Acta Pharmaceutica Sinica B

CC10137 is a first-in-class peripherally restricted 2A-adrenergic receptor (2AAR) agonist with broad-spectrum analgesic efficacy and a favorable safety profile. Systematic exploration of the chemical space surrounding first-in-class leads is important for defining series boundaries and guiding continued optimization, but conventional analogue-by-analogue medicinal chemistry samples only a small fraction of the accessible structural space. Here, we used a scaffold-seeded enumeration strategy to expand the chemical space surrounding CC10137 from four SAR-informed seed compounds comprising CC10137 and three closely related structural variants. Application of predefined medicinal chemistry transformation rules in StarDrop generated a virtual library of 16,601,163 unique structures. Morgan fingerprint-based principal component analysis indicated that the library occupied a highly multidimensional structural space involving variation in scaffold substitution, peripheral functional groups, and side-chain composition. A retrospective comparison set of 43 compounds independently designed and experimentally characterized in the earlier CC10137 program represented only approximately 0.00026% of the 16.6-million-member library, yet all 43 were recovered as exact structural matches. Three compounds selected directly from the virtual library retained 2AAR binding affinity and agonist potency below 25 nM. Five representative compounds further showed significant anti-allodynic effects in the in vivo spared nerve injury model, with inhibition rates ranging from 39.3% to 55.7%. These findings support scaffold-seeded computational enumeration as a practical strategy for systematic chemical-space mapping around a first-in-class lead and for identifying additional pharmacologically active structural regions for further optimization.

Allosteric modulation of G protein-coupled receptors (GPCR) is a rapidly advancing area of drug discovery with considerable therapeutic potential. In this study, we used various bioluminescence resonance energy transfer (BRET) assay configurations to investigate the differential activity of LY3154207, a dopamine D1 receptor (D1R)- positive allosteric modulator (PAM), in potentiating D1R-mediated signaling pathways. Our data showed that LY3154207 demonstrated clear bias toward {beta}-arrestin recruitment over G-protein engagement. Among the G-protein subtypes, LY3154207 preferentially potentiated Gs signaling induced by DA. Interestingly, when tested for its effect on the Gs-selective D1R agonist DHX and the Golf-selective agonist TAV, LY3154207 further enhanced the selectivity of these compounds, suggesting a probe-dependent effect. We also studied the structural mechanism underlying this subtype selectivity and found that W123 and R130 in the intracellular loop 2 (ICL2) of D1R were crucial for the activity of LY3154207. Furthermore, the N domain of the G-protein appeared to make minor contributions to this G-protein subtype selectivity of LY3154207. Lastly, our data demonstrated that LY3154207 induced cAMP production in the absence of the orthosteric ligand, indicating that this compound is an ago-PAM.

The classical estrogen receptor (ER) is a steroid hormone receptor known for its role in both health and disease. ER, like its counterpart ER{beta}, acts as a receptor for its endogenous ligand 17{beta}-estradiol (E2) and is capable of binding a diverse set of natural and synthetic small molecules. Several screening campaigns have identified various ER ligands, based on the oxabicyclo[3.3.1]-nonene scaffold, that act as ER agonists. One such campaign extensively characterized an oxabicyclic ER agonist, termed AB-1. Herein, we report the synthesis of a series of analogs based on the scaffold of AB-1 (herein termed 1), focusing on the enhancement of their binding to ER and functional potencies in ER mediated assays. We identify a new substituted compound 9 that achieves subnanomolar potencies for ER binding (IC50= 0.45 nM) and ER dependent transcription (EC50= 0.37 nM) and proliferation (EC50= 0.03 nM), with potencies approaching those of E2. The high potency of 9 provides a promising scaffold for the potential development of new ER-targeted therapeutics.

