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for thermodynamics and kinetics while presenting molecular dynamics and various spectroscopic methods in a lacking or outdated way.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.

Amyloid fibrils are traditionally associated with protein misfolding disorders; however, increasing evidence indicates that they can also perform beneficial biological functions, including antimicrobial defense. Here, we investigated whether structurally distinct amyloid polymorphs of hen egg white lysozyme (HEWL) exhibit enhanced antibacterial activity compared with the native protein. HEWL was converted into two amyloid polymorphs, flexible fibrils (FFs) and rigid fibrils (RFs), and their antibacterial activities were evaluated against the Gram-positive bacterium Staphylococcus aureus and the Gram-negative bacteria Escherichia coli (Top10) and Salmonella Typhimurium. Fibril formation was confirmed by circular dichroism (CD) spectroscopy, thioflavin T (ThT) fluorescence, and transmission electron microscopy (TEM), demonstrating morphologically distinct amyloid assemblies with different secondary-structure organizations. Fluorescence-based bacterial growth assays showed that native HEWL exhibited only moderate antibacterial activity, whereas both amyloid polymorphs produced potent, concentration-dependent bacterial growth inhibition. FFs and RFs consistently displayed greater antibacterial efficacy than native HEWL across all tested strains, with FFs exhibiting slightly stronger activity against S. Typhimurium. At concentrations of 600-800 M, FFs achieved >90% growth inhibition for all bacterial species examined. Cytotoxicity studies using SH-SY5Y human neuroblastoma cells demonstrated minimal toxicity for native HEWL, modest effects for FFs, and substantially greater toxicity for RFs, indicating that amyloid polymorphism influences both antimicrobial activity and mammalian cell compatibility. Collectively, these findings establish a direct relationship between amyloid structure, antibacterial efficacy, and cytotoxicity. The combination of potent antibacterial activity and relatively low cytotoxicity identifies FFs as a promising functional amyloid biomaterial for the development of next-generation antimicrobial materials.

Erythrocytosis, a disorder with increased erythrocyte production, has a heterogeneous aetiology, including rare congenital types linked to dysregulation of the oxygen-sensing pathway. Variants in the EGLN1 gene, encoding the prolyl hydroxylase that regulates hypoxia-inducible factor (HIF) stability, are associated with familial erythrocytosis type 3 (ECYT3). In patients with idiopathic erythrocytosis we previously identified two novel EGLN1 variants, c.1072C>T (p.(Pro358Ser)) and c.1124A>G (p.(Glu375Gly)), classified as variants of uncertain significance. Herein, we performed in silico and in vitro analyses to assess their structural and functional effects, using the known pathogenic variant p.(His374Arg) as a positive control. AlphaFold3 predictions revealed minimal conformational changes in the protein core for all variants, while stability predictions suggested reduced protein stability. Functional assays in HEK293 cells demonstrated significantly decreased protein levels and stability for p.(Pro358Ser) and p.(Glu375Gly), comparable to p.(His374Arg). However, luciferase reporter assays showed that, unlike p.(His374Arg), the novel variants did not substantially impair EGLN1 enzymatic activity or activate HIF signalling. Our results suggest that the novel variants may contribute to erythrocytosis through destabilization of EGLN1, supporting further studies to elucidate their precise impact on hypoxia regulation. This study highlights the complexity of studying EGLN1 variants and the importance of functional evaluation for clinical interpretation.

