GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit

Improved genetic screening with zygosity detection through multiplex high-resolution melting curve analysis and biochemical characterisation for G6PD deficiency

Accurate diagnosis of glucose-6-phosphate dehydrogenase (G6PD) deficiency is crucial for relapse malaria treatment using 8-aminoquinolines (primaquine and tafenoquine), which can trigger haemolytic anaemia in G6PD-deficient individuals. This is particularly important in regions where the prevalence of G6PD deficiency exceeds 3%-5%, including Southeast Asia and Thailand. While quantitative phenotypic tests can identify women with intermediate activity who may be at risk, they cannot unambiguously identify heterozygous females who require appropriate counselling. This study aimed to develop a genetic test for G6PD deficiency using high-resolution melting curve analysis, which enables zygosity identification of 15 G6PD alleles. In 557 samples collected from four locations in Thailand, the prevalence of G6PD deficiency based on indirect enzyme assay was 6.10%, with 8.08% exhibiting intermediate deficiency. The developed high-resolution melting assays demonstrated excellent performance, achieving 100% sensitivity and specificity in detecting G6PD alleles compared with Sanger sequencing. Genotypic variations were observed across four geographic locations, with the combination of c.1311C>T and c.1365-13T>C being the most common genotype. Compound mutations, notably G6PD Viangchan (c.871G>A, c.1311C>T and c.1365-13T>C), accounted for 15.26% of detected mutations. The high-resolution melting assays also identified the double mutation G6PD Chinese-4 + Canton and G6PD Radlowo, a variant found for the first time in Thailand. Biochemical and structural characterisation revealed that these variants significantly reduced catalytic activity by destabilising protein structure, particularly in the case of the Radlowo mutation. The refinement of these high-resolution melting assays presents a highly accurate and high-throughput platform that can improve patient care by enabling precise diagnosis, supporting genetic counselling and guiding public health efforts to manage G6PD deficiency-especially crucial in malaria-endemic regions where 8-aminoquinoline therapies pose a risk to deficient individuals.

Title: Identification of Redox State Based on the Difference in Solvation Dynamics

Oxidation-reduction (Redox) reactions are crucial for many biological processes, yet there is no method available to evaluate redox states in a non-invasive, continuous manner. Here we introduce a novel approach to distinguish between reduced and oxidized states of glutathione (GSH and GSSG, respectively) using aquaphotomics near-infrared (NIR) spectroscopy and multivariate analysis. We identified clear differences in NIR spectra reflecting not only glutathione itself, but different redox states of glutathione based on the spectral features of water molecular conformations interacting with the reaction site. Molecular dynamic simulations also revealed the difference in water molecule coordination and hydration numbers around the reaction site. This approach not only sheds light on the significance of water molecules in redox reactions but also enables non-destructive, continuous assessment of redox states, with potential applications for bioreactor optimization.

Gemini surfactant stabilized zein nanoparticles: Preparation, characterization, interaction mechanism, and antibacterial activity

To enhance the physicochemical properties of zein nanoparticles, zein complexes with two Gemini surfactants (12-3-12 and 12-4-12) were prepared using the anti-solvent method and investigated the physicochemical properties, formation mechanism and antibacterial activity. Results indicated that the optimal mass ratio between zein and Gemini surfactants was at 1:1, and the incorporation of Gemini surfactants significantly improved the surface properties of zein, reducing its surface hydrophobicity and surface tension, thereby enhancing its dispersion in aqueous media. Fluorescence spectroscopy and molecular docking experiments further elucidated the interaction mechanisms between zein and Gemini surfactant, revealing a spontaneous binding process, mainly driven by hydrophobic and hydrogen interaction, and a strong binding affinity of 12-4-12 with zein. Additionally, the zein/Gemini surfactant complexes exhibited significant antibacterial activity against Staphylococcus aureus, with the zein/12-4-12 complex showing particularly prominent inhibitory effects. Therefore, this research not only provides a theoretical foundation for the construction of Gemini surfactant stabilized zein nanoparticles but also points the way for the subsequent embedding of bacteriostatic agents to achieve synergistic antibacterial effects.

Structural Insights into the Mechanical Behavior of Large-Area 2D Covalent Organic Framework Nanofilms

Two-dimensional covalent organic frameworks (2D COFs) are periodic, permanently porous, lightweight solids with remarkable structural modularity, enabling precise control over their properties. As thin films, they have shown promising applications in chemical separations and organic electronics, making it crucial to understand their stability under mechanical stress. Here, we investigate how two different chemical linkages commonly used for 2D COFs, specifically imine and enamine, influence the mechanical properties of nanoscale thick films. Centimeter-scale 2D COF films with a thickness below 100 nm were synthesized by a condensation reaction at a liquid-liquid interface and subsequently transferred onto patterned substrates for mechanical testing. By employing a custom-made nanotensile testing platform, we achieved a comprehensive mechanical characterization of freestanding 2D COF films over a large area (0.5 mm2), a size relevant for device applications. The enamine-linked COF exhibits a higher Young's modulus and tensile strength but a lower fracture strain compared to the imine-linked COF, a difference attributed to the tightly stacked structure of the enamine-linked COF, as confirmed by molecular dynamics simulations. This distinct mechanical behavior reveals a fundamental relationship between the linkage chemistry of 2D COF and their mechanical properties, providing valuable insights that can drive the development of strong and durable thin-film devices based on 2D COFs.

Molecular dynamics simulation and validation of spiramycin extraction using the thermosensitive polymer NPE-108/water aqueous two-phase system

Spiramycin is a 16-membered macrolide antibiotic widely used in the medical field. Industrial extraction of antibiotics from fermentation broth using organic solvents raises various environmental and health concerns. In this study, a thermosensitive polymer, NPE-108, was used to construct an aqueous two-phase system (ATPS) for the extraction of spiramycin. We used Gromacs software to develop a molecular dynamics simulation model to reveal the distribution mechanism of spiramycin molecules in the NPE-108/water ATPS from a microscopic perspective. Additionally, we examined the effects of volume ratio, temperature, and pH on extraction through experimentation. Under the optimal conditions for forward extraction, the distribution coefficient and extraction efficiency were 25.3 and 89.9%, respectively. Under the optimal conditions for back extraction, the distribution coefficient and extraction efficiency were 6.8 and 81.5%, respectively. Optimization of crystallization conditions resulted in a crystal yield of 88.1% and a purity of 98.4%. The content of both spiramycin components and impurities in the crystalline sample met the requirements of the European Pharmacopeia. The results of this study provided insights into molecular interactions and the extraction process, offering a more environmentally friendly and economically viable alternative for industrial spiramycin production.

Exploring Metformin's Therapeutic Potential for Alzheimer's Disease: An In-Silico Perspective Using Well-Tempered Funnel Metadynamics

Alzheimer's disease (AD), often referred to as the "diabetes of the brain", is intricately linked to insulin resistance. Metformin, a first-line antidiabetic drug, has been anticipated as a potential treatment for AD and is currently undergoing phase 3 clinical trials. The potential success of metformin in treating AD could herald a new era in the management of this debilitating disease, providing hope for millions of people affected worldwide. Despite this fact, the precise molecular mechanisms underlying the therapeutic effects of metformin on AD remain poorly understood. To pursue this, in this present work, we implement a comprehensive computational approach combining classical molecular dynamics (MD) simulations and the advanced enhanced sampling technique funnel metadynamics (FM) to explore the dynamics and affinity of metformin and acetylcholinesterase (AChE), a novel target for AD. The MD and FM simulations suggest that metformin induces significant configurational changes within the AChE, resulting in weak and nonspecific binding. Furthermore, the presence of metformin alters the conformational landscape of AChE causing the emergence of metastable states and less rigid binding patterns. The binding energies for the metformin-AChE complex are -4.89 ± 1.2 kcal/mol and -1.68 ± 0.2 kcal/mol, as estimated through the molecular mechanics Poisson-Boltzmann surface area (MMPBSA) and FM approaches, respectively. To elucidate the binding energy relevance calculated by MMPBSA and FM approach with experimental inhibitory potency, ΔGexp is calculated using IC50 value reported in prior experimental studies. ΔGexp is estimated to be -3.59 kcal/mol. A comparison of these binding energy values with different methods highlights the moderate inhibitory potency of metformin toward AChE. This work provides molecular-level insights emphasizing the dynamic configurational changes induced by metformin within AChE and underscores its translational potential in the repurposing of AD.