Psoriasis is a chronic skin disease characterized by red, scaly plaques mainly driven by dysregulated T cells that induce keratinocytes (KCs) proliferation and inflammation. Despite significant advancements in disease management through biologics and topical therapies, these treatments offer only temporary relief and fail to prevent disease recurrence. Considering the current therapeutic needs, we described herein a novel small molecule TEM1657, derived from 3,5-dicaffeoylquinic acid with anti-inflammatory potency in imiquimod-induced psoriasis mouse model as well as in Th17-stimulated KCs. Mechanistically, its action is mediated through modulation of mitochondrial dynamics, specifically via OPA1, an inner mitochondrial membrane protein that alters mitochondrial calcium influx, and further impacts cellular bioenergetics. Moreover, TEM1657 rapidly suppresses transcription of NFKBIZ and various other psoriasis-associated genes. These observations highlighted a pathway that represents an innovative target in psoriasis and other NFKBIZ-related disorders.

MAPK-activated protein kinase 2 (MAPKAPK2, MK2) is a downstream substrate of p38 MAPK that regulates inflammatory signaling and cytokine synthesis, making it an attractive therapeutic target. Although several crystal structures of MAPKAPK2 with ATP-competitive inhibitors have supported drug discovery, structural elucidation of selective non-ATP-competitive inhibitors has remained challenging. MK-25 is a non-ATP-competitive furan-2-carboxamide MAPKAPK2 inhibitor developed at Merck to overcome the selectivity and cellular-efficacy limitations of ATP-competitive chemotypes. Here, we show through isothermal titration calorimetry that MK-25 binds the activated MAPKAPK2, consistent with state-dependent allosteric binding. To determine the binding mode of MK-25, we solved a 2.8 A resolution crystal structure of an activated MAPKAPK2 construct in ternary complex with the ATP-site inhibitor PF-3644022 and a bromo-analogue of MK-25. The ligand occupies a pocket in the C-lobe overlapping the protein-substrate recognition region and formed through rearrangements of D and G helices and the activation segment. These interactions are consistent with the structure-activity relationships reported for the furan-2-carboxamide chemotype and identify a ligandable allosteric pocket that may facilitate future structure-guided design of selective, non-ATP-competitive MAPKAPK2 inhibitors.

Exploring the ability of metabolic enzymes to interact with diverse small molecules can provide insights into their ligand recognition and activity regulation. Glucose-6-phosphate isomerase (GPI) is an enzyme that catalyzes the second step of glycolysis, a critical node that links glucose metabolism to other cytosolic pathways, such as pentose phosphate and hexosamine biosynthetic pathways. Despite its importance in cellular metabolism, little is known about the broad ligandability of GPI. Here, we performed a structure-based virtual screening using molecular docking to identify new modulators predicted to engage with the human GPI active site. Enzyme kinetic and binding studies confirmed eleven compounds as active-site binders of GPI, exhibiting inhibitory activities and binding affinities in upper micromolar to sub-millimolar range. The binding of several ligands to GPI active site was further supported by X-ray crystallographic data. In addition, in vitro assays were performed to evaluate the modulatory effects of the GPI hits on cellular glycolysis and viability. The identified inhibitors included the mono-phosphorylated metabolite of ribavirin, which inhibited glycolytic flux and cell viability; two compounds with phosphate bioisosteres; and endogenous phosphate-containing metabolites from the pentose phosphate, hexosamine, nucleotide, and mevalonate pathways. Collectively, these findings expanded the repertoire of human GPI ligands and revealed previously unrecognized GPI-metabolite interactions that may contribute to modulation of glycolytic flux.

Acute respiratory distress syndrome (ARDS) is marked by severe pulmonary edema and concomitant hypoxia, affecting hundreds of thousands of people a year, especially those in critical care conditions or suffering from septic shock. Previous studies have implicated that the ketogenic diet, a high-fat and low-carbohydrate diet, modulates inflammatory responses. However, the impact of the ketogenic diet on septic ARDS outcomes is unknown. Here, we demonstrated that mice on a ketogenic diet showed strikingly reduced lung injury and inflammation compared to those on a control diet during a murine model of endotoxin-induced lung injury, induced by intratracheal lipopolysaccharide (LPS) injection. Immune mass cytometry studies on lung tissue indicated that the ketogenic diet reduces immune cell infiltration. Treating mice with beta-hydroxybutyrate (BHB), the primary metabolite of ketogenesis, after the onset of ARDS reduced pulmonary edema and lung inflammation, as well as NF-kB activity, suggesting strong therapeutic potential. By multiplex analysis in bronchial alveolar lavage fluid, we observed that the ketogenic diet or BHB administration attenuates the chemotaxis and activation of immune cells. Altogether, our findings reveal that the ketogenic diet provides lung protection during endotoxin-induced lung injury through BHB.