Multiple-drug resistant (MDR) Staphylococcus aureus strains (like methicillin-resistant S. aureus or MRSA) uses an arsenal of antioxidant enzymes to mitigate host-induced oxidative stress. Among them the non-canonical Staphylococcal glutathione peroxidase (SaGpx) plays a crucial role in bacterial redox homeostasis by reducing peroxides via thioredoxin-dependent pathways. Thus, enabling oxidative stress mitigation during host infection. Despite its importance in S. aureus, its role in bacterial pathogenesis remains unexplored. This study aimed to elucidate the possible role of SaGpx in Staphylococcal virulence. First, we determined the high-resolution crystal structure of SaGpx (at 1.65 [A] resolution) using X-ray crystallography. Guided by the catalytic cleft architecture of SaGpx, small-molecule based inhibitors were then rationally designed and synthesized. These inhibitors exhibited good binding affinity to SaGpx and complete enzymatic blockade. These inhibitors exhibited potent anti-S. aureus activity (MICs 6.25-31.25 M) along with no cytotoxicity in L929 fibroblast wound-healing assays. Furthermore, the in vivo antibacterial ability of these inhibitors was evaluated using S. aureus-infected skin wound mouse model, where these compounds show potent antibacterial and wound healing ability supported by subsequent histological as well as immunohistochemical analysis. These findings suggest SaGpx as a possible virulence determinant in S. aureus and position these synthesized inhibitors as promising antivirulence therapeutics. HighlightsO_LIThe high-resolution crystal structure of Staphylococcal glutathione peroxidase is solved. C_LIO_LIBased on the SaGpx catalytic site, ,{beta}-unsaturated ketoesters derivatives are synthesized. C_LIO_LISynthesized ,{beta}-unsaturated ketoesters derivatives inhibit SaGpx activity and binds the protein at M range. C_LIO_LISynthesized ,{beta}-unsaturated ketoesters derivatives show in vitro antibacterial activity against S. aureus at low M range. C_LIO_LISynthesized ,{beta}-unsaturated ketoesters derivatives show in vivo antibacterial and wound healing ability S. aureus-infected skin wound mouse model. C_LI

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.

Engulfment and Cell Motility protein 1 (ELMO1) regulates cell migration, phagocytosis, and cytoskeletal remodeling, positioning it as a compelling therapeutic target across kidney diseases, oncology, enteric infections and inflammation. Despite this potential, no approved therapeutics or clinically validated small-molecule modulators of ELMO1 currently exist. ELMO1 functions by forming a complex with DOCK180 (or DOCK2) to activate the small GTPase Rac1, and the recent structural resolution of the ELMO1/DOCK2 complex now provides an opportunity to target this protein-protein interface directly. Here, we present the first investigation into the druggability of the ELMO1/DOCK2 complex and report the initial virtual screening to identify small-molecule inhibitors of this interaction. Molecular dynamics (MD) and free energy level (FEL) studies were carried out to validate the potential of the predicted hits. This work establishes a computational framework for the development of the first generation of ELMO1-targeted therapeutics. In addition to demonstrating the drugability of ELMO1, this work introduces two open-source Python tools for the rapid analysis and visualization of protein-protein interaction and ligand-protein MD trajectories from DESMOND output files. These tools are designed to be broadly accessible, offering practical utility to the wider DESMOND user community.

Predicting the location of metal-binding sites in proteins is crucial for fundamental biological questions and biotechnological applications. Over the past decade, the rise in metal-bound protein structures in the Protein Data Bank, combined with advanced statistical models such as deep learning, has accelerated the development of metal-binding site prediction tools. Several approaches are now available, offering high-quality benchmarks and predictive performance. Our initial development in this area is BioMetAll, whose first version was based on backbone pre-organization. Here, we introduce its second version, featuring two major updates: 1) metal-specific scoring functions and 2) prediction using backbone geometry alone or in combination with first coordination sphere descriptors. Apart from demonstrating metal sensitivity and yielding better benchmarking results, this new version allows the assessment of the influence of considering the metals first coordination sphere versus backbone pre-organization on how metallic species bind to proteins.

