ACS Omega

Biophysics is a rapidly advancing field with an incredible breadth of topics. Thus, undergraduate biophysics instructors have to strategize and decide what topics they will cover in their courses. Educational institutions utilize a variety of biophysics textbooks. A common deficiency of each of the existing texts is that it serves well a given set of topics (theory, illustrations, practice problems) and leaves out other areas. A typical example includes good theory and problems for thermodynamics and kinetics while presenting molecular dynamics and various spectroscopic methods in a lacking or outdated way. The authors of this manuscript teach a capstone Biophysical Chemistry three-quarter series (Western Washington University/WWU, Bellingham, WA) which ideally should resonate with the general and major-specific courses the students take within their major at WWU. To achieve this goal and to enrich the traditional lecture-based delivery, the instructors have developed and brought together key pedagogical elements: purpose-built online textbook with a uniform structure of the academic content and practice problems, a study sample (oligopeptide) of biophysical significance with a growing set of experimental and computational data and student-centric in-class activities including computer labs. Our Biophysical series emphasizes concepts and methods of computational structural biology (Molecular Dynamics) and spectroscopic approaches (IR, UV and NMR). Here we describe the details of our integrative approach, summarize key outcomes and chart ways to advance the biophysical chemistry series further. Our textbook can be found through LibreText.

IL-4Ra is a key regulatory receptor for type 2 inflammatory responses, signal transduce from IL-4 and IL-13 through binding with IL-13Ra or the gamma c chain to activate the downstream JAK1-STAT6 pathway. IL-4Ra is currently the most successful "golden target" in the field of allergic disease therapeutics. Its representative monoclonal antibody drug, dupilumab, through the dual blockade mechanism of IL-4/IL-13 has pioneered a new era of precision therapy for type 2 inflammation. In our manuscript, we employed large-scale deep learning-based computational design methods to de novo design mini-protein antagonists specific for both human and mouse IL-4Ra. The binding affinity was improved from 22.1 nM to 569 pM through partial diffusion. The design accuracy and binding specificity were verified through X-ray crystallography and biochemical studies. In vitro IL4/IL13 signal blockade assays revealed that de novo designed monomeric mini-protein antagonist exhibited comparable blockade ability to bivalent dupilumab. In vivo pharmacokinetic half-life studies demonstrated that fusion to an HSA-binding domain extended the half-life of the mini-protein antagonist from 2.7 hours to 60.6 hours. The IL-4Ra mini-protein antagonist had excellent expression levels, solubility and thermal stability. The IL4/IL13 signal blockade ability remained unchanged even after being heating to 95 degrees. In conclusion, through large-scale cluster computing and deep learning-based de novo design, we developed well-performed IL-4Ra mini-protein antagonist, and demonstrates certain potential for drug development.

Kinema is a traditional fermented soybean food indigenous to the eastern Himalayan regions of Nepal and India. The fermentation process is primarily mediated by the bacterium Bacillus subtilis, which produces several bioactive compounds and enzymes with potential therapeutic applications. Considering the growing burden of cardiovascular diseases and the need for effective fibrinolytic agents for thrombolytic therapy, this study aimed to extract, partially purify, and evaluate the thrombolytic potential of kinemakinase derived from kinema prepared from white soybeans. Partial purification of the enzyme was achieved using ammonium sulfate precipitation. Thrombolytic activity was assessed in vitro using human blood clots, where three enzyme dilutions demonstrated clot lysis ranging from 66% to 68%, indicating considerable fibrinolytic potential. In silico analyses were also performed to investigate the structural and functional characteristics of the enzyme. The tertiary structure obtained from UniProt was modeled using the Robetta server and refined with GalaxyRefine. Docking with fibrin using ClusPro 2.0 and molecular dynamics simulations using iMODS confirmed favorable interaction and structural stability, while disulfide engineering enhanced protein stability. The findings suggest that kinema-derived kinemakinase may serve as a promising alternative thrombolytic agent, warranting further biochemical characterization and dosage optimization.