The full efficacy range of ligands at CB1 and CB2 (i.e., inverse agonists, neutral agonists, partial agonists, full agonists, and high-efficacy agonists) has been reported collectively across numerous laboratories and assay platforms. Canonical Gi/o and {beta}-arrestin signaling have each been suggested to shape physiological effects differently via different classes of cannabinoid ligands. These prior efficacy classifications, however, were obtained in multiple assay systems, often using indirect, amplified readouts and different reference agonists, making them difficult to compare across ligands. Here we profiled a structurally diverse panel of 22 cannabinoid ligands: synthetic cannabinoid receptor agonists (SCRAs), {Delta}-tetrahydrocannabinol ({Delta}-THC) analogues, endocannabinoid analogues, and antagonists/inverse agonists at CB1 and CB2 receptors using bioluminescence resonance energy transfer (BRET) assays, measuring Gi1 engagement and {beta}-arrestin 2 recruitment and normalizing every response to the reference full agonist CP55,940. At CB1, SCRAs and {Delta}-THC analogues acted as high-efficacy agonists. At CB1, these high-efficacy agonists were also highly efficacious in {beta}-arrestin 2 recruitment. Across the panel, the most consistent trend was a loss of agonist efficacy from CB1 to CB2. Among antagonists, inverse agonists suppressed constitutive CB1 activity more than neutral antagonists. Together, these CP55,940-normalized measurements provide a common efficacy scale and a framework for interpreting pharmacodynamics of CB1 and CB2 cannabinoid receptors.

Computational safety evaluation of phytochemical libraries commonly relies on models trained on experimentally tested compounds and applied to much larger and chemically diverse collections. An important but often overlooked question is whether predicted compounds are adequately represented within the experimental chemical space underlying these models. Here, we examined this question for the Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT) database using experimentally characterized datasets for three anti-target endpoints: hERG blockade, cytochrome P450 (CYP) inhibition, and pregnane X receptor (PXR) induction. After structure standardization, 14,956 unique IMPPAT compounds were compared with 8,877 hERG, 4,905 CYP, and 4,138 PXR reference compounds using consensus nearest-neighbor similarity based on Morgan and atom-pair fingerprints. At a Tanimoto similarity threshold of 0.80, only 0.92%, 0.30%, and 0.46% of IMPPAT compounds had close measured analogs in the hERG, CYP, and PXR datasets, respectively. Relative to the internal nearest-neighbor distributions of the reference datasets, a typical IMPPAT compound lay near the 1st percentile, indicating substantial chemical-space separation. Compounds with close experimental analogs also showed distinct molecular characteristics, with descriptor-based logistic regression yielding cross-validated AUC values of 0.77-0.80. Plant-level enrichment was markedly reduced after excluding widely distributed metabolites and was further restricted when the nearest measured analog was required to have pIC50 or pEC50 [≥] 5. The remaining signals were concentrated in a limited number of taxa, including Rauvolfia, Sinopodophyllum/Dysosma, Cinchona, and Catharanthus roseus. Overall, most IMPPAT phytochemicals lack close structural representation among currently measured anti-target compounds. Computational safety predictions for these molecules should therefore be interpreted as extrapolations and accompanied by explicit measures of structural support. Absence of a close experimental analog should be regarded as a gap in available evidence rather than evidence of safety.

Thrombostasin is a cysteine-free anticoagulant protein produced by the horn fly Haematobia irritans, featuring an unusual stretch of seven consecutive aspartate residues within the polypeptide sequence. Here, we report the first chemical synthesis of native thrombostasin and a hepta-glutamate analogue, together with assessment of their thrombin inhibitory and anticoagulant activity.