The widespread use of synthetic food dyes, such as Acid Yellow 23 (AY 23), in the food, cosmetics, and pharmaceutical industries raises questions about their potential effects on biological systems and public health. The concentration-dependent interaction between AY 23 and bovine serum albumin (BSA), a crucial model protein for understanding pharmacokinetics and protein-ligand behaviour, was examined in this study. We demonstrate that, under physiological conditions, increasing dye concentrations from 50 M to 200 M results in notable conformational changes, increased surface hydrophobicity, and protein aggregation using a multimodal biophysical approach that includes fluorescence spectroscopy. Direct visualisation verified these structural changes and aggregate formation, whereas hemolytic assay confirmed the high hemolytic nature of AY 23-induced fibrils. Additionally, this study provides a mechanistic basis for the toxicological effects of AY 23, underscoring the implications of food dyes for public health.

Protein-RNA complexes drive fundamental cellular processes such as transcription and translation. Despite the prevalence and importance of protein-RNA interactions, the field lacks reliable and accessible methods to quantify the energetic favorability of these interactions. We propose an experimentally tuned protein-RNA score function that can be directly implemented into ROSETTA. Fine-tuning these score functions for predictive tasks requires repeated evaluations on a set of protein-RNA complexes, which can be computationally expensive given the number of parameters to tune. We used Bayesian Optimization to efficiently improve the energetic agreement between ROSETTA and experimentation. We observe significant interactions for specific RNA subclasses, serving as further confirmation of the physical validity of the score function. Beyond protein-RNA interaction prediction, we establish a framework to efficiently fine-tune ROSETTA score functions for any protein-class interaction using Bayesian Optimization. TOC FIGURE O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/739244v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@700559org.highwire.dtl.DTLVardef@6f4ca6org.highwire.dtl.DTLVardef@11157c0org.highwire.dtl.DTLVardef@1981456_HPS_FORMAT_FIGEXP M_FIG C_FIG

Melittin, the principal bioactive peptide of bee venom, exhibits promising antitumor activity, whereas its molecular mechanisms in cervical cancer remain incompletely understood. In this study, the biological effects and molecular responses of melittin in U14 cervical cancer cells were investigated using Astral data-independent acquisition (Astral-DIA)-based quantitative proteomics combined with molecular validation. The effects of melittin on cell migration, invasion, and cell death were evaluated by Transwell assays and PI/Hoechst staining. Differentially expressed proteins (DEPs) were screened and subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses. Representative oxidative stress-related genes and proteins were further validated by RT-qPCR and Western blotting. Melittin significantly inhibited the migration and invasion of U14 cervical cancer cells and increased cell death. Quantitative proteomics identified 9,782 protein groups and 187 DEPs, including 71 up- and 116 down-regulated proteins. KEGG pathway enrichment analysis revealed oxidative phosphorylation (OXPHOS) as the most significantly enriched pathway, together with glutathione metabolism, ferroptosis-related pathways, reactive oxygen species signaling, and mitophagy. GO term enrichment analysis indicated that DEGs were mainly engaged in mitochondrial function, electron transport, oxidoreductase activity, and energy metabolism. RT-qPCR assay demonstrated altered expression of Duox1, Gpx4, Gsx2, Nfe2l2, and Gstp2. Additionally, PPI analysis identified Gstp2 and ODC1 as representative hub proteins involved in redox regulation and metabolic adaptation. Furthermore, Western blotting confirmed increased GSTP2 expression following melittin treatment. Overall, these findings provide a comprehensive proteomic landscape of melittin-treated U14 cervical cancer cells and suggest that mitochondrial OXPHOS remodeling and redox-associated pathways may contribute to the antitumor activity of melittin.

Survival analysis in head and neck squamous cell carcinoma (HNSCC) is traditionally performed using Cox proportional hazards models, alongside some exploration into black-box machine learning methods. The Super Learner (SL) algorithm addresses this model selection dilemma by combining diverse candidate algorithms into a weighted ensemble to perform comparably to the best candidate method. This study evaluates the performance of SL in HNSCC. Proteomic features as well as clinical covariates from 96 CPTAC HNSCC samples were modeled with three candidate algorithms (Cox LASSO, Cox Ridge, and Random Survival Forest) as well as the ensemble SL method. Models were optimized via Unos time-dependent Concordance Index (C-index) and tested at 1- and 3-year time horizons using 2000 bootstrap resamples. The Cox Ridge regression model achieved the highest predictive accuracy among the four total methods. However, the SL demonstrated stable performance over both time horizons (1-year C-index: 0.985; 3-year C-index: 0.960). Variable importance analysis of the Cox Ridge model successfully identified malignant proteins (ATR, MAML1, MIEN1) alongside novel potential prognostic indicators (ZNF800, KERA). This analysis emphasizes the statistical necessity for larger cohorts for ensemble learning, while providing a benchmark of proteomic indicators in HNSCC.