Histone deacetylases (HDACs) are pivotal epigenetic regulators that modulate diverse cellular pathways by removing acetyl groups from lysine residues on both histone and non-histone proteins. Histone deacetylase 11 (HDAC11), the sole member of class IV HDACs, exhibits both deacetylation and fatty acid deacylation activities. Accumulating evidence implicates HDAC11 as a key epigenetic regulator of fundamental cellular processes, including metabolism, immune responses, and tissue development. Dysregulation of HDAC11 activity has been associated with inflammatory diseases, metabolic disorders, neurodegenerative conditions, and cancer, highlighting its potential as a therapeutic target. Although several HDAC11-specific inhibitors have been identified, none have progressed to clinical development. In this study, we aimed to discover HDAC11-selective inhibitors by integrating in silico and in vitro validation approaches. Homology modelling of the HDAC11 structure was conducted, followed by model validation, structure-based virtual screening, molecular dynamics (MD) simulations, and binding free energy calculations. We identified and validated three lead compounds and their intermediates using biochemical and cell-based assays. Fluorescence-based and HPLC-based enzymatic assays demonstrated potent inhibition of both the deacetylase and deacylase activities of HDAC11, with Inhibitor 6 and Inhibitor 3 exhibiting the strongest effects among the six compounds tested. Further, a decrease in lipid accumulation, reduced stability of the HDAC11 substrate SHMT2, as determined by immunoblot analysis and decreased cell viability, as assessed by MTT assay, confirmed HDAC11 inhibition in cellular models. The study shows that new HDAC11 inhibitors significantly reduce the viability of breast cancer cells and induce apoptosis; inhibitor 6, in particular, showed high potency, similar to the reference compound SIS-17. Flow cytometry showed that treated MDA-MB-231 cells exhibited cell-cycle arrest and increased apoptosis, a finding further confirmed by Annexin V/PI staining. Molecular analysis showed that BAX increased while BCL2 decreased, indicating that apoptotic pathways were activated in novel compound-treated MDA-MB-231 cells. The results suggest that inhibiting HDAC11 is an effective way to induce cancer cell death and provide a basis for further assessment of these compounds as potential treatments for breast cancer. Collectively, this study identifies novel zinc-chelating HDAC11 inhibitors containing a nitro-sp2 group, providing promising candidates for further therapeutic development.

Small RNAs (sRNAs) regulate the expression of many genes including those involved in antibiotic resistance and bacterial virulence, making them potential therapeutic targets. A molecule that binds an sRNA could interfere with its ability to bind its target mRNA and disrupt the regulation mechanism. Randomization and screening of natural arginine rich motif (ARM) peptides led to peptides capable of interfering with the sRNA MicF's ability to regulate ompF in Escherichia coli. Molecular dynamics simulations suggested that this effect was not a result of a direct disruption of the MicF-ompF interaction. Instead, the peptides interfere with binding of the chaperone Hfq, which is required for MicF-mediated regulation. Subsequent testing demonstrated peptide specificity for MicF over two other Hfq scaffolds and the ability to disrupt regulation of two additional MicF targets. Together, these findings support the use of synthetic ARMs as a potential tool for modulating sRNA function in bacteria.

Breast cancer (BC) is the second most common noncutaneous cancer and the second leading cause of cancer-related death in women. BC is classified into three primary subtypes, with triple-negative breast cancer (TNBC) having the poorest prognosis because it lacks specific targetable markers. Preclinical studies on TNBC indicated a common occurrence of diminished tumor-suppressor activity of PTEN, activating the PI3K/AKT/mTOR signaling pathway. Notably, published studies reveal that the WWP1 enzyme plays a pivotal role in driving PTEN degradation via ubiquitination, unveiling a promising therapeutic target for treating TNBC. In the search of new WWP1 inhibitors, we used artificial intelligence (AI)-driven computational strategies for de novo design of peptide-based WWP1 inhibitors and identified a hexapeptide, termed WI23-B, which demonstrated high nanomolar binding affinity to WWP1. In TR-FRET enzymatic assays, WI23-B inhibited WWP1 activity with an IC of approximately 11 {micro}M. In MCF7 and MDA-MB-231 breast cancer cell lines, WI23-B showed promising cytotoxic efficacy, particularly in combination with the PI3K inhibitor BYL719, also when it was loaded into nanocapsules. Collectively, these findings highlight WI23-B as a promising lead peptide with potent WWP1 inhibitory activity and synergistic antiproliferative effects when combined with PI3K inhibitors. While further structural optimization is required to enhance its potency and pharmacological properties, our results provide a strong foundation for the development of next-generation WWP1 inhibitors. Such agents have the potential to reshape therapeutic strategies for BC and TNBC by enabling more effective and less toxic treatment regimens, ultimately reducing the reliance on high-dose chemotherapy and minimizing adverse effects.