Pharmacological and Computational Investigations of Isosteviol 16-oxime for Attenuating Streptozotocin-induced Diabetic Neuroinflammation utilizing rat as Animal Model

Diabetic neuropathy (DN) is microvascular issues caused by diabetes mellitus (DM) that damages peripheral nerve system. DN-induced pain progression and persistence occur due to many risk factors, including as increased TNF-α, NF-κB, and COX-2 levels. It was investigated whether Isosteviol 16-oxime (IO) could protect against DM-induced neuropathic pain. For this purpose streptozotocin-induced diabetic rat model was employed. After four weeks of streptozotocin injection, IO was given till the sixth week. On days 28, 31, 35, 38, and 42, behavioral assessments were done before and after Streptozotocin administration. After six weeks of streptozotocin treatment, rats were sacrificed, and spinal cord and sciatic nerve samples were taken for molecular analysis. The interaction kinetics and binding affinities of IO with TNF-α, NF-κB, and COX-2 targets were studied using computational methods. IO intervention significantly (P < 0.001) reduced mechanical allodynia and thermal hyperalgesia. The treatment of IO led to increased GSH, GST, and CAT concentrations in the spinal cord and sciatic nerve, while reducing LPO levels (P < 0.001). IHC and Nissl staining showed that IO successfully reduced DN-induced pathological changes. IO also down regulated the expression of inflammatory mediators TNF-α, NF-κB, and COX-2, suggesting its potential as a neuroprotective drug. In comparison to pregabalin, IO demonstrated enhanced antinociceptive properties and diminished hyperalgesic effects. Consequently, IO exhibits a more pronounced reduction in pain perception and inflammation. Our investigation found that IO may protect against DM-induced neuroinflammation by suppressing cytokines and increasing antioxidant levels. More research is needed to determine the exact mechanism of IO in neuroprotection and pain reduction.

Rapid Access to Small Molecule Conformational Ensembles in Organic Solvents Enabled by Graph Neural Network-Based Implicit Solvent Model

Understanding and manipulating the conformational behavior of a molecule in different solvent environments is of great interest in the fields of drug discovery and organic synthesis. Molecular dynamics (MD) simulations with solvent molecules explicitly present are the gold standard to compute such conformational ensembles (within the accuracy of the underlying force field), complementing experimental findings and supporting their interpretation. However, conventional methods often face challenges related to computational cost (explicit solvent) or accuracy (implicit solvent). Here, we showcase how our graph neural network (GNN)-based implicit solvent (GNNIS) approach can be used to rapidly compute small molecule conformational ensembles in 39 common organic solvents reproducing explicit-solvent simulations with high accuracy. We validate this approach using nuclear magnetic resonance (NMR) measurements, thus identifying the conformers contributing most to the experimental observable. The method allows the time required to accurately predict conformational ensembles to be reduced from days to minutes while achieving results within one kBT of the experimental values.

Unveiling Dynamic Hotspots in Protein-Ligand Binding: Accelerating Target and Drug Discovery Approaches

Computational methods have transformed target and drug discovery, significantly accelerating the identification of biological targets and lead compounds. Despite its limitations, in silico molecular docking represents a foundational tool. Molecular Dynamics (MD) simulations, employing accurate force fields, provide near-realistic insights into a compound's behavior within a biological target. However, docking and MD predictions may be unreliable without precise knowledge of the target binding site. Through MD simulations, we investigated 100 co-crystal structures of biological targets complexed with active compounds, identifying key structural and energy dynamic features that govern target-ligand interactions. Our analysis provides a detailed quantitative description of these parameters, offering critical validation for improving the predictive reliability of docking and MD simulations. This work provides a robust framework for refining early-stage drug discovery and target identification.

Assessing Nonbonded Aggregates Populations: Application to the Concentration-Dependent IR O-H Band of Phenol

In this work, we present two alternative computational strategies to determine the populations of nonbonded aggregates. One approach extracts these populations from molecular dynamics (MD) simulations, while the other employs quantum mechanical partition functions for the most relevant minima of the multimolecular potential energy surfaces (PESs), identified by automated conformational sampling. In both cases, we adopt a common graph-theory-based framework, introduced in this work, for identifying aggregate conformations, which enables a consistent comparative assessment of both methodologies and provides insight into the underlying approximations. We apply both strategies to investigate phenol aggregates, up to the tetramer, at different concentrations in phenol/carbon tetrachloride mixtures. Subsequently, we simulate the concentration-dependent OH stretching IR region by averaging the harmonic Infrared (IR) spectra of aggregates using the populations predicted by each strategy. Our results indicate that the populations extracted from MD trajectories yield OH stretching signals that closely follow the experimental trends, outperforming the spectra from populations obtained by systematic conformational searches. Such a better performance of MD is attributed to a better description of the entropic contributions. Moreover, the proposed protocol not only successfully addresses a very challenging problem but also offers a benchmark to assess the accuracy of the intermolecular force fields.

Tuning partial charges of alkyl alcohols to improve simulated fluid properties

Standard simulation interaction parameters sometimes predict liquid properties at variance with experiment, especially for polar liquids. In this work, we systematically scaled the partial charges of three alkyl alcohols to evaluate whether adjusting the partial charges, and thus the electrostatic interactions, can improve agreement with experimental values of key liquid properties, including the dielectric constant, vapor pressure, density, and self-diffusion coefficient. Changing the partial charges also affects liquid structures, which are evaluated through a hydrogen bond analysis. We found that modest adjustment factors applied to all partial charges improve values for computed properties, but too large an adjustment causes string-like aggregation of molecular dipoles and inhibits system dynamics.

Electron transfer engineering of artificially designed cell factory for complete biosynthesis of steroids

Biosynthesis of steroids by artificially designed cell factories often involves numerous nicotinamide adenine dinucleotide phosphate (NADPH)-dependent enzymes that mediate electron transfer reactions. However, the unclear mechanisms of electron transfer from regeneration to the final delivery to the NADPH-dependent active centers limit systematically engineering electron transfer to improve steroids production. Here, we elucidate the electron transfer mechanisms of NADPH-dependent enzymes for systematically engineer electron transfer of Saccharomyces cerevisiae, including step-by-step engineering the electron transfer residues of 7-Dehydrocholesterol reductase (DHCR7) and P450 sterol side chain cleaving enzyme (P450scc), electron transfer components for directing carbon flux, and NADPH regeneration pathways, for high-level production of the cholesterol (1.78 g/L) and pregnenolone (0.83 g/L). The electron transfer engineering (ETE) process makes the electron transfer chains shorter and more stable which significantly accelerates deprotonation and proton coupled electron transfer process. This study underscores the significance of ETE strategies in steroids biosynthesis and expands synthetic biology approaches.

CO2 and SO2 Capture by Cryptophane-111 Porous Liquid: Insights from Molecular Dynamics Simulations and Computational Chemistry

A computational study of the encapsulation of a gaseous mixture of CO2 and SO2 in a Type II porous liquid is performed under different conditions. The system is composed of cryptophane-111 molecules dispersed in dichloromethane, and it is described using classic molecular dynamics at atomistic resolution. Gaseous CO2 tends to almost fully occupy cryptophane-111's cavities during the first phases of simulation, and, afterwards, it is surpassed by SO2's tendency for occupation. Calculations are performed at five different temperatures in the range of 273 K-310 K, finding a positive correlation between SO2 adsorption and temperature. An evaluation of the radial distribution function of SO2 and CO2 with respect to cryptophane-111 is employed to quantify the number of captured molecules, and an energy study using Density Functional Theory methods is also performed to evaluate the relative stability of the two gases inside the porous liquid.

Linker Design Principles for the Precision Targeting of Oncogenic G-Quadruplex DNA with G4-Ligand-Conjugated Oligonucleotides

G-quadruplex (G4) DNA structures are noncanonical secondary structures found in key regulatory regions of the genome, including oncogenic promoters and telomeres. Small molecules, known as G4 ligands, capable of stabilizing G4s hold promise as chemical probes and therapeutic agents. Nevertheless, achieving precise specificity for individual G4 structures within the human genome remains a significant challenge. To address this, we expand upon G4-ligand-conjugated oligonucleotides (GL-Os), a modular platform combining the stabilizing properties of G4-ligands with the sequence specificity of guide DNA oligonucleotides. Central to this strategy is the linker that bridges the G4 ligand and the guide oligonucleotide. In this study, we develop multiple conjugation strategies for the GL-Os that enabled a systematic investigation of the linker in both chemical composition and length, enabling a thorough assessment of their impact on targeting oncogenic G4 DNA. Biophysical, biochemical, and computational evaluations revealed GL-Os with optimized linkers that exhibited enhanced binding to target G4s, even under thermal or structural stress. Notably, longer linkers broadened the range of targetable sequences without introducing steric hindrance, thereby enhancing the platform's applicability across diverse genomic contexts. These findings establish GL-Os as a robust and versatile tool for the selective targeting of individual G4s. By facilitating precise investigations of G4 biology, this work provides a foundation for advancing G4-targeted therapeutic strategies and exploring their role in disease contexts.

Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation

Background/Objectives: Montelukast (MLK), a leukotriene receptor antagonist, has been associated with neuropsychiatric side effects. This study aimed to rationally modify MLK's structure to reduce these risks by optimizing its interactions with dopamine D2 (DRD2) and serotonin 5-HT1A receptors using computational molecular simulation techniques. Methods: A library of MLK derivatives was designed and screened using structural similarity analysis, molecular docking, molecular dynamics (MD) simulations, MM/PBSA binding free energy calculations, and ADME-Tox predictions. Structural similarity analysis, based on Tanimoto coefficient fingerprinting, compared MLK derivatives to known neuropsychiatric drugs. Docking was performed to assess initial receptor binding, followed by 100 ns MD simulations to evaluate binding stability. MM/PBSA calculations quantified binding affinities, while ADME-Tox profiling predicted pharmacokinetic and toxicity risks. Results: Several MLK derivatives showed enhanced DRD2 and 5-HT1A binding. MLK_MOD-42 and MLK_MOD-43 emerged as the most promising candidates, exhibiting MM/PBSA binding free energies of -31.92 ± 2.54 kcal/mol and -27.37 ± 2.22 kcal/mol for DRD2 and -30.22 ± 2.29 kcal/mol and -28.19 ± 2.14 kcal/mol for 5-HT1A, respectively. Structural similarity analysis confirmed that these derivatives share key pharmacophoric features with atypical antipsychotics and anxiolytics. However, off-target interactions were not assessed, which may influence their overall safety profile. ADME-Tox analysis predicted improved oral bioavailability and lower neurotoxicity risks. Conclusions: MLK_MOD-42 and MLK_MOD-43 exhibit optimized receptor interactions and enhanced pharmacokinetics, suggesting potential neuropsychiatric applications. However, their safety and efficacy remain to be validated through in vitro and in vivo studies. Until such validation is performed, these derivatives should be considered as promising candidates with optimized receptor binding rather than confirmed safer alternatives.

3D meshwork architecture of the outer coat protein CotE: implications for bacterial endospore sporulation and germination

Bacillus cereus, a Gram-positive aerobic bacterium commonly found in soil, food, and water, forms endospores that can withstand harsh environmental conditions. The endospores are encased in a protective spore coat consisting of multiple layers of proteins, among which, CotE serves as a crucial morphogenetic protein within the outer coat. In this study, we observed that the homotrimeric CotE protein underwent further oligomerization induced by Ca2+ and was subsequently dissociated by dipicolinic acid, a compound released from the spore core during germination. Through cryo-electron microscopy and tomography analyses of the Ca2+-induced CotE oligomer, combined with structural predictions and biochemical studies, we propose a three-dimensional meshwork organization facilitated by tryptophan-based interactions between CotE trimers. The resulting meshwork was organized in a defective diamond-like tetrahedral configuration. These insights enhance our understanding of how CotE contributes to endospore morphogenesis and germination through the rapid disassembly of these layers.

IMPORTANCE

Bacterial endospores are highly resilient structures that allow bacteria to survive extreme environmental conditions, making them a significant concern in food safety and healthcare. The protein CotE plays a critical role in forming the protective outer coat of these endospores. Our research uncovers the three-dimensional meshwork architecture of CotE and reveals how it contributes to the structural integrity and rapid disassembly of endospores during germination. By understanding CotE's unique 3D structure and its interaction with other molecules, we gain valuable insights into how bacterial endospores are formed and how they can be effectively targeted for sterilization. This work not only advances our fundamental knowledge of bacterial endospore biology but also has potential applications in developing new strategies to combat bacterial contamination and improve sterilization techniques in the food and healthcare industries.

Liquid-Liquid Phase Transition in Simulated Supercooled Water Nanodroplets

Using simulations, we demonstrate how a liquid-liquid phase transition (LLPT) manifests in supercooled water nanodroplets. Selecting an interaction potential for which a LLPT occurs in the bulk liquid, we conduct simulations of supercooled water nanodroplets having between 1000 and 80000 molecules. We show that as the droplet size decreases, the Laplace pressure grows large enough to drive the droplets through the transition from the low-density to the high-density liquid phase, and that all droplets in this size range are large enough to have cores exhibiting the structure and properties of bulk water. To guide experiments, we estimate the range of values for the critical pressure of the LLPT in real water that can be observed using nanodroplets, and propose structural and dynamical measures by which the LLPT in nanodroplets can be detected.

Hexadecanoic acid analogs as potential CviR-mediated quorum sensing inhibitors in Chromobacterium violaceum: an in silico study

Chromobacterium violaceum is a Gram-negative, rod-shaped and opportunistic human pathogen. C. violaceum is resistant to various antibiotics due to the production of quorum sensing (QS)-controlled virulence factor and biofilm formation. Hence, we need to find alternative strategies to overcome the antimicrobial resistance and biofilm formation in Gram-negative bacteria. QS is a mechanism in which bacteria's ability to regulate the virulence factors and biofilm formations leads to disease progression. Previously, hexadecanoic acid was identified as a CviR-mediated quorum-sensing inhibitor. In this study, we aimed to discover potential analogs of hexadecanoic acid as a CviR-mediated quorum-sensing inhibitor against C. violaceum by using ADME/T prediction, density functional theory, molecular docking, molecular dynamics and free energy binding calculations. ADME/T properties predicted for analogs were acceptable for human oral absorption and feasibility. The highest occupied molecular orbitals and lowest unoccupied molecular orbitals gap energies predicted and found oleic acid with -0.3748 energies. Docosatrienoic acid exhibited the highest binding affinity -8.15 Kcal/mol and strong and stable interactions with the amino acid residues on the active site of the CviR protein. These compounds on MD simulations for 100 ns show strong hydrogen-bonding interactions with the protein and remain stable inside the active site. Our results suggest hexadecanoic acid analogs could serve as anti-QS and anti-biofilm molecules for treating C. violaceum infections. However, further validation and investigation of these inhibitors against CviR are needed to claim their candidacy for clinical trials.

Combining QSAR techniques, molecular docking, and molecular dynamics simulations to explore anti-tumor inhibitors targeting Focal Adhesion Kinase

Focal Adhesion Kinase (FAK) is an important target for tumor therapy and is closely related to tumor cell genesis and progression. In this paper, we selected 46 FAK inhibitors with anticancer activity in the pyrrolo pyrimidine backbone to establish 3D/2D-QSAR models to explore the relationship between inhibitory activity and molecular structure. We have established two ideal models, namely, the Topomer CoMFA model (q 2 = 0.715, r 2 = 0.984) and the Holographic Quantitative Structure-Activity Relationship (HQSAR) model (q 2 = 0.707, r 2 = 0.899). Both models demonstrate excellent external prediction capabilities.Based on the QSAR results, we designed 20 structurally modified novel compounds, which were subjected to molecular docking and molecular dynamics studies, and the results showed that the new compounds formed many robust interactions with residues within the active pocket and could maintain stable binding to the receptor proteins. This study not only provides a powerful screening tool for designing novel FAK inhibitors, but also presents a series of novel FAK inhibitors with high micromolar activity that can be used for further characterization. It provides a reference for addressing the shortcomings of drug metabolism and drug resistance of traditional FAK inhibitors, as well as the development of novel clinically applicable FAK inhibitors.

Salmonella Typhi serine threonine kinase T4519 induces lysosomal membrane permeabilization by manipulating Toll-like receptor 2-Cystatin B-Cathepsin B-NF-κB-reactive oxygen species pathway and promotes survival within human macrophages

Intracellular pathogens of Salmonella spp. survive and replicate within the phagosomes, called Salmonella-containing vacuoles (SCVs) inside macrophages by manipulating phagosomal maturation and phagolysosome formation. While controversies exist about the phagosomal traffic of Salmonella Typhimurium, little studies were carried out with the intracellular survival mechanisms of Salmonella Typhi (S. Typhi). We had previously reported that a eukaryote-like serine/threonine kinase of S. Typhi (T4519) contributes to survival within macrophages and activates host pro-inflammatory signaling pathways regulated by NF-κB. However, neither the mechanisms underlying NF-κB activation nor how it contributes to intracellular survival of S. Typhi were studied. Here we show, by using antibody-mediated blocking and gene knockdown studies that T4519 activates Toll-like receptor 2 (TLR2) signals in the human monocyte-derived macrophages. We computationally predicted the NH2-terminal glycine rich repeat domain of T4519 as the TLR2-binding moiety and confirmed the interaction by co-immunoprecipitation experiment. TLR2-T4519 interaction transcriptionally repressed cystatin B, a cathepsin B inhibitor, leading to the activation of cytosolic cathepsin B, leaked from the lysosomes of the infected cells. Through a series of RT-qPCR, western blotting, gene knockdown, flow cytometry and confocal microscopy experiments, we have shown that active cytosolic cathepsin B cleaves IKB-α, resulting in nuclear translocation of NF-κB and transactivation of its target genes, including reactive oxygen species (ROS), which in turn induces lysosomal membrane permeabilization (LMP). TLR2-dependent targeting of the cystatin B-cathepsin B-NF-κB-ROS pathways by T4519, leading to LMP promotes phagosomal survival of S. Typhi. This study describes a unique mechanism of the exploitation of host NF-κB signaling pathways by bacterial pathogens to promote its own persistence within macrophage cells.

