk-inspired strong and tough hydrogel fibers with anti-freezing and water retention properties

Ideal hydrogel fibers with high toughness and environmental tolerance are indispensable for their long-term application in flexible electronics as actuating and sensing elements. However, current hydrogel fibers exhibit poor mechanical properties and environmental instability due to their intrinsically weak molecular (chain) interactions. Inspired by the multilevel adjustment of spider silk network structure by ions, bionic hydrogel fibers with elaborated ionic crosslinking and crystalline domains are constructed. Bionic hydrogel fibers show a toughness of 162.25 ± 21.99 megajoules per cubic meter, comparable to that of spider silks. The demonstrated bionic structural engineering strategy can be generalized to other polymers and inorganic salts for fabricating hydrogel fibers with broadly tunable mechanical properties. In addition, the introduction of inorganic salt/glycerol/water ternary solvent during constructing bionic structures endows hydrogel fibers with anti-freezing, water retention, and self-regeneration properties. This work provides ideas to fabricate hydrogel fibers with high mechanical properties and stability for flexible electronics.

AlphaLISA-Based Immunoassay for Detection of Troponin T in Serum of Patients with Acute Myocardial Infarction.

Survival and prognosis of patients with acute myocardial infarction (AMI) are highly dependent on rapid and accurate diagnosis of myocardial damage. Troponin T is the primary diagnostic biomarker and is widely used in clinical practice. Amplified luminescent proximity homogeneous assay (AlphaLISA) may provide a solution to rapidly detect a small amount of analyte through molecular interactions between special luminescent donor beads and acceptor bead. Here, a double-antibody sandwich assay was introduced into AlphaLISA for rapid detection for early diagnosis of AMI and disease staging evaluation. The performance of the assay was evaluated. The study found that the cTnT assay has a linear range of 48.66 to 20,000 ng/L with a limit of detection of 48.66 ng/L. In addition, the assay showed no cross-reactivity with other classic biomarkers of myocardial infarction and was highly reproducible with intra- and inter-batch coefficients of variation of less than 10%, notably, only 3min was taken, which is particularly suitable for clinical diagnosis. These results suggest that our method can be conveniently applied in the clinic to determine the severity of the patient's condition.

Emerging Trends in Bilosomes as Therapeutic Drug Delivery Systems

In recent years, there has been a notable surge in the utilization of stabilized bile acid liposomes, chemical conjugates, complexes, mixed micelles, and other drug delivery systems derived from bile acids, often referred to as bilosomes. The molecular structure and interactions of these amphiphilic compounds provide a distinctive and captivating subject for investigation. The enhanced stability of new generation bilosomes inside the gastrointestinal system results in the prevention of drug degradation and an improvement in mucosal penetration. These characteristics render bilosomes to be a prospective nanocarrier for pharmaceutical administration, prompting researchers to investigate their potential in other domains. This review paper discusses bilosomes that have emerged as a viable modality in the realm of drug delivery and have significant promise for use across several domains. Moreover, this underscores the need for additional investigation and advancement in order to comprehensively comprehend the prospective uses of bilosomes and their effectiveness in the field of pharmaceutical administration. This review study explores the current scholarly attention on bilosomes as prospective carriers for drug delivery. Therapeutic areas where bilosomes have shown outstanding performance in terms of drug delivery are outlined in the graphical abstract.

Long non-coding RNAs as promising targets for controlling disease vector mosquitoes.

Hematophagous female mosquitoes are important vectors of numerous devastating human diseases, posing a major public health threat. Effective prevention and control of mosquito-borne diseases rely considerably on progress in understanding the molecular mechanisms of various life activities, and accordingly, the molecules that regulate the various life activities of mosquitoes are potential targets for implementing future vector control strategies. Many long non-coding RNAs (lncRNAs) have been identified in mosquitoes and significant progress has been made in determining their functions. Here, we present a comprehensive overview of the research advances on mosquito lncRNAs, including their molecular identification, function, and interaction with other non-coding RNAs, as well as their synergistic regulatory roles in mosquito life activities. We also highlight the potential roles of competitive endogenous RNAs in mosquito growth and development, as well as in insecticide resistance and virus-host interactions. Insights into the biological functions and mechanisms of lncRNAs in mosquito life activities, viral replication, pathogenesis, and transmission will contribute to the development of novel drugs and safe vaccines.

DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.

Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.