Long noncoding RNAs encode for microproteins that regulate cellular functions. Small regulatory peptide of amino acid response (SPAR) is a microprotein in the lysosome that responds to amino acid availability of the cell. In this study, we investigated the interactions between SPAR and SLC38A9, a lysosomal amino acid transporter and receptor involved in the mechanistic target of rapamycin 1 (mTORC1) pathway. We found that SPAR binds SLC38A9 and inhibits arginine transport in SLC38A9. Moreover, the downstream recruitment of Rag GTPases is also inhibited when SPAR is present in SLC38A9 liposomes. Docking model shows potential interactions between SPAR and SLC38A9. Together, these findings reveal the mechanism of mTORC1 inhibition through microprotein SPAR and illustrates the power of non long coding RNAs in altering cellular functions. Statement of SignificanceMicroproteins encoded from long noncoding RNAs are emerging as critical regulators of many pathways. This study investigates a novel mechanism of SPAR microprotein that directly regulates the mechanistic target of rapamycin complex1 (mTORC1) signaling pathway through the lysosomal amino acid transporter SLC38A9. SPAR blocks both arginine transport and the downstream recruitment of Rag GTPases. These findings provide critical results in how SPAR controls cellular amino acid availability, while broadly highlighting the powerful regulatory mechanism of microproteins in cellular processes.

This present work shows that E-hook fragments possess functional structure differences governed by electrostatic interactions and sequence composition. The acidic C-terminal tails of tubulin, known as E-hooks, play a central role in regulating interactions between microtubules and motor proteins, microtubule-associated proteins, and enzymatic modifiers. Despite their functional importance, the intrinsic structural properties of these peptide segments remain poorly characterized due to their intrinsically disordered nature. In this work, we present quantum-mechanically optimized structures of hexamer peptides derived from {beta}-tubulin E-hook sequences. Density functional theory calculations were used to optimize peptide geometries using progressively larger basis sets. From the optimized geometries we calculated theoretical Raman spectra, Ramachandran backbone dihedral distributions, and measured radii of gyration to resolve composition dependent structural tendencies. The combined Raman and conformational analyses provide a systematic computational approach for comparing simulated and experimental Raman spectra of tubulin E-hooks and other intrinsically disordered proteins and offer insight into how E-hooks contribute to the recognition mechanisms underlying the tubulin code.

Green synthesis of zinc oxide nanoparticles (ZnO NPs) offers a sustainable strategy for developing multifunctional antimicrobial nanomaterials. In this study, ZnO NPs were synthesized using Azadirachta indica leaf extract and characterized by UV-vis spectroscopy, FTIR, XRD, SEM, and GC-MS. The nanoparticles exhibited a characteristic absorption peak at 352 nm, a direct band gap of 3.07 eV, and hexagonal wurtzite crystallinity with an average crystallite size of approximately 32 nm. The biosynthesized ZnO NPs showed concentration-dependent antibacterial activity against Erwinia carotovora, producing inhibition zones of up to 25.9 mm. Mechanistic studies revealed significant membrane damage, evidenced by 4.77-fold and 5.62-fold increases in extracellular protein and amino acid leakage, respectively, with marked alterations in bacterial protein profiles detected by SDS-PAGE. The nanoparticles also exhibited strong antioxidant activity, achieving 89.4% DPPH radical scavenging, and induced dose-dependent cytotoxicity in HepG2 cells with an estimated IC50 of 124.8 g/mL. These findings demonstrate that neem-mediated ZnO nanoparticles possess potent antibacterial activity through membrane disruption while exhibiting promising antioxidant properties, highlighting their potential as eco-friendly nanomaterials for the management of bacterial soft rot and other phytopathogenic diseases.