Dynamic self-assembled meso-structures formed across a wide concentration range in aqueous solutions of propranolol hydrochloride

HYPOTHESIS

Nanoscale characterisation of the self-associated species formed by amphiphilic pharmaceuticals in aqueous solution carries relevance across their entire journey from development through to manufacture - relevant, therefore, not only as regards formulation of the drug products as medicines, but also potentially relevant to their bioavailability, activity, and clinical side effects. Such knowledge and understanding, however, can only be fully secured by applying a range of experimental and theoretical methodologies.

EXPERIMENTS

Herein, we apply a synergistic combination of solubility, surface tension, SANS, NMR and UV spectroscopic studies, together with MD simulation and QM calculations, to investigate the meso-structures of propranolol hydrochloride aggregates in bulk aqueous solutions, at concentrations spanning 2.5 mM to > 200 mM. In addition, we explore the effects of adding NaCl to mimic the ionic strength of physiological fluids, and the differences between racemate and single enantiomer.

FINDINGS

There is a continuum of particle sizes shown to exist across the entire concentration range, with molecules joining and leaving on the nanosecond timescale, and with the distributions of aggregate sizes varying with drug and salt concentration. Given that propranolol is a highly prescribed (WHO essential) medicine, disfavouring aggregators from consideration in high-throughput screening for potential new drug candidates - as many have advocated - should thus be done cautiously.

[Mechanism of Cnidii Fructus in the treatment of periodontitis with osteoporosis based on network pharmacology, molecular docking, and molecular dynamics simulation]

OBJECTIVES

This study aimed to explore the active components, potential targets, and mechanism of Cnidii Fructus in the treatment of periodontitis with osteoprosis through network pharmacology, molecular docking, and molecular dynamics simulation technology.

METHODS

The main chemical constituents and targets of Cnidii Fructus were screened using the TCMSP and SwissTargetPrediction databases, as well as literature reports. Targets of periodontitis and osteoporosis were predicted using different databases. The intersection targets of Cnidii Fructus, periodontitis, and osteoporosis were obtained using Venny 2.1. The protein-protein interaction network was formed on the STRING platform. Cytoscape 3.9.1 was used to construct the active component-intersection target interaction network, perform the topological analysis, and screen key targets and core active components. Furthermore, the Metascape database was used to perform gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis on the intersection targets. The top five key targets and core active components were selected as receptor proteins and ligand small molecules. Discovery Studio 2019 was used to dock ligands and receptors and visualize the docking results. Molecular dynamics simulation was conducted using Gromacs2022.3 to assess the stability of the interactions between the core active components and the main targets.

RESULTS

A total of 20 potential active ingredients of Cnidii Fructus were screened, and 116 targets of Cnidii Fructus were obtained for treating periodontitis and osteoporosis. GO and KEGG analyses of the 116 targets showed that Cnidii Fructus may play a therapeutic role through the phosphoinositide 3-kinase-protein kinase B (PI3K-Akt) and advanced glycation end products-receptor for advanced glycation end products (AGE-RAGE) signaling pathways. Molecular docking showed that the core constituents were well bound to the main targets. Molecular dynamics simulations confirmed the stability of the Diosmetin-AKT1 complex system.

CONCLUSIONS

The preliminary discovery of the potential molecular pharmacological mechanism of Cnidii Fructus extract in the targeted treatment of periodontitis with osteoporosis through a multi-component, multitarget, and multi-pathway approach can serve as a theoretical foundation for future drug-development research and clinical application.

Identification and Structural Characterization of a Novel COL3A1 Gene Duplication in a Family With Vascular Ehlers-Danlos Syndrome

BACKGROUND

Vascular Ehlers-Danlos syndrome (vEDS) is caused by alterations in the COL3A1 gene, typically involving missense variants that replace glycine residues. In contrast, short in-frame insertions, deletions, and duplications are rare and pose significant challenges for investigation.

METHODS

The histological examination of vascular tissue from a 26-year-old man, who died from a common iliac artery aneurysm and whose mother died at age 60 from an abdominal aortic dissection, strongly suggested a diagnosis of Ehler-Danlos type IV. Ex vivo collagen phenotype assessment, molecular analysis, and in silico structural studies of type III collagen were subsequently performed.

RESULTS

Ex vivo analysis of the patient's fibroblasts revealed altered collagen synthesis, whereas the molecular testing identified a novel 18-nucleotide in-frame duplication (c.2868_2885dup-GGGTCTTGCAGGACCACC) in the COL3A1 gene, resulting in a six-amino acid insertion, p.(Leu958_Gly963dup). Structural investigation indicated that this duplication led to a local perturbation of the collagen triple helix near a metalloproteinase cleavage site.

CONCLUSION

This study highlights the pathogenic role of a novel in-frame duplication in the COL3A1 gene, demonstrating how this seemingly benign alteration significantly compromises collagen turnover and contributes to the development of vEDS.

Anticancer efficacy of thiazole-naphthyl derivatives targeting DNA: Synthesis, crystal structure, density functional theory, molecular docking, and molecular dynamics studies

Two newly synthesized ligands, 1-((2-(4-(4-methoxyphenyl)thiazol-2-yl)hydrazono)methyl)naphthalen-2-ol (HL1) and 1-((2-(4-(naphthalen-1-yl)thiazol-2-yl)hydrazono)methyl)naphthalen-2-ol (HL2) were characterized using spectroscopy and single X-ray crystallography. Both belong to triclinic systems with space groups P21/c (HL1) and P-1 (HL2), exhibiting planar structures. Biological assays revealed significant antitumor activity, with HL2 showing significant antitumor activity against HepG2 cells (IC50: 3.2 ± 0.1 μM) compared to HL1 (IC50: 7.3 ± 0.3 μM). Mechanistic studies revealed HL2 induces apoptosis, while HL1 triggers necroptosis, and both were non-toxic to peripheral blood mononuclear cells (PBMC). UV-Vis titration showed that HL2 binds more strongly to DNA (Kb: 1.08 ± 0.215 × 105 M-1) than HL1 (Kb: 1.02 ± 0.155 × 104 M-1), attributed to stronger naphthyl chromophore stacking with DNA base pairs. Supporting this, hypochromic effects, circular dichroism spectra, and increased DNA viscosity suggest HL2 is a moderate intercalator, while HL1 functions as a groover binder. Docking studies revealed that in HL2, an additional naphthyl group enhances DNA binding affinity, explaining its superior efficacy. Molecular dynamics simulations further confirmed the stable binding of both ligands to DNA in the biological environment. These experimental and theoretical findings highlight the superior binding affinity of HL2 and its potential as a promising candidate for cancer therapy.

Substrate recognition in Bacillus anthracis sortase B beyond its canonical pentapeptide binding motif and use in sortase-mediated ligation

Sortases are critical cysteine transpeptidases that facilitate the attachment of proteins to the cell wall in Gram-positive bacteria. These enzymes are potential targets for novel antibiotic development, and versatile tools in protein engineering applications. There are six classes of sortases recognized, yet class A sortases (SrtA) are the most widely studied and utilized. SrtA enzymes endogenously recognize the amino acid sequence LPXTG, where X = any amino acid, with additional promiscuity now recognized in multiple positions for certain SrtA enzymes. Much less is known about Class B sortases (SrtB), which target a distinct sequence, typically with an N-terminal Asn, e.g., variations of NPXTG or NPQTN. Although understudied overall, two SrtB enzymes were previously shown to be specific for heme transporter proteins, and in vitro experiments with the catalytic domains of these enzymes reveal activities significantly worse than SrtA from the same organisms. Here, we use protein biochemistry, structural analyses, and computational simulations to better understand and characterize these enzymes, specifically investigating Bacillus anthracis SrtB (baSrtB) as a model SrtB protein. Structural modeling predicts a plausible enzyme-substrate complex, which is verified by mutagenesis of binding cleft residues. Furthermore, residues N- and C-terminal to the pentapeptide recognition motif are critical for observed activity. Finally, we use chimeric proteins to identify mutations that improve baSrtB activity by ∼4-fold, and demonstrate the feasibility of sortase-mediated ligation using a baSrtB enzyme variant. These studies provide insight into SrtB-target binding as well as evidence that SrtB enzymes can be modified to be of potential use in protein engineering.