Cancer of the uterine corpus is the fourth leading cancer and the fifth leading cause of cancer-related death in women in the United States. Chemotherapeutic resistance, specifically platinum-resistance, contributes to this problem. Therefore, an alternative treatment regimen is required. Using inorganic copper oxide nanoparticles (CuO NPs), we evaluated cancer cell responses indicative of anti-neoplastic activity. CuO NPs were characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), dynamic light scattering (DLS) and laser Doppler velocimetry (LDV). The nanoparticles were rod-like and had a diameter of 70 {+/-} 30 nm and a copper content ranging from 77% - 82.6%. The hydrodynamic diameter and the zeta potential significantly decreased with more particles in solution. These materials were also used in four endometrial cancer cell lines and one cervical cancer cell line to evaluate cell viability, apoptosis, migration, and reactive oxygen species. In endometrial cancer cell lines, the IC50 values ranged from 1.028 ug/mL in HEC-1A cells to 73.62 ug/mL in Ishikawa cells, indicating that different cells have vastly different responses to CuO NPs. The results also indicated cell line-dependent differences in apoptosis, oxidation potential, and migration. Further, the cervical cancer cell line was modified using CRISPR technology to highlight a common germline mutation that causes earlier onset and more aggressive cancer progression. These genetic mutations resulted in differences in a loss of redox potential without observable changes in apoptosis or migration. The results of these studies indicate that CuO NPs elicit effects dependent upon the stage of cancer. Anticipated long-term applications of these studies includes the potential as a target-specific anti-cancer agent, designed using knowledge at the interface of colloids and the tumor environment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/729888v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1e0fe68org.highwire.dtl.DTLVardef@5e776dorg.highwire.dtl.DTLVardef@1f2aad6org.highwire.dtl.DTLVardef@add7fc_HPS_FORMAT_FIGEXP M_FIG C_FIG Copper oxide nanoparticles (CuO NPs) were characterized upon receipt using electron microscopy, elemental analysis, dynamic light scattering, laser Doppler velocimetry, and Fourier-transform infrared spectroscopy. These CuO NPs were exposed to HeLa cells with and without DNA mismatch repair deficiencies to assess the impacts on cancer cell migration, apoptosis, and redox potential.

Production of recombinant proteins frequently yields inclusion bodies that must undergo refolding to yield active protein. Here, we optimized the refolding conditions for the recombinant leucyl aminopeptidase (rPepL) from Lactocaseibacillus casei expressed in inclusion bodies from E. coli. Several chemical additives were assessed for how well they facilitated an increase in refolding efficiency. The best, 0.5 M L-arginine, yielded 50.8% refolding. The addition of stabilizers, such as sucrose and glycerol, with L-arginine further increased yields to 85%. Urea at lower concentrations (0.25-0.5 M) also facilitated an increase in the refolding yield when co-added with L-arginine, whereas guanidinium chloride inhibited it. Sugars and polyols exhibited dose-dependent effects, with ranges for optima also defined. Fluorescence spectroscopy verified enhancements in the refolding under the optimized conditions. Molecular dynamics simulation under mixed solvent conditions provided atomic insights about stabilizing interactions that are likely to facilitate increased refolding. The results show that a series of aggregation suppressors and protein stabilizers can, in a collaborative way, increase the refolding efficiency for the recombinant proteins from the inclusion bodies. The protocol with the optimization using the additives L-arginine, sucrose, and glycerol is an efficient method for the production of active rPepL. This article outlines the best refolding method to recover recombinant leucyl aminopeptidase from inclusion bodies of E. coli using L-arginine combined with sucrose and glycerol. The combined experimental observations and computational simulations elucidate the molecular process of additive-induced stabilization, which elucidates how aggregation inhibition and hydrogen-bonded stabilization act synergistically. The results presented herein answer both mechanistic understanding and experimental guidance for improving protein refolding.