Cell confluency is a major determinant of cell-cell communication, protein interactions, access to nutrients, and signalling dynamics, thereby significantly impacting biological outcomes. Lung cancer cells like A549 are widely used as screening models for scientific studies wherein their growth in vitro progress from non-confluent to confluent growth. In this study, we investigated the transcriptomic adaptations associated with the transition of A549 cells from baseline non-confluent to confluent growth. Comparative transcriptomic analysis between confluent and cells at baseline identified 815 upregulated and 671 downregulated transcripts. Pathway enrichment analysis of deregulated transcripts in confluent cells revealed enhanced cholesterol and sterol biosynthetic pathways, along with suppression of chromosomal segregation and mitotic pathways. At confluency, an increased expression of glucose transporters (SLC2, SLC60, and SL37 families) and glycolytic pathways, and a decrease in amino acid transporters (SLC1, SLC7, SLC38, and SLC36) and amino acid metabolic pathways is observed. A reduced one-carbon metabolic signature (SHMT2, DHFR, and MTHFD2) and enhanced fatty acid precursor synthesis (HMGCLL1, ALDH6A1, and AASS) were also observed at confluency. 1H NMR profiling of culture media revealed higher glucose and glutamine utilisation with lactate accumulation during culture maturation. Collectively, the data suggest transcriptome-level rewiring in A549 cells with preferential biosynthesis of lipids and sterols at confluency and underscore the importance of considering culture maturity in cancer biology, metabolism, and therapeutic studies.

Melittin exhibits antitumor activity in cervical cancer models, yet the long non-coding RNA (lncRNA) response and associated regulatory networks remain poorly understood. Here, strand-specific RNA-seq data from melittin-treated and untreated U14 murine cervical cancer cells were analyzed to characterize melittin-responsive lncRNAs and explore their potential functional associations. A total of 28,162 lncRNAs were identified, including 27,307 known and 855 novel transcripts. Differential expression analysis revealed 404 differentially expressed lncRNAs (DElncRNAs), comprising 191 upregulated and 213 downregulated lncRNAs, w most of which were predicted to localize to the cytoplasm or nucleus. Cis-target analysis identified 52 neighboring mRNAs as putative targets of 46 DElncRNAs. Functional enrichment highlighted mitochondrial electron transfer and redox-related processes, including the mitochondrial electron transfer flavoprotein complex, electron-transferring-flavoprotein dehydrogenase activity, ubiquinone binding, and quinone binding. In parallel, melittin induced mitochondrial membrane depolarization and increased intracellular reactive oxygen species accumulation in U14 cells. Co-expression analysis further identified 138 lncRNAs co-expressed with 161 mRNAs, which were enriched in chromatin remodeling, DNA replication, and DNA repair. EdU incorporation decreased with increasing melittin concentrations, indicating suppression of DNA synthesis and proliferative activity. RT-qPCR analysis confirmed the expression trends of selected DElncRNAs. Collectively, these findings demonstrate extensive remodeling of the lncRNA landscape in melittin-treated U14 cells and suggest that melittin-responsive lncRNA-mRNA networks are associated with mitochondrial redox disruption and impaired DNA synthesis. This study provides a transcriptomic framework for identifying candidate lncRNA-mRNA regulatory axes underlying the antitumor response to melittin.

Endophytic fungi associated with the Himalayan yew (Taxus wallichiana) represent an underexplored source of bioactive secondary metabolites. This study investigated the extracellular metabolites of Annulohypoxylon purpureonitens isolated from Nepalese T. wallichiana using bioactivity screening combined with LCMS/MS-based metabolomics. The fungal extract exhibited broad-spectrum antibacterial activity, showing the strongest inhibition against Staphylococcus aureusand Enterococcus faecalis (MIC = 500 ug/mL). It also displayed notable antioxidant capacity(DPPH, ABTS, TPC &TFC) and cytotoxicity against HeLa and MCF-7 cancer cell lines. Metabolite profiling via GNPS molecular networking, manual MS/MS validation, and MASST reverse metabolomics putatively identified diverse compounds, including hydroquinidine, chlorogenic acid, muramic acid, and cordycepin conjugates widely distributed across public microbial datasets. Overall, A. purpureonitens is a promising source of multifunctional metabolites, laying a foundation for future compound isolation and functional characterization.