Histone modification-driven structural remodeling unleashes DNMT3B in DNA methylation

The DNA methyltransferase 3B (DNMT3B) plays a vital role in shaping DNA methylation patterns during mammalian development. DNMT3B is intricately regulated by histone H3 modifications, yet the dynamic interplay between DNMT3B and histone modifications remains enigmatic. Here, we demonstrate that the PWWP (proline-tryptophan-tryptophan-proline) domain within DNMT3B exhibits remarkable dynamics that enhances the enzyme's methyltransferase activity upon interactions with a modified histone H3 peptide (H3K4me0K36me3). In the presence of H3K4me0K36me3, both the PWWP and ADD (ATRX-DNMT3-DNMT3L) domains transition from autoinhibitory to active conformations. In this active state, the PWWP domain most often aligns closely with the catalytic domain, allowing for simultaneous interactions with H3 and DNA to stimulate DNA methylation. The prostate cancer-associated DNMT3B R545C mutant is even more dynamic and susceptible to adopting the active conformation, resulting in aberrant DNA hypermethylation. Our study suggests the mechanism by which conformational rearrangements in DNMT3B are triggered by histone modifications, ultimately unleashing its activity in DNA methylation.

Mechanistic Insights into the Reactive Uptake of Bromine Nitrate at the Air-Water Interface: Interplay between Halogen Bonding and Solvation

The reactive uptake of bromine nitrate (BrONO2) into aqueous aerosols is a pivotal process in atmospheric bromine chemistry. BrONO2 forms halogen bonds with adjacent water molecules, disrupting hydrogen-bond networks and potentially triggering unique chemical behaviors. However, the role of halogen bonds in interfacial reactions remains an open question. Herein, we employ a comprehensive approach combining quantum chemistry calculations, classical molecular dynamics, ab initio molecular dynamics (AIMD) simulations, and advanced enhanced sampling methods to investigate the solvation and hydrolysis of bromine nitrate (BrONO2) at the air-water interface. Our simulations reveal that BrONO2 can stably exist at the interface, providing favorable conditions for its hydrolysis. The interplay between halogen bonding and solvation facilitates the spontaneous formation of H2OBrONO2 at the interface, which subsequently reacts to produce HOBr and HNO3. Free energy calculations indicate that this reaction is both kinetically and thermodynamically favorable at the air-water interface with an energy barrier of approximately 3.0 kcal/mol at 300 K. The insights from this simulation study will help guide future experiments to explore how water clouds affect halogen chemistry.

Investigating the Therapeutic Ability of Novel Antimicrobial Peptide Dendropsophin 1 and Its Analogues through Membrane Disruption and Monomeric Pore Formation

Antimicrobial peptides (AMPs) are an alternative source of antibiotics that fight worldwide antibiotic-resistant catastrophes. Dendropsophin 1 (Dc1) is a recently invented novel AMP with 17 amino acid residues obtained from the screen secretion of a frog named Dendropsophus columbianus. Dc1 has two slightly mutated analogues, namely, Dc1.1 and Dc1.2, with improved cationicity and mean amphipathic moment to enhance the selective toxicity against microorganisms. Experimental results indicate that Dc1 and Dc1.1 have similar antimicrobial activity against Gram-negative bacteria Escherichia coli and Gram-positive bacteria Staphylococcus aureus, whereas the synthesized peptide Dc1.2 has shown antimicrobial activity against a wide range of microorganisms. However, the molecular level details of the peptide-membrane interaction and the corresponding changes in the peptide structure remain elusive. In this study, we investigate the bacterial membrane disruption capability of these AMPs by running a total of 14.2 μs long molecular dynamics (MD) simulations. Our findings suggest that all three peptides affect the upper layer of the membrane with different degrees of disruption. After penetration, Dc1 and Dc1.2 retain stable α-helices in the core region, indicating the potential to disrupt the second layer. However, secondary structure analysis shows that Dc1.2 attains extended helical regions on the C-terminus, suggesting it as the superior candidate among the analogues to have the potential of stable pore formation, leading to bacterial cell death. To speed up our study, we adopt a one-transmembrane configuration of Dc1, Dc1.1, and Dc1.2 and find toroidal pores with subsequent water leakage for Dc1.2.

Impact of the Torsion Angle in Y6-Backbone Acceptors on the Open-Circuit Voltage in Organic Solar Cells

In organic solar cells (OSCs), optimizing the molecular geometry is crucial for improving device efficiency by reducing recombination rates and maximizing charge transfer (CT) state energy. Understanding the structure-property relationship regarding molecular geometry, electronic structure, and open-circuit voltage (Voc) is essential. By employing molecular dynamics simulations and density functional theory calculations, we explored how intramolecular torsion angles (θ) between conjugated moieties impact Voc. Small θ promotes molecular orbital energy degeneracy, reducing the CT energy (ECT) and its energetic disorder (σCT). While a low ECT can increase non-radiative energy losses (ΔEnr), a small σCT decreases ΔEnr. Balancing these effects is essential to maximize the value of ECT - ΔEnr for high Voc. L8-BO exhibits large θ, resulting in high ECT of 1.17 eV in PM6/L8-BO compared to 1.04 eV in PM6/Y6, while the latter has 0.17 eV lower ΔEnr. Consequently, PM6/L8-BO achieved a Voc of 0.87 V, surpassing 0.81 V of PM6/Y6. These findings were consistent with experimental 0.89 V in PM6/L8-BO and 0.84 V in PM6/Y6. This study demonstrates the crucial role of intramolecular dihedral angles on OSC material design, as they significantly influence the conjugation effect and CT state distribution.

Innovative Application of Medicinal Insects: Employing UHPLC-MS, Bioinformatics, In Silico Studies and In Vitro Experiments to Elucidate the Multi-Target Hemostatic Mechanism of Glenea cantor (Coleoptera: Cerambycidae) Charcoal-Based Medicine

Background: Longhorn beetles, a widely recognized group of Chinese traditional medicinal insects, are characterized by their notable hemostatic properties. However, the comprehensive understanding of their medicinal potential has been hindered by the limitations of current research methodologies. Methods: This study focuses on the species Glenea cantor (Fabricius), which can produce several generations per year, and introduces a novel method using microwave carbonization techniques. By employing an in vitro coagulation test, UHPLC-MS, network pharmacology, molecular docking, and molecular dynamics simulation, the hemostatic efficacy and mechanism of action of Glenea cantor charcoal medicine (GC-CM) were thoroughly studied. Results: In vitro coagulation tests showed that GC-CM significantly reduced the activated partial thromboplastin time (APTT) and prothrombin time (PT), indicating its ability to enhance the coagulation cascade and preliminarily confirming its hemostatic efficacy (p < 0.01 vs. blank control group). The analysis revealed that GC-CM comprises 453 components, including 137 bioactive components with high human utilization. After predictions via databases such as SwissTargetPrediction and deduplication, 215 targets linked to hemostatic specificity were identified. These targets regulate signaling pathways such as platelet activation, complement and coagulation cascades, and cGMP-PKG. Molecular docking demonstrated strong affinities between key targets such as SRC and PIK3R1 and compounds such as 2',6'-dihydroxy 4'-methoxydihydrochalcone, and 1-monolinoleoyl-rac-glycerol (binding energy < -5 kcal/mol). Molecular dynamics simulations show good binding capacity between core components and targets Conclusions: The aim of this study was to elucidate the material basis and mechanism of the hemostatic efficacy of GC-CM, offering a model for exploring other insect-based medicinal resources.

Molecular Dynamics Study on the Heat of Phase Transition of Chloroacetate from the Bulk to the Surface Phases

Based on the surface adsorption theory developed in our group and molecular dynamics simulations, the adsorption behaviors of methyl chloroacetate, ethyl chloroacetate, propyl chloroacetate, methyl dichloroacetate, and methyl trichloroacetate at the vapor-liquid interface have been thoroughly investigated. The surface layer thickness of these five liquids shows a significant increase as temperature increases, but it decreases significantly with the increase of intermolecular interactions of chloroacetates. It is found with our surface adsorption theory that the reversible heat of phase transition for chloroacetates from bulk phase to surface phase increases from methyl chloroacetate to propyl chloroacetate with the alkyl chain and also increases from methyl chloroacetate to methyl trichloroacetate as the number of chloro group increases. Molecular dynamics simulation is exploited to calculate the entropies of these five liquids in the surface and bulk regions at various temperatures. The variation trends of the simulated results are consistent with those of the phase transition heats determined with our surface adsorption theory.

Computation-Enabled Structure-Based Discovery of Potent Binders for Small-Molecule Aptamers

Aptamers, functional nucleic acids recognized for their high target-binding affinity and specificity, have been extensively employed in biosensors, diagnostics, and therapeutics. Conventional screening methods apply evolutionary pressure to optimize affinity, while counter-selections are used to minimize off-target binding and improve specificity. However, aptamer specificity characterization remains limited to target analogs and experimental controls. A systematic exploration of the chemical space for aptamer-binding chemicals (targets) is crucial for uncovering aptamer versatility and enhancing target specificity in practical applications, a task beyond the scope of experimental approaches. To address this, we employed a high-throughput three-stage structure-based computational framework to identify potent binders for two model aptamers. Our findings revealed that the l-argininamide (L-Arm)-binding aptamer has a 31-fold higher affinity for the retromer chaperone R55 than for L-Arm itself, while guanethidine and ZINC10314005 exhibited comparable affinities to L-Arm. In another case, norfloxacin and difloxacin demonstrated over 10-fold greater affinity for the ochratoxin A (OTA)-binding aptamer OBA3 than OTA, introducing a fresh paradigm in aptamer-target interactions. Furthermore, pocket mutation studies highlighted the potential to tune aptamer specificity, significantly impacting the bindings of L-Arm or norfloxacin. These findings demonstrate the effectiveness of our computational framework in discovering potent aptamer binders, thereby expanding the understanding of aptamer-binding versatility and advancing nucleic acid-targeted drug discovery.