Abstract Tricyclic coumarins (TCs) exhibit defensive properties against herbivorous insects and possess valuable pharmacological properties for humans. They are mainly distributed in the Apiaceae, Rutaceae, Moraceae, and Fabaceae families. The chemical structural diversity of TCs in these families primarily arises from differences in skeletal variety and attachment position of the third ring, as observed in unsaturated furanocoumarins (FCs) and saturated dihydrofuranocoumarins (DHFCs). In TC biosynthesis, the FC and DHFC pathways diverge through distinct oxidation patterns. The product specificity of the reported cytochrome P450 monooxygenase at the branching point suggests that these TC groups are produced in nearly identical ratios; however, some species of the genus Angelica (Apiaceae) accumulate DHFCs at higher levels than FCs. In this study, we investigated the enzymatic mechanism responsible for forming these two TC groups using A. keiskei, a Japanese native species used as a medicinal and edible herb. Organ-specific transcriptome analysis highlighted a P450 member CYP71AJ62 that exhibited a close correlation with TC accumulation across organs. Enzymatic characterization demonstrated that CYP71AJ62 predominantly forms a hydroxylated DHFC, vaginidiol, which may promote DHFC over FC skeletal formation in TC biosynthesis. Phylogenetic analysis suggested that CYP71AJ62 has been derived from a gene responsible for FC formation by functional shift without gene duplication. Subsequent three-dimensional structural modeling and site-directed mutagenesis revealed that two amino acid residues on substrate recognition sites cooperatively determine the product specificity of this P450 enzyme. This study provides new insights into the molecular evolutionary process underlying ring-structure diversification and, more broadly, the adaptation of plants to their environments.

COVID-19 highlighted the need for antivirals that can be rapidly deployed against both current and future coronavirus threats. CMX990 is a clinical stage coronavirus main protease (Mpro) inhibitor bearing a unique trifluoromethoxymethyl ketone warhead. Here, we broadly evaluate its pan-coronavirus target engagement, antiviral breadth, and pharmacologic differentiation. Across a reporter panel of 24 Mpro enzymes spanning alpha-, beta-, delta-, and gamma-coronaviruses, CMX990 retained robust potent activity, including against nirmatrelvir-resistant SARS-CoV-2 variants. In direct comparison, nirmatrelvir and ensitrelvir showed diminished potency against non-SARS-CoV-2 coronaviruses. Live-virus assays corroborated this breadth, with potent, selective activity against SARS-CoV-2, SARS-CoV-1, MERS-CoV, and additional human coronaviruses. Structural studies revealed a conserved covalent binding mode centered on the catalytic Cys of coronavirus Mpro. In serial-passage studies, resistance emerged only after approximately twice as many serial passages under CMX990 selection as under nirmatrelvir selection, without selecting for the canonical nirmatrelvir-resistance substitution E166V. Extracellular washout experiments revealed superior persistence of antiviral activity relative to nirmatrelvir, consistent with durable target engagement. In a murine SARS-CoV-2 infection model, once-daily CMX990 protected against weight loss and reduced lung viral titers to near baseline levels. Collectively, these findings identify CMX990 as a structurally and functionally validated pan-coronavirus protease inhibitor supporting its potential as a pandemic-ready antiviral candidate.