Eukaryotic translation initiation is tightly regulated by interactions among translation initiation factors (eIFs) that ensure accurate start codon selection. The translation regulator, eIF5 mimic protein 1 (5MP1) contributes to this process by competing with eIF5 for binding to eIF2, thereby increasing the stringency of translation initiation. Despite its important regulatory role and emerging involvement in tumorigenesis, structural information on human 5MP1 remains limited. Here, we report the near-complete backbone and partial side-chain NMR resonance assignments of the C-terminal domain of human 5MP1 (residues 250-419), carrying a W404E substitution that disrupts dimerization. The WT protein forms a dimer at NMR concentrations, which increases the effective size of the protein and also causes disappearance of peaks corresponding to aminoacids at the dimer interface due to conformational exchange. Backbone resonance assignments were completed for 96.4% of the non-proline residues. Secondary structure was analyzed using Chemical Shift Index (CSI) and compared with the AlphaFold structural model. Regions of disagreement between the experimental and computational secondary structure assignments were further examined using 15N-NOESY-HSQC spectra, allowing experimental validation of local structural features. While the AlphaFold model accurately reproduces the overall fold of the 5MP1 C-terminal domain, several localized discrepancies were identified, particularly near the N- and C-terminal regions of the domain, where experimental NMR data support alternative secondary structure assignments. These resonance assignments and experimentally validated structural features provide a foundation for future investigations of the molecular interactions, dynamics, and functions of 5MP1 in translation initiation.

Plant-derived small molecules possess highly diverse physicochemical properties, and the computational design of their protein recognition elements depends not only on the global structural quality of candidate backbones, but also on whether the local binding pocket, ligand-contact pattern, and predefined recognition conformation can be consistently retained after sequence design and structural back-prediction. To explore pocket-design strategies for different types of natural-product small molecules, this study selected capsaicin, (4R)-limonene, and quercetin as model ligands, representing a flexible amphipathic molecule, a compact hydrophobic monoterpene, and a rigid polyphenolic flavonoid scaffold, respectively, and covering the dimensions of pungent sensory flavor, volatile aroma, and flavonoid functional constituents. A ligand- physicochemical-property-guided computational design and multi-stage prioritization framework was established for candidate protein binders. The results showed that candidates with favorable initial global structural scores did not necessarily form reasonable local small-molecule binding pockets, indicating that evaluation of the local ligand environment is essential for candidate prioritization. After screening, 31 partial- pocket candidate backbones for capsaicin, 75 buried hydrophobic-pocket candidate backbones for (4R)-limonene, and 56 pocket-qualified candidate backbones for quercetin were obtained. Further sequence design and structural back-prediction analyses indicated that a subset of candidates could maintain the original pocket geometry and major ligand-contact patterns after sequence realization. Overall, these results suggest that the physicochemical properties of different plant-derived small molecules substantially influence the efficiency of de novo protein pocket formation, with compact hydrophobic ligands being more compatible with buried hydrophobic- pocket strategies, whereas flexible or multipolar ligands require a more refined balance between hydrophobic burial and polar exposure. This study provides a pre- experimental computational prioritization framework for natural-product small- molecule-recognizing proteins and offers candidate resources for subsequent protein expression, in vitro binding validation, active-constituent enrichment, and development of small-molecule biorecognition tools. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/743643v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@8fe6c2org.highwire.dtl.DTLVardef@176cef2org.highwire.dtl.DTLVardef@10c8201org.highwire.dtl.DTLVardef@2b28cf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Antisense oligonucleotides (ASO) are nucleotide polymers that hybridize to sense strands and have been successful in treating a variety of diseases. A wide range of strategies have been investigated to optimize and develop ASO for clinical studies. A key objective for this study was to provide an overview of the range of detailed data that get be obtained and provide an updated method review on how to design surface plasmon resonance (SPR) kinetic experiments for DNA oligonucleotide hybridization studies that can also be applied to other ASO including peptide nucleic acids (PNA). We describe many lessons learned from published literature and provide a state-of-the-art strategy and methods for generating not only kinetic but also thermodynamic characterizations of oligonucleotide hybridization. In this study we have performed an SPR kinetic and thermodynamic analysis for the hybridization of HIF1 antisense DNA strands to its immobilized Intron2-Exon3 splice site sense DNA strand to provide insight, in general, on the optimal length and insight into optimal design of DNA ASOs. We provide a process on how to design experiments to: 1.) obtain oligonucleotide-length dependent kinetics, 2.) analyze reactions to obtain association and dissociation rate kinetics (ka, kd), assess if hybridization follows a 2-state model and to obtain kinetic dissociation constants (Kd), 3.) perform temperature-dependent hybridization kinetics to obtain thermodynamic values ({Delta}H{degrees}, {Delta}S{degrees} and {Delta}G{degrees}) that can give insight into the molecular interactions driving hybridization, 4.) compare experimental thermodynamic values to values derived from nearest-neighbor prediction models to identify atypical reactions and importantly 5.) enable calculations to predict oligomer hybridization affinity at the physiological 37 {degrees}C temperature to asses if the design of the oligomer will have the required cellular activity for a therapeutic effect. The strategy and results presented throughout the paper are compared to previous SPR reports and suggestions made to optimize kinetic studies.