Molecular Insights into the Rhamnolipid-Promoted Enzymatic Performance on Removing Phenolic Pollutants

Horseradish peroxidase (HRP) is a metalloenzyme widely used in various biochemical applications but is susceptible to activity loss and instability under suboptimal conditions. In this study, rhamnolipid (RL) was, for the first time, employed as an additive to enhance the catalytic performance of HRP, including in a dual-enzyme cascade system with glucose oxidase (GOx). We carried out catalytic experiments on phenol degradation and showed that protecting HRP from deactivation is critical in maintaining the high catalytic effect in the dual-enzyme cascade. The computational simulation revealed that the selective binding between polyphenolic products with RL clears the side products at the active pocket of HRP, maintaining the accessibility and high catalytic activity of HRP to phenolic substrates. This work discovered the underpinned mechanism in RL-protected enzyme-catalysis, enabling advanced design and widespread application of natural enzymes in organic removal and water remediation.

Dynamic doping and interphase stabilization for cobalt-free and high-voltage Lithium metal batteries

Cobalt-free spinel LiNi0.5Mn1.5O4 (LNMO) positive electrodes, promise high energy density when coupled with lithium negative electrodes, due to the high discharge voltage platform. However, the intrinsic dissolution of Mn in positive electrode, electrolyte decomposition at high voltage, and dendrite growth on lithium severely compromise cycling stability, limiting the practical application. Herein, we propose ferrocene hexafluorophosphate as an electrolyte additive to achieve dynamic doping of Fe3+ in positive electrodes during electrochemical cycling. Furthermore, additive molecule preferentially decomposes at both the positive and negative electrode interfaces, forming thin, dense inorganic positive electrode electrolyte interphase and F, P-rich inorganic solid electrolyte interphase respectively, effectively stabilizing electrode interfaces. Consequently, the Li | |LNMO batteries based on modified electrolytes effectively enhance cycling stability and rate performance at a charge cutoff voltage of 4.9 V and an LNMO pouch cell performs consistently over 160 cycles. Additionally, the efficacy of ferrocene hexafluorophosphate extends beyond LNMO, demonstrating its universal applicability in stabilizing positive electrodes operating at challenging voltages, including LiNi0.8Co0.1Mn0.1O2, LiNi0.6Co0.2Mn0.2O2, and LiCoO2 and a 470 Wh kg-1 level Li metal pouch cell was successfully realized.

Synthesis, in silico and in vitro antimicrobial efficacy of some amidoxime-based benzimidazole and benzimidamide derivatives

Amidoximes are employed as building blocks to synthesise heterocyclic motifs with biological significance. They are very reactive and are used as prodrugs of amidine. This present study unveils the synthesis of amidoxime-based benzimidazole and benzimidamide motifs and evaluates their in silico and in vitro antimicrobial potential as future drug candidates. The compounds (2a, 2b, 4a-c) were synthesized using multi-step synthetic pathways. The synthesised compounds were characterised using physico-chemical examination, 1H- and 13C-NMR, DEPT-135, and FT-IR spectroscopic analyses. The in silico antimicrobial potentials of the synthesized compounds were carried out against glucosamine-6-phosphate synthase of E. coli (PDB ID: 2VF5), and N-myristoyltransferase (NMT) of C. albicans (PDB ID: 1IYL), while the in vitro antimicrobial screening was investigated against selected bacteria and fungi. The in silico studies were carried out using predicted ADMET screening, molecular docking, MM-GBSA, induced-fit docking (IFD), and molecular dynamics (MD) simulation studies. Furthermore, the in vitro experimental validations were performed using the agar diffusion method and the standard antibacterial and antifungal drugs used were gentamicin and ketoconazole respectively. The predicted toxicity test of the compounds showed no significant risk, except for 4c, which showed high tumorigenic risk. Compounds 2b and 2a gave better binding energies; -8.0 kcal mol-1 for 2VF5 and -11.7 kcal mol-1 for 1IYL, respectively. The antimicrobial zone of inhibition and minimum inhibitory concentration values were 40 mm and 3.90 mg mL-1 against S. mutans, then 42 mm and 1.90 mg mL-1 against C. albicans. Potential antimicrobial drug candidates have been identified in this report and should be explored for future preclinical research.

The solvation of Na+ ions by ethoxylate moieties enhances adsorption of sulfonate surfactants at the air-water interface

HYPOTHESIS

Experiments show pronounced synergy in the reduction of surface tension when the nonionic surfactant Poly(oxy-1,2-ethanediyl), .alpha.-tris(1-phenylethyl)phenyl-.omega.-hydroxy- (Ethoxylated tristyrylphenol, EOT) is mixed with the anionic surfactant Sodium 4-dodecylbenzenesulfonate (NaDDBS). We hypothesize that the synergism is due to counterion (cation) effects. This would be unusual as one of the surfactants is nonionic. To test this hypothesis, the molecular mechanisms responsible need to be probed using experiments and simulations.

APPROACH

The interfacial properties of mixtures comprising EOT and NaDDBS are investigated using equilibrium molecular dynamics (MD) simulations. Free energy calculations using thermodynamic integration and umbrella sampling methods are employed to analyze the molecular interactions at surface and reveal the role of counterion solvation on the results observed. Simulation snapshots and trajectories are interrogated to confirm the findings.

FINDINGS

Simulation results indicate that the ethoxylate moieties solvate Na+ ions, forming long-lasting cation-EOT complexes. Free energy calculations suggest that these complexes are more stable at the interface than in the bulk, likely because of changes in the dielectric properties of water. The cation-EOT complexes, in turn, cause a stronger affinity between the interface and NaDDBS when EOT is present. Similar studies conducted for mixtures of EOT and cationic surfactant Dodecylammonium chloride (DAC) do not show evidence of Cl- ions solvation via the ethoxylate moieties, while the DAC headgroup was found to form hydrogen bonds with the EOT headgroup. This suggests that the mechanisms observed are likely ion specific.

Computational analysis of antimicrobial peptides targeting key receptors in infection-related cardiovascular diseases: molecular docking and dynamics insights

Infection-related cardiovascular diseases (CVDs) pose a significant health challenge, driving the need for novel therapeutic strategies to target key receptors involved in inflammation and infection. Antimicrobial peptides (AMPs) show the potential to disrupt pathogenic processes and offer a promising approach to CVD treatment. This study investigates the binding potential of selected AMPs with critical receptors implicated in CVDs, aiming to explore their therapeutic potential. A comprehensive computational approach was employed to assess AMP interactions with CVD-related receptors, including ACE2, CRP, MMP9, NLRP3, and TLR4. Molecular docking studies identified AMPs with high binding affinities to these targets, notably Tachystatin, Pleurocidin, and Subtilisin A, which showed strong interactions with ACE2, CRP, and MMP9. Following docking, 100 ns molecular dynamics (MD) simulations confirmed the stability of AMP-receptor complexes, and MM/PBSA calculations provided quantitative insights into binding energies, underscoring the potential of these AMPs to modulate receptor activity in infection and inflammation contexts. The study highlights the therapeutic potential of Tachystatin, Pleurocidin, and Subtilisin A in targeting infection-related pathways in CVDs. These AMPs demonstrate promising receptor binding properties and stability in computational models. Future research should focus on in vitro and in vivo studies to confirm their efficacy and safety, paving the way for potential clinical applications in managing infection-related cardiovascular conditions.

Amino acid variants in the HLA-DQA1 and HLA-DQB1 molecules explain the major association of variants with relapse status in pediatric patients with steroid-sensitive nephrotic syndrome

BACKGROUND

Management of patients with steroid-sensitive nephrotic syndrome (SSNS) is challenging because of frequent relapses. Causal variants in the human leukocyte antigen (HLA) class II region that are associated with relapse remain undetermined.

METHODS

We collected a cohort of East Asian individuals comprising 206 pediatric patients with SSNS and 435 healthy controls from Southwest China. Ninety children with steroid-sensitive nephrotic syndrome without relapse (SSNSWR) and 116 children with steroid-dependent and/or frequent relapse nephrotic syndrome (SDNS/FRNS) were genotyped using Sanger sequencing. We then measured the transcriptional level, allele expression imbalance (AEI) and functional proteins of HLA-DQA1 and HLA-DQB1 in different stages of SDNS/FRNS.