Objective To systematically evaluate the predictability of drug chemical structures against the complete set of MedDRA Preferred Terms (PTs), construct a comprehensive structure adverse reaction landscape, validate the utility of molecular fingerprint representations in pan-screening tasks, and establish quantitative tools for drug safety pre-screening. Methods Drug adverse event association data were compiled from SIDER 4.1 and its derivative compilation Nsider, encompassing 2,005 approved drugs, of which 1,120 small-molecule drugs with successfully retrieved chemical structures were retained for analysis. For each Preferred Term (PT) meeting the minimum sample-size threshold ([&ge;]25 positive and [&ge;]30 negative drugs; n = 768), XGBoost classifiers were trained using MACCS 166-bit fingerprints, with model performance evaluated via 5-fold stratified cross-validation. A PT was designated as high-confidence if it achieved a validation AUC [&ge;] 0.75, a cross-validation AUC [&ge;] 0.70, and passed Benjamini Hochberg false discovery rate (FDR) correction (q < 0.05). The entire analytical pipeline was replicated using Morgan ECFP4 2048-bit fingerprints to assess the robustness of fingerprint selection. The robustness of significance screening was independently validated by permutation testing (500 random label permutations), and model generalizability was evaluated through Bemis-Murcko scaffold-based stratified split validation. SHAP (SHapley Additive exPlanations) analysis was employed to identify critical structural features, and mechanism-based case studies further demonstrated concordance between model-identified features and established pharmacophores. Results Among the 768 modelable PTs, 71 (9.2%) met the high-confidence significance criteria (FDR q < 0.05), predominantly comprising nervous system disorders (10 PTs) and psychiatric disorders (9 PTs). The toxicities exhibiting the strongest structural predictability included hyperprolactinaemia (AUC = 0.968), dermatitis acneiform (AUC = 0.966), tardive dyskinesia (AUC = 0.952), and breast tenderness (AUC = 0.979). Under a unified XGBoost hyperparameter configuration, the low-dimensional MACCS fingerprint (166-bit) demonstrated near-equivalent performance to the high-dimensional Morgan fingerprint (2048-bit) in pan-screening tasks ({Delta}AUC = -0.012, Cohen's d = 0.16), and achieved comparable performance at a substantially lower dimensionality across 18 of 22 organ systems. SHAP analysis identified key structural fragments corresponding to established pharmacophores (six-membered rings, tertiary amine cores, heteroatomic bonds, and bridged heteroatomic chains), and mechanism-based case studies further demonstrated that the model captured structural patterns concordant with known pharmacophores of D2 antagonists, EGFR inhibitors, and related agents. Bemis-Murcko scaffold-based stratified split validation revealed a median AUC decrease of merely 0.042, with 66% of PTs maintaining an AUC [&ge;] 0.70 under scaffold-split conditions. Immune-mediated and multifactorial endpoints remained structurally opaque under the current data conditions. Conclusion This study constructed a comprehensive structure-adverse reaction predictability landscape encompassing 768 MedDRA PTs; seventy-one PTs achieved high-confidence criteria. The MACCS 166-bit fingerprint achieved near-equivalent performance to the Morgan 2048-bit fingerprint at a markedly lower dimensionality, and its chemically explicit features enable direct translation of model outputs into structural alerts, providing a computational tool for prospective screening of potential adverse reaction profiles for any novel compound. A tiered assessment strategy is proposed: machine learning ensemble models for high-confidence screening, substructure alert rules for high-specificity exclusion, and pharmacovigilance signal detection for complementary coverage of structurally unpredictable endpoints. Bemis-Murcko scaffold-based stratified split validation further demonstrated that the median generalization performance decrease was merely 0.042 AUC, with 66% of PTs maintaining an AUC [&ge;] 0.70 under scaffold-split conditions, corroborating the existence of a genuine chemical basis underlying structure-adverse reaction mappings.

Alkaline ceramidase 2 (ACER2) catalyzes the hydrolysis of ceramides into sphingosine and free fatty acids, playing crucial roles in regulating various biological processes, including but not limited to cell proliferation, survival, and the DNA damage response. However, a pharmacological tool that regulates its catalytic and signaling functions remains to be developed. In this study, N-[(1S,2R)-1-hydroxy-1-phenylpropan-2-yl]dodecane-1-sulfonamide (KPB82) was identified as a potent and selective ACER2 inhibitor. In vitro enzymatic assays showed that KPB82 inhibited ACER2 with an IC50 of 190 nM, while displaying minimal activity against acid and neutral ceramidases (IC50> 100 {micro}M) and no significant inhibition of alkaline ceramidase 1 or alkaline ceramidase 3. Enzymatic kinetic studies revealed that KPB82 is a competitive inhibitor of ACER2. The three-dimensional structure of ACER2 was modeled in the AlphaFold3 server, revealing key Zn2+-coordinating histidine residues and a substrate-binding pocket. Molecular docking studies demonstrated that KPB82 binds ACER2 within this pocket, forming hydrogen bonds with the catalytically important amino residues, Asp93 and His215, and interacting with several hydrophobic residues. Lactate dehydrogenase release assays revealed that KPB82 significantly reduced cytotoxicity in HeLa cells overexpressing ACER2, as well as in HCT116 cells, RT4 cells, and human umbilical vein endothelial cells treated with the DNA-damaging agent doxorubicin. Lipidomic analysis showed that KPB82 inhibited sphingosine production in response to ACER2 overexpression or doxorubicin treatment. Collectively, these findings demonstrate that KPB82 is a potent and selective ACER2 inhibitor capable of suppressing ACER2-dependent biological processes and highlight its potential as a tool for studying ceramide metabolism and ACER2-mediated signaling pathways.