Accurate assessment of ligand coordinate-density consistency across different resolutions remains challenging in macromolecular crystallography. We introduce the atomic Box Correlation Coefficient (aBCC), an atom-level metric for evaluating the consistency between ligand atomic coordinates and electron density in a resolution-standardized framework. To predict aBCC values from electron-density maps, we developed QAEmap, a machine-learning model based on three-dimensional convolutional neural networks (3D-CNNs). The model was trained using Fourier-truncated electron-density maps and corresponding ligand coordinates generated from high-resolution structures in the Protein Data Bank. It was evaluated using both Fourier-truncated electron-density maps and experimentally determined PDB structures. was evaluated using both Fourier-truncated electron-density maps and experimentally determined PDB structures.The prediction accuracy gradually decreased with decreasing resolution, but remained reliable up to [~]3.5 [A]. These results demonstrate that aBCC enables resolution-standardized atom-wise evaluation of coordinate-density consistency across different resolutions and provide a foundation for further development and refinement of machine learning-based coordinate validation. SynopsisWe introduce the atomic box correlation coefficient (aBCC), a machine learning-based metric for the resolution-standardized atom-level evaluation of ligand coordinate-density consistency in crystallographic structures. aBCC provides a common framework for assessing and communicating the local coordinate reliability between structural biologists and researchers in structure-based drug discovery.

Many functional RNA motifs adopt structures that deviate from the canonical A-form helix and are emerging targets for RNA-directed therapeutics. The microtubule-associated protein tau (MAPT) A-bulge motif (5'-GCAGU/5'-ACGU) is one such motif. Because its structure is stabilized by a delicate balance of local interactions, its accurate modeling remains a major challenge for molecular dynamics (MD) simulations. The experimentally determined nuclear magnetic resonance (NMR) structure of the MAPT A-bulge motif provides a stringent test of whether RNA force fields can accurately reproduce the experimentally observed conformation. Most current AMBER-family RNA force-field models have incorrectly favored a non-native base-triple state of the MAPT A-bulge motif over the experimentally observed stacked state. Structural comparison of the stacked and base-triple conformations revealed that overly favorable NH-N hydrogen bonds between the bulged adenosine and an adjacent Watson-Crick base pair were the primary source of this imbalance. We developed gHBfix-18Ab, an 18-component hydrogen-bond correction that distinguishes NH and NH2; donors. gHBfix-18Ab was combined with the previously developed OL3CP and NBfix0BPh corrections to generate the composite model gHBfix-18Ab*. This model restored the experimentally observed stacked state as the global minimum in the calculated free-energy profile and improved agreement with NMR-derived distance data for the A-bulge region. Importantly, gHBfix-18Ab* did not produce marked structural destabilization of the cUUCGg tetraloop, a widely used benchmark for RNA force-field validation, suggesting that the refinement preserves the stability of the unrelated RNA motif. These results demonstrate that targeted refinement of hydrogen-bond interactions provides a practical strategy for systematic improvement of RNA force fields toward more accurate modeling of noncanonical RNA motifs.