RESULTS

rs1464545187 in ANKRD36 was associated with an approximately 1.69-fold greater risk for SSNSWR (P = 0.04; 95% confidence interval [CI], 1.05-2.72). Clustered risk variants in HLA-DQA1 and HLA-DQB1 were significantly associated with SDNS/FRNS (rs1047989: P = 2.26E-07, odds ratio [OR] = 2.25, 1.65-3.05; rs9273471: P = 5.45E-05, OR = 1.84, 1.37-2.46; HLA-DQB1*06:02: P = 0.017, OR = 0.19, 0.04-0.77). The genotype distributions of rs1047989, 2:171713702, rs1049123, rs9273471, and HLA-DQB1*06:02 in patients with SSNS were significantly different from those in healthy controls. rs1047989 (HLA-DQA1) was significantly associated with a greater number of infections at relapse in SDNS/FRNS patients (P = 0.045, OR = 6.79, 95% CI: 1.29-168.52). Flow cytometry showed that the proportion of cells expressing HLA-DQA1+/DQB1+ (HLA-DQA1+, P = 0.0046; HLA-DQB1+, P = 0.0045) was lowest in the relapse stage. In addition, the mRNA levels of HLA-DQA1 and HLA-DQB1 were significantly greater in the relapse group than in the remission group (HLA-DQA1, P = 0.03; HLA-DQB1, P = 0.002). No significant AEIs were detected in the different stages of SDNS/FRNS. The rs1047989 variant is likely to affect the structure and stability of HLA-DQA1.

CONCLUSION

rs1464545187 is a risk locus for SSNSWR but not SDNS/FRNS in Chinese children. Functional variations in HLA-DQA1 and HLA-DQB1 are implicated in regulating the immune response of SSNS patients, which may explain the typical triggering of SDNS/FRNS onset by infections.

A Machine Learning Model for the Prediction of Water Contact Angles on Solid Polymers

The interaction between water and solid surfaces is an active area of research, and the interaction can be generally defined as hydrophobic or hydrophilic depending on the level of wetting of the surface. This wetting level can be modified, among other methods, by applying coatings, which often modify the chemistry of the surface. With the increase in available computing power and computational algorithms, methods to develop new materials and coatings have shifted from being heavily experimental to including more theoretical approaches. In this work, we use a range of experimental and computational features to develop a supervised machine learning (ML) model using the XGBoost algorithm that can predict the water contact angle (WCA) on the surface of a range of solid polymers. The mean absolute error (MAE) of the predictions is below 5.0°. Models composed of only computational features were also explored with good results (MAE < 5.0°), suggesting that this approach could be used for the "bottom-up" computational design of new polymers and coatings with specific water contact angles.

Amber ff24EXP-GA, Based on Empirical Ramachandran Distributions of Glycine and Alanine Residues in Water

Molecular dynamics (MD) offers important insights into intrinsically disordered peptides and proteins (IDPs) at a level of detail that often surpasses that available through experiments. Recent studies indicate that MD force fields do not reproduce intrinsic conformational ensembles of amino acid residues in water well, which limits their applicability to IDPs. We report a new MD force field, Amber ff24EXP-GA, derived from Amber ff14SB by optimizing the backbone dihedral potentials for guest glycine and alanine residues in cationic GGG and GAG peptides, respectively, to best match the guest residue-specific spectroscopic data. Amber ff24EXP-GA outperforms Amber ff14SB with respect to conformational ensembles of all 14 guest residues x (G, A, L, V, I, F, Y, Dp, Ep, R, C, N, S, T) in GxG peptides in water, for which complete sets of spectroscopic data are available. Amber ff24EXP-GA captures the spectroscopic data for at least 7 guest residues (G, A, V, F, C, T, Ep) better than CHARMM36m and exhibits more amino acid specificity than both the parent Amber ff14SB and CHARMM36m. Amber ff24EXP-GA reproduces the experimental data on three folded proteins and three longer IDPs well, while outperforming Amber ff14SB on short unfolded peptides.

Active-Learning Assisted General Framework for Efficient Parameterization of Force-Fields

This work presents an efficient approach to optimizing force field parameters for sulfone molecules using a combination of genetic algorithms (GA) and Gaussian process regression (GPR). Sulfone-based electrolytes are of significant interest in energy storage applications, where accurate modeling of their structural and transport properties is essential. Traditional force field parametrization methods are often computationally expensive and require extensive manual intervention. By integrating GA and GPR, our active learning framework addresses these challenges by achieving optimized parameters in 12 iterations using only 300 data points, significantly outperforming previous attempts requiring thousands of iterations and parameters. We demonstrate the efficiency of our method through a comparison with state-of-the-art techniques, including Bayesian Optimization. The optimized GA-GPR force field was validated against experimental and reference data, including density, viscosity, diffusion coefficients, and surface tension. The results demonstrated excellent agreement between GA-GPR predictions and experimental values, outperforming the widely used OPLS force field. The GA-GPR model accurately captured both bulk and interfacial properties, effectively describing molecular mobility, caging effects, and interfacial arrangements. Furthermore, the transferability of the GA-GPR force field across different temperatures and sulfone structures underscores its robustness and versatility. Our study provides a reliable and transferable force field for sulfone molecules, significantly enhancing the accuracy and efficiency of molecular simulations. This work establishes a strong foundation for future machine learning-driven force field development, applicable to complex molecular systems.

Computational Design and In Vitro and In Vivo Characterization of an ApoE-Based Synthetic High-Density Lipoprotein for Sepsis Therapy

Introduction: Septic patients have low levels of high-density lipoproteins (HDLs), which is a risk factor. Replenishing HDLs with synthetic HDLs (sHDLs) has shown promise as a therapy for sepsis. This study aimed to develop a computational approach to design and test new types of sHDLs for sepsis treatment. Methods: We used a three-step computational approach to design sHDL nanoparticles based on the structure of HDLs and their binding to endotoxins. We tested the efficacy of these sHDLs in two sepsis mouse models-cecal ligation and puncture (CLP)-induced and P. aeruginosa-induced sepsis models-and assessed their impact on inflammatory signaling in cells. Results: We designed four sHDL nanoparticles: two based on the ApoA-I sequence (YGZL1 and YGZL2) and two based on the ApoE sequence (YGZL3 and YGZL4). We demonstrated that an ApoE-based sHDL nanoparticle, YGZL3, provides effective protection against CLP- and P. aeruginosa-induced sepsis. The sHDLs effectively suppressed inflammatory signaling in HEK-blue or RAW264 cells. Conclusions: Unlike earlier approaches, we developed a new approach that employs computational simulations to design a new type of sHDL based on HDL's structure and function. We found that YGZL3, an ApoE sequence-based sHDL, provides effective protection against sepsis in two mouse models.

Synthesis, antibacterial activity, in silico ADMET prediction, docking, and molecular dynamics studies of substituted phenyl and furan ring containing thiazole Schiff base derivatives

This study synthesized eighteen phenyl and furan rings containing thiazole Schiff base derivatives 2(a-r) in five series, and spectral analyses confirmed their structures. The in vitro antibacterial activities of the synthesized analogs against two gram-positive and two gram-negative bacteria were evaluated by disk diffusion technique. Compounds (2d) and (2n) produced prominently high zone of inhibition with 48.3 ±  0.6 mm and 45.3 ±  0.6 mm against B. subtilis, respectively, compared to standard ceftriaxone (20.0 ±  1.0 mm). However, the antibacterial potency of the compounds with furan ring was more notable than that of phenyl ring-containing derivatives. Molecular docking and dynamic study were performed based on the wet lab outcomes of (2d) and (2n), where both derivatives remained in the binding site of the receptors during the whole simulation time with RMSD and RMSF values below 2 nm. In silico ADMET prediction studies of the synthesized compounds validated their oral bioavailability. A more detailed study of the quantitative structure-activity relationship is required to predict structural modification on bioactivity and MD simulation to understand their therapeutic potential and pharmacokinetics.

The Competition Between Cation-Anion and Cation-Triglyme Interaction in Solvate Ionic Liquids Probed by Far Infrared Spectroscopy and Molecular Dynamics Simulations

Glyme-based electrolyte solutions provide new concepts for developing suitable lithium-ion batteries. The so-called solvate ionic liquids (SILs) are promising electrolytes. They are most efficient in equimolar mixtures of lithium bis(trifluoromethanesulfonyl)imide ([Li][NTf2]) and glyme, wherein the [Li]+ cation is supposedly fully solvated by glyme molecules. Here, we performed far (FIR) and mid (MIR) infrared spectroscopy for probing the solvation and local structures around the [Li]+ ions. In particular, we studied the competition between the triglyme molecule (G3) and the salt anions for the coordination to the lithium cations with increasing [Li][NTf2] concentration. The formation of nano structures in the [Li][NTf2]:G3 mixtures is discussed in terms of contact (CIP) and solvent-separated (SIP) ion pairs in solution. At low salt concentrations, the [Li]+ cations are solvated by two triglyme molecules resulting in SIPs only. With increasing salt concentration, [Li]+ is predominantly solvated by one triglyme molecule as [Li(triglyme)1]+ but still remains in contact to one of the four oxygen atoms of the [NTf2]- anion. Molecular dynamics (MD) simulations provide a molecular picture of the [Li][NTf2]:G3 mixtures that supports the conclusions drawn from the experimental findings.