The folate receptor (FR) is overexpressed in a range of human tumours including ovarian cancer cells. We propose that the overexpression of the FR on the surface of ovarian tumour cells could be exploited for the selective delivery of a DNA damage response inhibitor (DDRi) in the form of an intact folate drug conjugate (FDC). This approach would improve the therapeutic index of the parent DDRi facilitating combination studies of the DDRi-based FDC with DNA damaging chemotherapy. FR-mediated cellular uptake of the proposed folate drug conjugates is requisite for FDC selective delivery into tumours. In this study, we synthesised a series of olaparib-based folate conjugates that maintained the biochemical PARP1 inhibition associated with olaparib and showed binding affinity for the folate receptor. Significantly, we identified compounds 10b and 11 that selectively enter FR overexpressing tumour cells via folate receptor-mediated endocytosis in their intact form and engage with their target as demonstrated by the potent inhibition of PARylation (KB cells, PARylation IC50 = 5.7 and 3.9 nM; respectively).

Macrophages are critical regulators of inflammation and tissue homeostasis, yet aberrant macrophage activation contributes to a wide spectrum of inflammatory and malignant diseases. Therapeutic strategies that directly reduce macrophage numbers have shown promise, but macrophage survival pathways remain incompletely defined, limiting the development of targeted therapeutic strategies. Here, we establish a high-throughput screening platform to identify small molecule inhibitors that impair macrophage survival. Screening a library of more than 2,000 targeted compounds in a cell survival assay, combined with in silico and in vitro analysis of macrophage specificity, revealed the identification of three potent inhibitors: BIX-01294, GSK-J4, and Masitinib. All three compounds downregulated leukemia inhibitory factor receptor (LIFR), whose inhibition markedly reduced macrophage viability. In vivo, these inhibitors effectively depleted large peritoneal macrophages, ameliorated key symptoms of macrophage activation syndrome (MAS), and suppressed tumor growth in a syngeneic transplanted melanoma model as well as in an autochthonous lung cancer model. Together, these findings identify small molecule-mediated macrophage depletion as a promising therapeutic strategy and establish an experimental approach to uncover regulators of macrophage survival.

Lysine-directed covalent liganding offers a promising strategy to expand the covalently ligandable proteome beyond cysteine. However, broadly applicable and selective lysine-reactive scaffolds remain limited. Here, we designed SCL-alkyne, a simplified azaphilone probe derived from the natural product sclerotiorin (SCL), for the global profiling of lysine reactivity in bacteria. SCL-alkyne displayed high intrinsic selectivity for lysine in vitro and in live Escherichia coli cells. In situ proteome profiling revealed that 84% of engaged sites belong to lysine residues and the protein N-terminus. Reactivity mapping provided an inventory of highly reactive sites showing that only a limited subset of reactive lysines is located in functional regions of proteins. Analysis of proteins enriched via the SCL-alkyne probe unraveled bacterial chemotaxis as a major target pathway which was confirmed by an impaired chemotactic response upon treatment of bacteria with SCL-alkyne. Competitive profiling of three structurally related azaphilone natural products identified 60 protein targets belonging to pathways related to iron-sulfur cluster assembly and antioxidant function. This study not only highlights the diverse modes-of-action of natural product azaphilones, but also establishes its core scaffold as effective lysine-reactive chemotype for identifying ligandable lysines.