Members of the transforming growth factor-{beta} (TGF-{beta}) superfamily, including inhibins and activins, are structurally related glycoprotein dimers that regulate reproductive and endocrine signaling. Their high degree of molecular similarity presents challenges for label-free analytical discrimination. To evaluate the ability of Raman spectroscopy to distinguish closely related TGF-{beta} superfamily proteins based on intrinsic vibrational fingerprints. Raman spectra of recombinant human Inhibin -subunit, Inhibin B ({beta}B homodimer), and Activin A ({beta}A--{beta}A) were acquired using confocal Raman microscopy with 532 nm excitation. Spectra were baseline-corrected, area-normalized, and analysed using principal component analysis (PCA). Distinct spectral signatures were observed across the 500--1800 cm-1 region. Differences within the S--S stretching region (500--550 cm-1) were consistent with variations in disulfide-bond environments, with the Inhibin -subunit exhibiting the highest relative intensity in this region. Variations in the amide I band (1600--1700 cm-1) suggested differences in protein secondary structure, while aromatic amino acid vibrations provided additional discriminatory features. PCA revealed clear clustering and separation of all three protein classes based on their Raman fingerprints. Raman spectroscopy enables label-free differentiation of structurally related endocrine glycoproteins and demonstrates potential for the structural characterization and classification of inhibin and activin proteins within the TGF-{beta} superfamily.

Lysolipin I (1) is a highly bioactive xanthone with strong antibacterial and cytotoxic properties. Given the limited number of lysolipin analogues, discovery of new natural lysolipin derivatives is important for understanding their structure-activity relationships. A soil-derived Streptomyces sp. P8-2B18 harbors a putative lysolipin biosynthetic gene cluster and LC-MS based metabolomic analysis revealed the production of lysolipin I along with unreported analogues. Large-scale fermentation followed by isolation led to the discovery of four new analogues, lysolipins J-M (2- 5), the structures of which were elucidated by mass spectrometric and NMR spectroscopic data analyses. Lysolipin L features a five-membered lactam F ring, which was unprecedented in reported lysolipins. Lysolipin M has a novel skeleton, with an extra methyl (Me-36) and a glycosyl group replacing a 1,3-oxane ring in lysolipin I. While lysolipins I, J and K displayed strong activity against Staphylococcus aureus and Aspergillus flavus with MIC values ranging from 0.25 to 4 g/mL and lysolipin L showed only moderate activities, lysolipin M was inactive (>50 g/mL). Lysolipins I-K showed potent cytotoxic activity against prostate cancer cell lines LNCaP and C4-2B, with IC50 values in the submicromolar range. In contrast, lysolipin L exhibited no cytotoxicity and lysolipin M exhibited substantially reduced potency. Their broad, non-selective bioactivities restricted their applicability as therapeutic agents.

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.

In a recent study of a mice model it was suggested that after myocardial infarction Serum Amyloid A (SAA) aggregates are formed that contribute to the long-term complications of the infarct, and that a similar mechanism may exist for humans. Motivated by this hypothesis we have designed four peptide candidates that may interfere with formation of SAA3 fibrils, and using all-atom molecular dynamics have evaluated their ability to destabilize SAA fibrils. As the lifetime of peptide drugs can be increased by replacing L-amino acids with their mirror D-amino acids, we have built the peptides from D-amino acids. We identify two of these peptides, DRI-R5S and DRI-H6A, as promising drug candidates.