Micellar Solvent Accessibility of Esterified Polyoxyethylene Chains as Crucial Element of Polysorbate Oxidation: A Density Functional Theory, Molecular Dynamics Simulation and Liquid Chromatography/Mass Spectrometry Investigation

Given that the amphiphilicity of polysorbates represents a key factor in the protection of proteins from particle formation, the loss of this property through degradative processes is a significant concern. Therefore, the present study sought to identify the factors that contribute to the oxidative cleavage of the polysorbate (PS) molecule and to ascertain the preferred sites of degradation. In order to gain insight into the radical susceptibility of the individual polysorbate segments and their accessibility to water, conceptual density functional theory calculations and molecular dynamics simulations were performed. The behavior of monoesters and diesters was examined in both monomer form and within the context of micelles. The theoretical results were corroborated by experimental findings, wherein polysorbate 20 was subjected to 50 ppb Fe2+ and 100,000 lx·h of visible light, and subsequently stored at 25 °C/60% r.h. or 40 °C/75% r.h. for a period of 3 months. Molecular dynamics simulations demonstrated that unesterified polyoxyethylene(POE) chains within a polysorbate 20 molecule exhibited the greatest water accessibility, indicating their heightened susceptibility to oxidation. Nevertheless, the oxidative cleavage of esterified polyoxyethylene chains of a polysorbate 20 molecule is highly detrimental to the protective effect on protein particle formation. This occurs presumably at the oxyethylene (OE) units in the vicinity of the sorbitan ring, leaving a nonamphiphilic molecule in the worst case. Consequently, the critical degradation sites were identified, resulting in the formation of degradation products that indicate a loss of amphiphilicity in PS.

Allosteric inhibition of NMDA receptors by low dose ketamine

Ketamine, a general anesthetic, has rapid and sustained antidepressant effects when administered at lower doses. Anesthetic levels of ketamine reduce excitatory transmission by binding deep into the pore of NMDA receptors where it blocks current influx. In contrast, the molecular targets responsible for antidepressant levels of ketamine remain controversial. We used electrophysiology, structure-based mutagenesis, and molecular and kinetic modeling to investigate the effects of ketamine on NMDA receptors across an extended range of concentrations. We report functional and structural evidence that, at nanomolar concentrations, ketamine interacts with membrane-accessible hydrophobic sites on NMDA receptors, which are distinct from the established pore-blocking site. These interactions stabilize receptors in pre-open states and produce an incomplete, voltage- and pH-dependent reduction in receptor gating. Notably, this allosteric inhibitory mechanism spares brief synaptic-like receptor activations and preferentially reduces currents from receptors activated tonically by ambient levels of neurotransmitters. We propose that the hydrophobic sites we describe here account for clinical effects of ketamine not shared by other NMDA receptor open-channel blockers such as memantine and represent promising targets for developing safe and effective neuroactive therapeutics.

Structural insights into temperature-dependent dynamics of METPsc1, a miniaturized electron-transfer protein

The design of protein-metal complexes is rapidly advancing, with applications spanning catalysis, sensing, and bioremediation. We report a comprehensive investigation of METPsc1, a Miniaturized Electron Transfer Protein, in complex with cadmium. This study elucidates the impact of metal coordination on protein folding and structural dynamics across temperatures from 100 K to 300 K. Our findings reveal that METPsc1, composed of two similar halves stabilized by intramolecular hydrogen bonds, exhibits a unique "clothespin-like" recoil mechanism. This allows it to adapt to metal ions of varying radii, mirroring the flexibility observed in natural rubredoxins. High-resolution crystallography and molecular dynamics simulations unveil concerted backbone motions and subtle temperature-dependent shifts in side-chain conformations, particularly for residues involved in crystal packing. Notably, CdS bond lengths increase with temperature, correlating with anisotropic motions of the sulfur atoms involved in second-shell hydrogen bonding. This suggests a dynamic role of protein matrix upon redox cycling. These insights into METPsc1 highlight its potential for catalysis and contribute to the designing of artificial metalloproteins with functional plasticity.

Antioxidant effect, DNA-binding, and transport of the flavonoid acacetin influenced by the presence of redox-active Cu(II) ion: Spectroscopic and in silico study

Acacetin (AC) is a natural polyphenol from the group of flavonoids. It is well established that the behavior of flavonoids depends on the presence of redox-active substances; therefore, we aim to investigate their biological activity following the interaction with Cu(II) ion. Our study demonstrates that AC can effectively bind Cu(II) ions, as confirmed by UV-Vis and EPR spectroscopy as well as DFT calculations. AC appears as a potent scavenger against the model ABTS radical cation by itself, but this ability is significantly limited upon Cu(II) coordination. The possible mild synergistic effect of AC in the presence of vitamin C and glutathione was also shown by the ABTS•+ test. In contrast, an inhibitory effect was observed in the presence of Cu(II) ions. The equimolar addition of AC to the model Fenton-like system containing Cu(II) did not have a noticeable effect on the concentration of hydroxyl radicals produced, but in its excess the formation of •OH decreased, as proved by EPR spin trapping. Absorption titrations and gel electrophoresis revealed effective binding to calf thymus (CT)-DNA with a stronger interaction for the Cu(II)-AC complex. The detailed mode of binding to biomolecules was described using molecular docking and molecular dynamics. Obtained results indicate that the double helix of DNA unwinds after interaction with the Cu(II)-AC complex. Fluorescence spectroscopy, employing human serum albumin (HSA), suggested a potential transport capacity for both AC and its Cu(II) complex.

Exploring Holy Basil's Bioactive Compounds for T2DM Treatment: Docking and Molecular Dynamics Simulations with Human Omentin-1

Type 2 Diabetes Mellitus (T2DM) presents a substantial health concern on a global scale, driving the search for innovative therapeutic strategies. Phytochemicals from medicinal plants, particularly Ocimum tenuiflorum (Holy Basil), have garnered attention for their potential in T2DM management. The increased focus on plant-based treatments stems from their perceived safety profile, lower risk of adverse effects, and the diverse range of bioactive molecules they offer, which can target multiple pathways involved in T2DM. Computational techniques explored the binding interactions between O. tenuiflorum phytochemicals and Human Omentin-1, a potential T2DM target. ADMET evaluation and targeted docking identified lead compounds: Luteolin (-4.84 kcal/mol), Madecassic acid (-4.12 kcal/mol), Ursolic acid (-5.91 kcal/mol), Stenocereol (-5.59 kcal/mol), and Apigenin (-4.64 kcal/mol), to have a better binding affinity to target protein compared to the control drug, Metformin (-2.01 kcal/mol). Subsequent molecular dynamics simulations evaluated the stability of Stenocereol, Luteolin, and Metformin complexes for 200 nanoseconds, analysing RMSD, RMSF, RG, SASA, PCA, FEL, and MM-PBSA parameters. Results indicated Stenocereol's strong binding affinity with Omentin-1, suggesting its potential as a potent therapeutic agent for T2DM management. These findings lay the groundwork for further experimental validation and drug discovery endeavours.

Hydrolysis of chitin and chitosans by the human chitinolytic enzymes: chitotriosidase, acidic mammalian chitinase, and lysozyme

Human chitinolytic enzymes trigger growing interest, not only because a wide range of diseases and allergic responses are linked to chitinous components of pathogens, including their interplay with human enzymes, but also due to the increasing use of chitosans in biomedical applications. Here, we present a detailed side-by-side analysis of the only two human chitinases, chitotriosidase and acidic mammalian chitinase, as well as human lysozyme. By analyzing the cleavage of well-characterized chitosan polymers and defined chitin and chitosan oligomers, we report mild processivity and a quantitative subsite preference typical for GH18 chitinases for chitotriosidase and acidic mammalian chitinase. In contrast, lysozyme is negligibly processive and preferentially binds acetylated units at subsites -2, -1, and +1, thus exhibiting an even higher overall preference for acetylated units. A common feature of all three enzymes is their endo-chitinase behavior. For efficient hydrolysis, chitotriosidase or lysozyme require substrates of ≥4 or ≥5 units, respectively, and we identified defined chitosan oligomers which can competitively inhibit chitotriosidase. Knowledge about the enzymes' actions provides insight into the metabolic fate of chitin and chitosans in the human body, which is crucial to develop and approve chitosan applications, and to elucidate molecular mechanisms in chitin-associated diseases.