Background: Natural compounds from avocado fruit (avocadene, avocadyne, and acetate derivatives) exhibit notable biological activity, although their molecular mechanisms remain unclear. The avocado-derived lipids exert potent nematocidal activity against several parasitic nematodes. In Caenorhabditis elegans (C. elegans), those compounds caused concentration-dependent toxicity, impairing first stage larval growth, egg hatching, and adult survival. Treated worms exhibited impaired mitochondrial respiration, reduced oxygen consumption, and elevated reactive oxygen species. These effects suggest that avocado lipids disrupt mitochondrial function and lipid metabolism, in part by inhibiting acetyl-CoA carboxylase, the rate-limiting enzyme of fatty acid biosynthesis. Methods: We investigated the effects of these compounds on the lipid profile of C. elegans and their association with endogenous lipid pools using NMR spectroscopy, click-chemistry-based fluorescence labeling, thin-layer chromatography (TLC), and microscopy. Results: Lipidomic analysis of stage 4 larvae (L4) and embryos treated with avocadene acetate revealed increased lipid NMR signals. Fluorescence-assisted TLC and NMR further suggested that avocadyne preferentially associates with triglyceride-linked fatty acids, particularly monounsaturated and flexible polyunsaturated chains, without detectable interactions with conformationally-constrained polyunsaturated species. Fluorescent avocadyne derivatives were efficiently internalized with distinct localization patterns in L4 larvae and embryonic cells. Conclusions: Overall, the lipid homeostasis remodeling of L4 larvae in response to lipotoxic shock was associated with phospholipid increase and remarkable lipid droplets onset, whereas embryos showed accumulation of lipids in enlarged droplets and developmental arrest.

Objective White smoke inhalation injury (WSI) causes severe acute lung damage with no specific therapy currently available. Sphingolipid metabolism is implicated in pulmonary inflammation, but its transcriptional regulatory landscape in WSI remains unexplored. This study aimed to identify key sphingolipid metabolism related genes and evaluate their regulatory roles and therapeutic potential in WSI. Methods We established a rat model of WSI and performed integrated bulk RNA sequencing, weighted gene coexpression network analysis (WGCNA), and single-cell RNA sequencing (scRNAseq) to screen for differentially expressed sphingolipid metabolism-related genes (DESRGs). Protein-protein interaction (PPI) network with four centrality algorithms was used to prioritize hub genes. In silico gene knockout and molecular docking were conducted to assess regulatory functions and identify potential drug candidates. Results We identified 22 DESRGs that were predominantly enriched in DNA replication and cell cycle pathways rather than canonical sphingolipid metabolic processes. PPI consensus prioritized three hub genes--Top2a, Ttk, and Ccna2--with Top2a exhibiting the highest expression in epithelial cells and significant downregulation after smoke exposure. ScRNAseq revealed immune cell infiltration and epithelial differentiation trajectories. Virtual knockout showed that Top2a depletion affected the largest transcriptomic fraction (~0.4%) and was enriched in lysosome biogenesis, innate immunity, phagocytosis, and lipid catabolism. Molecular docking identified thalidomide as a high affinity ligand for Top2a (Vina score: -8.5 kcal/mol). Conclusion Our multiomics integrative framework identifies Top2a as a central regulatory hub linking sphingolipid associated inflammation to epithelial responses in WSI, and nominates thalidomide as a potential drug repurposing candidate. These findings provide prioritized targets for future translational investigation.

The High Mobility Group Box 1 (HMGB1) protein performs multiple essential functions in the body, ranging from DNA regulation to the activation and mediation of immune responses. However, HMGB1 has been also implicated in several pathological conditions, such as rheumatoid arthritis, sepsis, autoimmune diseases, tumors, and Alzheimer's disease. As a result, HMGB1 is of increasing interest as a therapeutic target. Binding to heparin has been reported to inhibit HMGB1's pathological activity during sepsis in clinical settings. In this work, we compare the interactions of HMGB1 with heparin and its' synthetic analog linear polyglycerol sulfate (lPGS) from the viewpoint of stability and changes to association behavior. This analysis focuses on thermal stability, secondary-structure changes, and particle-size evolution using nano-differential scanning fluorimetry (nanoDSF), circular dichroism spectroscopy (CD), and dynamic light scattering (DLS).