We aimed to repurpose the non-nucleoside reverse transcriptase (RT) inhibitor (NNRTI) rilpivirine (RPV) as a targeted protein degrader (TPD) of HIV-1 RT. Structure-guided modeling identified a TPD bifunctional linker exit trajectory from RPV that threads the NNRTI entrance channel. Ten RPV analogs (RPV') with varied warhead-linker attachments retained RT inhibition and antiviral activity, guiding selection of an amide-linked connector for degrader construction. We synthesized Proteolysis Targeting Chimeras (PROTACs) designed to recruit CUL4CRBN and CUL2VHL, alongside adamantyl acetic acid-based Hydrophobic Tags (HyTs). TPDs were evaluated for RT inhibition, virus inhibition, biophysical target engagement, and proteasome-dependent degradation. Some PROTACs showed minimal antiviral activity or limited solubility for our assays, whereas the HyT with a tetraethylene glycol (PEG4) linker (PEG4-Ad) exhibited low nanomolar potency to suppress HIV-1 replication and acceptable solubility. PEG4-Ad reduced RT levels in a proteasome-dependent manner without cytotoxicity but did not exhibit superior potency against RPV resistance mutations. MD simulations suggested that PEG4 linkers maximize episodic exposure of the hydrophobic tag, consistent with PEG4-Ad efficacy. These data highlight the promise - and constraints - of antiviral degraders, indicating that linker-controlled hydrophobic tag exposure and subcellular target accessibility may be critical design parameters for prospective therapeutics.

Cyclic peptides can engage targets beyond the reach of small molecules, but their discovery typically relies on libraries reused across targets, diversification around a known interaction motif, or computational methods limited to a handful of non-canonical building blocks. Here, we present nCycle-Forge, a simulated annealing framework that designs cyclic peptide binders by iteratively substituting building blocks and scoring each proposal by cofolding with the target. We designed, synthesized, and screened 1,472 cyclic peptides against the active-site pocket of Thrombin and the shallow p53-binding surface of MDM2 from the target sequence alone and without fixing binding mo-tifs. The library yielded chemically diverse hits against both targets in a single round without experimental optimization, with hit rates comparable to or up to 24-fold higher than in larger experimental libraries. Purified designs reached sub- to low-micromolar potency, with the best Thrombin inhibitor at Ki 0.14 M and the best MDM2 binder at EC50 2.4 M. Surface plasmon resonance confirmed direct binding, competition with or-thosteric inhibitors at both sites, and weaker binding under conditions expected to linearize the designs. nCycle-Forge requires no building block-specific parameterization, conformer generation, or retraining, and provides a target-focused route to functional cyclic peptides beyond the canonical amino acid alphabet.

Hypertriglyceridemia is commonly managed with lipid-lowering drugs such as statins; however, adverse effects, dose intolerance, and financial barriers may limit their use. Therefore, affordable and potentially safer plant-derived alternatives warrant investigation. This study evaluated the lipid-lowering effects of ethanol extracts of Fucus vesiculosus and Phytolacca berry, administered individually or in combination, in mice fed a butter-enriched diet for 12 weeks. Forty-eight mice were randomly assigned to six groups: normal control (Group 1), butter control (Group 2), statin control (Group 3), Fucus vesiculosus extract (Ext-1; Group 4), Phytolacca berry extract (Ext-2; Group 5), and the combined extracts (Group 6). Body weight, organ-to-body-weight ratios, serum lipid parameters, and histopathological changes were assessed. Group 3 showed the lowest final body weight, while Group 6 demonstrated a comparable body-weight trajectory. Organ-to-body-weight ratios varied among groups, with Group 3 generally showing the highest values and Group 6 comparatively lower ratios for several organs. Group 5 had the lowest total cholesterol concentration, followed by Group 3, whereas Group 6 showed cholesterol levels comparable to the normal control and statin groups. Notably, Group 6 exhibited the lowest serum triglyceride concentration (129.9 mg/dL). Histopathological examination revealed relatively mild hepatic alterations and limited vascular plaque formation in Group 6. The combined extracts demonstrated favorable effects on body-weight gain and serum lipid profiles, particularly triglycerides, with comparatively mild histopathological changes. Further mechanistic, dose-response, toxicity, and long-term studies are warranted before clinical application can be considered.